From 112e30af7b70fc7ba68f20e0fd5f00a260413e61 Mon Sep 17 00:00:00 2001 From: shubham0108 Date: Thu, 13 Jul 2017 11:54:28 +0530 Subject: [PATCH 1/6] First Commit --- data/ML_Data/Bag-Of-Features.yml | 15987 ++++++++++++++++ data/ML_Data/disp_var.dat | Bin 0 -> 462944 bytes data/ML_Data/images1.dat | Bin 0 -> 8768 bytes data/PCL-files/bunny.pcd | 407 + data/PCL-files/cube.ply | 24 + data/PCL-files/kumamon.pcd | Bin 0 -> 3477504 bytes etc/FOSSEE_Image_Processing_Toolbox.quit | 34 + etc/FOSSEE_Image_Processing_Toolbox.quit~ | 34 + etc/FOSSEE_Image_Processing_Toolbox.start | 82 + etc/FOSSEE_Image_Processing_Toolbox.start~ | 77 + etc/FOSSEE_Optimization_Toolbox.quit~ | 34 + etc/FOSSEE_Optimization_Toolbox.start~ | 85 + help/builder_help.sce | 21 + help/builder_help.sce~ | 21 + help/builder_helps.sce~ | 21 + help/en_US/CascadeObjectDetector.xml | 102 + help/en_US/adaptHistEq.xml | 77 + help/en_US/arrowedline.xml | 23 + help/en_US/bagOfFeatures.xml | 77 + help/en_US/blur.xml | 68 + 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     +
    inputImage: +

    input image on which the objects should be detected.

    +
    classifierList: +

    a matrix of strings containing the location of the xml files which are to be used in the detection.

    +
    scale: +

    Parameter specifying how much the image size is reduced at each image scale.

    +
    minNeighbors: +

    Parameter specifying how many neighbors each candidate rectangle should have to retain it.

    +
    flags: +

    the method used in detection.it should be either 1 or 4 or 2 or 8.

    +
    min size: +

    Minimum possible object size. Objects smaller than that are ignored.

    +
    max size: +

    Maximum possible object size. Objects larger than that are ignored.

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    + + + + +
    + << Calibrate + + + FOSSEE_Image_Processing_Toolbox + + + arrowedline >> + +
    +
    +
    + + + + FOSSEE_Image_Processing_Toolbox >> FOSSEE_Image_Processing_Toolbox > CascadeObjectDetector + +

    +

    CascadeObjectDetector

    +

    This function is used to detect objects in an image.

    + + +

    Calling Sequence

    + 
    detect=CascadeObjectDetector(inputImage,classifierList);
+detect=CascadeObjectDetector(inputImage,classifierList,scale);
+detect=CascadeObjectDetector(inputImage,classifierList,scale,minNeighbors);
+detect=CascadeObjectDetector(inputImage,classifierList,scale,minNeighbors,flags);
+detect=CascadeObjectDetector(inputImage,classifierList,scale,minNeighbors,flags,minSize);
+detect=CascadeObjectDetector(inputImage,classifierList,scale,minNeighbors,flags,minSize,maxSize);
    + +

    Parameters

    +
    out: +

    the output image with all specified detections.

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zK*|3Xg8x-L|NrT(71i7ezn?Pfuh_mdUDzGsZ#Kp6_q4e+9llsf&DJBf%2LJieQfC1 zjc~tZ2&NkjXiv3_O=##2JTEHw|5dmC [] ) then + add_help_chapter("FOSSEE_Image_Processing_Toolbox", path_addchapter, %F); + clear add_help_chapter; + end + clear path_addchapter; +end +end + +// add demos +// ============================================================================= + +if ( %t ) then +if or(getscilabmode() == ["NW";"STD"]) then + mprintf("\tLoad demos\n"); + //pathdemos = pathconvert(root_tlbx+"/demos/sci_FOSSEE_Image_Processing_Toolbox.dem.gateway.sce",%f,%t); + //add_demo("FOSSEE_Image_Processing_Toolbox",pathdemos); + //clear pathdemos ; +end +end + +// ============================================================================= + +clear etc_tlbx root_tlbx Version a opt lib_path; diff --git a/etc/FOSSEE_Image_Processing_Toolbox.start~ b/etc/FOSSEE_Image_Processing_Toolbox.start~ new file mode 100755 index 0000000..bf6a60e --- /dev/null +++ b/etc/FOSSEE_Image_Processing_Toolbox.start~ @@ -0,0 +1,77 @@ +// Copyright (C) 2017 - IIT Bombay - FOSSEE +// +// This file must be used under the terms of the BSD. +// This source file is licensed as described in the file LICENSE, which +// you should have received as part of this distribution. The terms +// are also available at +// https://opensource.org/licenses/BSD-3-Clause +// Author: Shamika Mohanan +// Organization: FOSSEE, IIT Bombay +// Email: toolbox@scilab.in + +mprintf("Start FOSSEE Image Processing Toolbox\n"); + +[a, opt] = getversion(); +Version = opt(2); + +etc_tlbx = get_absolute_file_path("FOSSEE_Image_Processing_Toolbox.start"); +etc_tlbx = getshortpathname(etc_tlbx); +root_tlbx = strncpy( etc_tlbx, length(etc_tlbx)-length("\etc\") ); + +//Load functions library +// ============================================================================= +mprintf("\tLoad macros\n"); +pathmacros = pathconvert( root_tlbx ) + "macros" + filesep(); +fipt_lib = lib(pathmacros); +clear pathmacros; + +// load gateways +// ============================================================================= + +mprintf("\tLoad gateways\n"); +[a, opt] = getversion(); +Version = opt(2); +ilib_verbose(0); +if getos()=="Windows" then +// lib_path = root_tlbx + "/thirdparty/windows/bin/" + Version;*/ +// link(lib_path+filesep()+"IpOptFSS.dll");*/ +// link(lib_path+filesep()+"IpOpt-vc10.dll");*/ +else + lib_path = root_tlbx + "/thirdparty/linux/lib/" + Version; +// lib_path="/usr/lib";*/ +// link(lib_path + "/libopencv_core.so");*/ +// link(lib_path + "/libopencv_highgui.so");*/ +// link(lib_path + "/libopencv_imgproc.so");*/ + +end +exec(pathconvert(root_tlbx + filesep() + "sci_gateway" + filesep() + "loader_gateway.sce",%f)); + +// Load and add help chapter +// ============================================================================= +if ( %t ) then +if or(getscilabmode() == ["NW";"STD"]) then + mprintf("\tLoad help\n"); + path_addchapter = pathconvert(root_tlbx+"/jar"); + if ( isdir(path_addchapter) <> [] ) then + add_help_chapter("FOSSEE_Image_Processing_Toolbox", path_addchapter, %F); + clear add_help_chapter; + end + clear path_addchapter; +end +end + +// add demos +// ============================================================================= + +if ( %t ) then +if or(getscilabmode() == ["NW";"STD"]) then + mprintf("\tLoad demos\n"); + //pathdemos = pathconvert(root_tlbx+"/demos/sci_FOSSEE_Image_Processing_Toolbox.dem.gateway.sce",%f,%t); + //add_demo("FOSSEE_Image_Processing_Toolbox",pathdemos); + //clear pathdemos ; +end +end + +// ============================================================================= + +clear etc_tlbx root_tlbx Version a opt lib_path; diff --git a/etc/FOSSEE_Optimization_Toolbox.quit~ b/etc/FOSSEE_Optimization_Toolbox.quit~ new file mode 100755 index 0000000..86ed18a --- /dev/null +++ b/etc/FOSSEE_Optimization_Toolbox.quit~ @@ -0,0 +1,34 @@ +// Copyright (C) 2015 - IIT Bombay - FOSSEE +// +// This file must be used under the terms of the BSD. +// This source file is licensed as described in the file LICENSE, which +// you should have received as part of this distribution. The terms +// are also available at +// https://opensource.org/licenses/BSD-3-Clause +// Author: Harpreet Singh +// Organization: FOSSEE, IIT Bombay +// Email: toolbox@scilab.in + + +function quitModule() + + etc_tlbx = get_absolute_file_path("FOSSEE_Optimization_Toolbox.quit"); + etc_tlbx = getshortpathname(etc_tlbx); + root_tlbx = strncpy( etc_tlbx, length(etc_tlbx)-length("\etc\") ); + + //unlink libraries + [bOK, ilib] = c_link('FOSSEE_Optimization_Toolbox'); + if bOK then + ulink(ilib); + end + + // Remove Preferences GUI + // ============================================================================= + if getscilabmode() == "STD" then + removeModulePreferences(root_tlbx); + end + ulink(); +endfunction + +clear quitModule; + diff --git a/etc/FOSSEE_Optimization_Toolbox.start~ b/etc/FOSSEE_Optimization_Toolbox.start~ new file mode 100755 index 0000000..f2a5a06 --- /dev/null +++ b/etc/FOSSEE_Optimization_Toolbox.start~ @@ -0,0 +1,85 @@ +// Copyright (C) 2017 - IIT Bombay - FOSSEE +// +// This file must be used under the terms of the BSD. +// This source file is licensed as described in the file LICENSE, which +// you should have received as part of this distribution. The terms +// are also available at +// https://opensource.org/licenses/BSD-3-Clause +// Author: Shamika Mohanan +// Organization: FOSSEE, IIT Bombay +// Email: toolbox@scilab.in + +mprintf("Start FOSSEE Image Processing Toolbox\n"); + +[a, opt] = getversion(); +Version = opt(2); + +etc_tlbx = get_absolute_file_path("FOSSEE_Image_Processing_Toolbox.start"); +etc_tlbx = getshortpathname(etc_tlbx); +root_tlbx = strncpy( etc_tlbx, length(etc_tlbx)-length("\etc\") ); + +//Load functions library +// ============================================================================= +mprintf("\tLoad macros\n"); +pathmacros = pathconvert( root_tlbx ) + "macros" + filesep(); +symphony_lib = lib(pathmacros); +clear pathmacros; + +// load gateways +// ============================================================================= + +mprintf("\tLoad gateways\n"); +[a, opt] = getversion(); +Version = opt(2); +ilib_verbose(0); +if getos()=="Windows" then + lib_path = root_tlbx + "/thirdparty/windows/bin/" + Version; + link(lib_path+filesep()+"IpOptFSS.dll"); + link(lib_path+filesep()+"IpOpt-vc10.dll"); +else + lib_path = root_tlbx + "/thirdparty/linux/lib/" + Version; + link(lib_path + "/libCoinUtils.so"); + link(lib_path + "/libClp.so"); + link(lib_path + "/libClpSolver.so"); + link(lib_path + "/libOsi.so"); + link(lib_path + "/libOsiCommonTests.so"); + link(lib_path + "/libOsiClp.so"); + link(lib_path + "/libCgl.so"); + link(lib_path + "/libSym.so"); + link(lib_path + "/libOsiSym.so"); + link(lib_path + "/libcoinblas.so"); + link(lib_path + "/libcoinlapack.so"); + link(lib_path + "/libcoinmumps.so"); + link(lib_path + "/libipopt.so"); +end +exec(pathconvert(root_tlbx + filesep() + "sci_gateway" + filesep() + "loader_gateway.sce",%f)); + +// Load and add help chapter +// ============================================================================= +if ( %t ) then +if or(getscilabmode() == ["NW";"STD"]) then + mprintf("\tLoad help\n"); + path_addchapter = pathconvert(root_tlbx+"/jar"); + if ( isdir(path_addchapter) <> [] ) then + add_help_chapter("FOSSEE_Optimization_Toolbox", path_addchapter, %F); + clear add_help_chapter; + end + clear path_addchapter; +end +end + +// add demos +// ============================================================================= + +if ( %t ) then +if or(getscilabmode() == ["NW";"STD"]) then + mprintf("\tLoad demos\n"); + pathdemos = pathconvert(root_tlbx+"/demos/sci_FOSSEE_Image_Processing_Toolbox.dem.gateway.sce",%f,%t); + add_demo("FOSSEE_Image_Processing_Toolbox",pathdemos); + clear pathdemos ; +end +end + +// ============================================================================= + +clear etc_tlbx root_tlbx Version a opt lib_path; diff --git a/help/builder_help.sce b/help/builder_help.sce new file mode 100755 index 0000000..4d4e031 --- /dev/null +++ b/help/builder_help.sce @@ -0,0 +1,21 @@ +// Copyright (C) 2015 - IIT Bombay - FOSSEE +// +// Author: Shamika Mohanan +// Organization: FOSSEE, IIT Bombay +// Email: toolbox@scilab.in +// This file must be used under the terms of the BSD. +// This source file is licensed as described in the file LICENSE, which +// you should have received as part of this distribution. The terms +// are also available at +// https://opensource.org/licenses/BSD-3-Clause + +mode(-1) +lines(0) + +toolbox_title = "FOSSEE_Image_Processing_Toolbox" + +help_dir = get_absolute_file_path('builder_help.sce'); + +tbx_builder_help_lang("en_US", help_dir); + +clear toolbox_title; diff --git a/help/builder_help.sce~ b/help/builder_help.sce~ new file mode 100755 index 0000000..da2f4f7 --- /dev/null +++ b/help/builder_help.sce~ @@ -0,0 +1,21 @@ +// Copyright (C) 2015 - IIT Bombay - FOSSEE +// +// Author: Harpreet Singh +// Organization: FOSSEE, IIT Bombay +// Email: harpreet.mertia@gmail.com +// This file must be used under the terms of the BSD. +// This source file is licensed as described in the file LICENSE, which +// you should have received as part of this distribution. The terms +// are also available at +// https://opensource.org/licenses/BSD-3-Clause + +mode(-1) +lines(0) + +toolbox_title = "FOSSEE_Optimization_Toolbox" + +help_dir = get_absolute_file_path('builder_help.sce'); + +tbx_builder_help_lang("en_US", help_dir); + +clear toolbox_title; diff --git a/help/builder_helps.sce~ b/help/builder_helps.sce~ new file mode 100755 index 0000000..da2f4f7 --- /dev/null +++ b/help/builder_helps.sce~ @@ -0,0 +1,21 @@ +// Copyright (C) 2015 - IIT Bombay - FOSSEE +// +// Author: Harpreet Singh +// Organization: FOSSEE, IIT Bombay +// Email: harpreet.mertia@gmail.com +// This file must be used under the terms of the BSD. +// This source file is licensed as described in the file LICENSE, which +// you should have received as part of this distribution. The terms +// are also available at +// https://opensource.org/licenses/BSD-3-Clause + +mode(-1) +lines(0) + +toolbox_title = "FOSSEE_Optimization_Toolbox" + +help_dir = get_absolute_file_path('builder_help.sce'); + +tbx_builder_help_lang("en_US", help_dir); + +clear toolbox_title; diff --git a/help/en_US/CascadeObjectDetector.xml b/help/en_US/CascadeObjectDetector.xml new file mode 100755 index 0000000..cc2aab3 --- /dev/null +++ b/help/en_US/CascadeObjectDetector.xml @@ -0,0 +1,102 @@ + + + + + + + + CascadeObjectDetector + This function is used to detect objects in an image. + + + + + Calling Sequence + + + detect=CascadeObjectDetector(inputImage,classifierList); + detect=CascadeObjectDetector(inputImage,classifierList,scale); + detect=CascadeObjectDetector(inputImage,classifierList,scale,minNeighbors); + detect=CascadeObjectDetector(inputImage,classifierList,scale,minNeighbors,flags); + detect=CascadeObjectDetector(inputImage,classifierList,scale,minNeighbors,flags,minSize); + detect=CascadeObjectDetector(inputImage,classifierList,scale,minNeighbors,flags,minSize,maxSize); + + + + + + Parameters + + out: + the output image with all specified detections. + inputImage: + input image on which the objects should be detected. + classifierList: + a matrix of strings containing the location of the xml files which are to be used in the detection. + scale: + Parameter specifying how much the image size is reduced at each image scale. + minNeighbors: + Parameter specifying how many neighbors each candidate rectangle should have to retain it. + flags: + the method used in detection.it should be either 1 or 4 or 2 or 8. + min size: + Minimum possible object size. Objects smaller than that are ignored. + max size: + Maximum possible object size. Objects larger than that are ignored. + + + + + Description + + + +This function is used to detect objects in an image. + + + + + + + Examples + + + diff --git a/help/en_US/adaptHistEq.xml b/help/en_US/adaptHistEq.xml new file mode 100644 index 0000000..1b87fbf --- /dev/null +++ b/help/en_US/adaptHistEq.xml @@ -0,0 +1,77 @@ + + + + + + + + adaptHistEq + Performs Contrast Limited Adaptive Histogram Equalisation + + + + + Calling Sequence + + outputImage = adaptHistEq(inputImage) + outputImage = adaptHistEq(inputImage, clip_limit) + + + + + + Parameters + + inputImage : + The input image on which histogram equalisation is to be implemented + clip_limit : + The target hgram bins. + + + + + Description + +As an alternative to using histeq, you can perform contrast-limited adaptive histogram equalization (CLAHE) using the adapthisteq function. While histeq works on the entire image, adapthisteq operates on small regions in the image, called tiles. Each tile's contrast is enhanced, so that the histogram of the output region approximately matches a specified histogram. After performing the equalization, adapthisteq combines neighboring tiles using bilinear interpolation to eliminate artificially induced boundaries. + + + + + + + Examples + + + + + Examples + + + + + Authors + + Shubham Lohakare, NITK Surathkal + Yash Balghat + + + diff --git a/help/en_US/arrowedline.xml b/help/en_US/arrowedline.xml new file mode 100755 index 0000000..35e4553 --- /dev/null +++ b/help/en_US/arrowedline.xml @@ -0,0 +1,23 @@ + + + + + + + + arrowedline + + + + diff --git a/help/en_US/bagOfFeatures.xml b/help/en_US/bagOfFeatures.xml new file mode 100755 index 0000000..d2430f8 --- /dev/null +++ b/help/en_US/bagOfFeatures.xml @@ -0,0 +1,77 @@ + + + + + + + + bagOfFeatures + This function is used to create a Bag-of-Words model (BoW model). + + + + + Calling Sequence + + bag = bagOfFeatures(imgSet); + bag = bagOfFeatures(imgSet, Name, Value, ...); + + + + + + Parameters + + bag: + Bag of visual words + imgSet: + An imageSet structure + VocabularySize: + (Optional) Number of visual words (Default- 500) + StrongestFeatures: + (Optional) Fraction of strongest features (Default- 1.0) + Upright: + (Optional) Orientation of SURF feature vector (Default- true) + Verbose: + (Optional) Enable progress display to screen (Default- true) + + + + + Description + +BoW model is applied to classify images by treating image features as words. The bagOfFeatures object contains a bag of visual words that help in image classification. + + + + + + + Examples + + + + + Authors + + Rohit Suri + Umang Agrawal + + + diff --git a/help/en_US/blur.xml b/help/en_US/blur.xml new file mode 100755 index 0000000..ff16114 --- /dev/null +++ b/help/en_US/blur.xml @@ -0,0 +1,68 @@ + + + + + + + + blur + This function is used to blur an image using the normalized box filter. + + + + + Calling Sequence + + B = blur(input_image ,ksize_width,ksize_height,anchorX,anchorY); + + + + + + Parameters + + A: + image matrix of the source image. + ksize_width : + Defines the width of the kernel to be used in pixels. + ksize_width : + Defines the height of the kernel to be used in pixels. + anchorX : + Indicates where the x coordinate of the anchor point (the pixel evaluated) is located with respect to the neighborhood. If there is a negative value, then the center of the kernel is considered the anchor point. + anchorY : + Indicates where the y coordinate of the anchor point (the pixel evaluated) is located with respect to the neighborhood. If there is a negative value, then the center of the kernel is considered the anchor point. + B : + output image with the applied blur fucntion. + + + + + Description + +The function smoothes an image using the kernel specified with its dimesnsions. + + + + + + + Examples + + + diff --git a/help/en_US/boxfilter.xml b/help/en_US/boxfilter.xml new file mode 100644 index 0000000..535b505 --- /dev/null +++ b/help/en_US/boxfilter.xml @@ -0,0 +1,86 @@ + + + + + + + + boxfilter + Blurs an image using the box filter. + + + + + Calling Sequence + + outputImage = boxfilter(InputArraysrc, intddepth,size1x,size1y,pointx,pointy, bool_normalize) + + + + + + Parameters + + InputArraysrc : + Input image to be blurred + intddepth : + The output image depth (-1 to use src.depth()) + size1x : + Width for the blurring kernel size + size1y : + Height for the blurring kernel size + pointx : + x-coordinate for anchor point (Default value -1) + pointy : + y-coordinate for anchor point (Default value -1) + bool_normalize : + flag, specifying whether the kernel is normalized by its area or not + + + + + Description + +Unnormalized box filter is useful for computing various integral characteristics over each pixel neighborhood, such as covariance matrices of image derivatives (used in dense optical flow algorithms, and so on). + + + + + + + Examples + + + + + Examples + + + + + Authors + + Shubham Lohakare, NITK Surathkal + Priyanka Hiranandani, NIT Surat + + + diff --git a/help/en_US/build_help.sce b/help/en_US/build_help.sce new file mode 100755 index 0000000..ad64f19 --- /dev/null +++ b/help/en_US/build_help.sce @@ -0,0 +1,17 @@ +// Copyright (C) 2015 - IIT Bombay - FOSSEE +// +// Author: Shamika Mohanan +// Organization: FOSSEE, IIT Bombay +// Email: toolbox@scilab.in +// This file must be used under the terms of the BSD. +// This source file is licensed as described in the file LICENSE, which +// you should have received as part of this distribution. The terms +// are also available at +// https://opensource.org/licenses/BSD-3-Clause +TOOLBOX_TITLE="FOSSEE_Image_Processing_Toolbox" +help_lang_dir = get_absolute_file_path('build_help.sce'); + +tbx_build_help(TOOLBOX_TITLE, help_lang_dir); + +clear help_lang_dir; + diff --git a/help/en_US/build_help.sce~ b/help/en_US/build_help.sce~ new file mode 100755 index 0000000..0205c56 --- /dev/null +++ b/help/en_US/build_help.sce~ @@ -0,0 +1,17 @@ +// Copyright (C) 2015 - IIT Bombay - FOSSEE +// +// Author: Shamika Mohanan +// Organization: FOSSEE, IIT Bombay +// Email: harpreet.mertia@gmail.com +// This file must be used under the terms of the BSD. +// This source file is licensed as described in the file LICENSE, which +// you should have received as part of this distribution. The terms +// are also available at +// https://opensource.org/licenses/BSD-3-Clause + +help_lang_dir = get_absolute_file_path('build_help.sce'); + +tbx_build_help(TOOLBOX_TITLE, help_lang_dir); + +clear help_lang_dir; + diff --git a/help/en_US/circle.xml b/help/en_US/circle.xml new file mode 100755 index 0000000..5721562 --- /dev/null +++ b/help/en_US/circle.xml @@ -0,0 +1,84 @@ + + + + + + + + circle + This function circle draws a simple or filled circle on an image with a given center and radius. + + + + + Calling Sequence + + cir=circle(inputImage,xcor,ycor,radius,r,g,b); + cir=circle(inputImage,xcor,ycor,radius,r,g,b,thickness); + cir=circle(inputImage,xcor,ycor,radius,r,g,b,thickness,linetype); + cir=circle(inputImage,xcor,ycor,radius,r,g,b,thickness,linetype,shift); + + + + + + Parameters + + cir: + The output image with the circle drawn in it. + inputImage: + The input image on which the circle should be drawn. + xcor: + X-coordinate of the center + ycor: + Y-coordinate of the center + r: + red color value of the circle.It should be in the range 0-255. + b: + blue color value of the circle.It should be in the range 0-255. + g: + green color value of the circle.It should be in the range 0-255. + thickness: + Line thickness. + linetype: + Type of the circle boundary.It can be 0 or 4 or 8. + shift: + Number of fractional bits in the point coordinates. + + + + + Description + +This function circle draws a simple or filled circle on an image with a given center and radius. + + + + + + + + + Examples + + + diff --git a/help/en_US/correctMatches.xml b/help/en_US/correctMatches.xml new file mode 100755 index 0000000..cd99c0f --- /dev/null +++ b/help/en_US/correctMatches.xml @@ -0,0 +1,64 @@ + + + + + + + + correctMatches + This function Refines coordinates of corresponding points using openCV's functions. + + + + + Calling Sequence + + [newPoints1, newPoints2] = correctMatches(F, points1, points2) + + + + + + Parameters + + + + + + Description + +The function implements the Optimal Triangulation Method (see Multiple View Geometry for details). For each given point correspondence points1[i] <-> points2[i], and a fundamental matrix F, it computes the corrected correspondences newPoints1[i] <-> newPoints2[i] that minimize the geometric error d(points1[i], newPoints1[i])^2 + d(points2[i],newPoints2[i])^2 (where d(a,b) is the geometric distance between points a and b ) subject to the epipolar constraint newPoints2^T * F * newPoints1 = 0 . + + + + + + + Examples + + + diff --git a/help/en_US/cvtColor.xml b/help/en_US/cvtColor.xml new file mode 100755 index 0000000..54caaf3 --- /dev/null +++ b/help/en_US/cvtColor.xml @@ -0,0 +1,122 @@ + + + + + + + + cvtColor + This function is used to transform a image from one space to other like rgb to gray and vice versa. + + + + + Calling Sequence + + + inputImage=imread("lena.jpeg"); + outputImage=cvtColor(inputImage,codeString); + outputImage=cvtColor(inputImage,codeString,dstCn); + + + + + + + Parameters + + dstCn: + number of channels in the destination image; if the parameter is 0, the number of the channels is derived automatically from src and code + codeString: + A string which specifies the type of conversion.The different types are listed below. + "CV_BGR2GRAY": + Conversion is from BGR(blue-green-red) space to GRAY. + "CV_RGB2GRAY": + Conversion is from RGB(red-green-blue) space to GRAY. + "CV_GRAY2BGR": + Conversion is from BGR(blue-green-red) space. + "CV_GRAY2RGB": + Conversion is from to GRAY to RGB(blue-green-red) space. + "CV_BGR2XYZ" : + Conversion is from BGR(blue-green-red) space to CIE XYZ. + "CV_RGB2XYZ" : + Conversion is from RGB(red-green-blue) space to CIE XYZ. + "CV_XYZ2BGR" : + Conversion is from to CIE XYZ to BGR space. + "CV_XYZ2RGB" : + Conversion is from to CIE XYZ to RGB(red-green-blue) space. + "CV_BGR2YCrCb": + Conversion is from BGR(blue-green-red) space to luma-chroma. + "CV_RGB2YCrCb" : + Conversion is from RGB(red-green-blue) space to luma chroma. + "CV_YCrCb2BGR" : + Conversion is from luma-chroma to BGR(blue-green-red) space. + "CV_YCrCb2RGB" : + Conversion is from luma-chroma to RGB(red-green-blue) space. + "CV_BGR2HSV": + Conversion is from BGR(blue-green-red) space to HSV. + "CV_RGB2HSV": + Conversion is from RGB space to HSV. + "CV_HSV2BGR": + Conversion is from to HSV to BGR(blue-green-red) space. + "CV_HSV2RGB": + Conversion is from to HSV to RGB(red-green-blue) space. + "CV_BGR2HLS": + Conversion is from BGR(blue-green-red) space to HLS. + "CV_RGB2HLS": + Conversion is from RGB space to HSV. + "CV_HLS2BGR": + Conversion is from HLS to BGR(blue-green-red) space. + "CV_HLS2RGB": + Conversion is from HLS to RGB(red-green-blue) space. + "CV_BGR2Lab": + Conversion is from BGR(blue-green-red) space to CIE Lab. + "CV_RGB2Lab": + Conversion is from RGB space to CIE Lab. + "CV_Lab2BGR": + Conversion is from CIE Lab to BGR(blue-green-red) space. + "CV_Lab2RGB": + Conversion is from CIE Lab to RGB space. + "CV_BGR2Luv": + Conversion is from BGR(blue-green-red) space to CIE Luv. + "CV_RGB2Luv": + Conversion is from RGB space to CIE Luv. + "CV_Luv2BGR": + Conversion is from CIE Luv to BGR(blue-green-red) space. + "CV_Luv2RGB": + Conversion is from CIE Luv to RGB space. + + + + + Description + + + +This function is used to transform a image from one space to other like rgb to gray and vice versa. + + + + + + + Examples + + + diff --git a/help/en_US/deconvlucy.xml b/help/en_US/deconvlucy.xml new file mode 100755 index 0000000..e38df1a --- /dev/null +++ b/help/en_US/deconvlucy.xml @@ -0,0 +1,65 @@ + + + + + + + + deconvlucy + This function is used to Deblur image using Lucy-Richardson method + + + + + Calling Sequence + + J = deconvlucy(I1, I2); + J = deconvlucy(I1, I2, NUMIT) + + + + + + Parameters + + I1: + image matrix of the source image . + I2: + image matrix of the source image from last iteraion. + NUMIT: + The number if iterations specified to achieve the desired result. + B : + output image in the deconvoluted form. + + + + + Description + +J = deconvlucy(I, PSF, NUMIT) specifies the number of iterations the deconvlucy function performs. If this value is not specified, the default is 10. + + + + + + + Examples + + + diff --git a/help/en_US/demosaic.xml b/help/en_US/demosaic.xml new file mode 100755 index 0000000..14b34bf --- /dev/null +++ b/help/en_US/demosaic.xml @@ -0,0 +1,66 @@ + + + + + + + + demosaic + This function converts the Bayer pattern encoded image to the truecolor image, RGB. + + + + + Calling Sequence + + image=imread("lena.jpeg",0) + dem=demosaic(image,"gbrg"); + dem=demosaic(image,"bggr"); + dem=demosaic(image,"rggb"); + dem=demosaic(image,"grbg"); + + + + + + Parameters + + dem: + the output image + image: + the image which should be converted. + + + + + Description + + + +This function converts the Bayer pattern encoded image to the truecolor image, RGB. + + + + + + + Examples + + + diff --git a/help/en_US/denoiseColor.xml b/help/en_US/denoiseColor.xml new file mode 100644 index 0000000..d58f39e --- /dev/null +++ b/help/en_US/denoiseColor.xml @@ -0,0 +1,91 @@ + + + + + + + + denoiseColor + Removes colored noise from the image + + + + + Calling Sequence + + outputImage = denoiseColor(src, strengthFilter,strengthFilterColor, tempWindowSize, searchWindowSize) + + + + + + Parameters + + src : + The input image with colored noise. + strengthFilter : + The noise filter for white gaussian noise. + strengthFilterColor : + The noise filter for colored noise. + tempWindowSize : + Size in pixels of the template patch that is used to compute weights. Should be odd. + searchWindowSize : + Size in pixels of the window that is used to compute weighted average for given pixel. Should be odd. + + + + + Description + +The function is used to remove colored noise from an image. It is the modification of fasNlmeansDenoising function +The output is a denoised image + + + + + + + Examples + + + + + Examples + + + + + Authors + + Shubham Lohakare, NITK Surathkal + Ashish Mantosh Barik, NIT Rourkela + + + diff --git a/help/en_US/detectMinEigenFeatures.xml b/help/en_US/detectMinEigenFeatures.xml new file mode 100755 index 0000000..597f8b6 --- /dev/null +++ b/help/en_US/detectMinEigenFeatures.xml @@ -0,0 +1,66 @@ + + + + + + + + detectMinEigenFeatures + This function is used to find corner points in an image using Minimum Eigen Value algorithm. + + + + + Calling Sequence + + points = detectMinEigenFeatures(I); + points = detectMinEigenFeatures(I, Name, Value, ...); + + + + + + Parameters + + points: + Structure of corner points + I: + Input image to detectHarrisFeatures() + MinQuality: + (Optional) Minimum accepted quality of corners (Default- 0.01) + FilterSize: + (Optional) Dimension of Gaussian Filter (Default: 5) + ROI: + (Optional) Rectangular region for corner detection + + + + + Description + +This function detects corners in an image I. These corner points are used to extract features and hence recognize the contents of an image. + + + + + + + Examples + + + diff --git a/help/en_US/ellipse.xml b/help/en_US/ellipse.xml new file mode 100755 index 0000000..1149ec7 --- /dev/null +++ b/help/en_US/ellipse.xml @@ -0,0 +1,93 @@ + + + + + + + + ellipse + This function draws a simple or thick elliptic arc or fills an ellipse sector. + + + + + Calling Sequence + + elli=ellipse(inputImage,xcor,ycor,firstAxis,secondAxis,angle,startAngle,endAngle,r,g,b); + elli=ellipse(inputImage,xcor,ycor,firstAxis,secondAxis,angle,startAngle,endAngle,r,g,b,thickness); + elli=ellipse(inputImage,xcor,ycor,firstAxis,secondAxis,angle,startAngle,endAngle,r,g,b,thickness,linetype); + elli=ellipse(inputImage,xcor,ycor,firstAxis,secondAxis,angle,startAngle,endAngle,r,g,b,thickness,linetype,shift); + + + + + + Parameters + + elli: + The output image with the ellipse drawn in it. + inputImage: + The input image on which the ellipse should be drawn. + xcor: + X-coordinate of the center + ycor: + Y-coordinate of the center + firstAxis: + the first axis of the ellipse. + secondAxis: + the second axis of the ellipse. + angle: + Ellipse rotation angle in degrees. + startAngle: + Starting angle of the elliptic arc in degrees. + endAngle: + Ending angle of the elliptic arc in degrees. + r: + red color value of the ellipse.It should be in the range 0-255. + b: + blue color value of the ellipse.It should be in the range 0-255. + g: + green color value of the ellipse.It should be in the range 0-255. + thickness: + Line thickness. + linetype: + Type of the ellipse boundary.It can be 0 or 4 or 8. + shift: + Number of fractional bits in the point coordinates. + + + + + Description + + + +This function draws a simple or thick elliptic arc or fills an ellipse sector. + + + + + + + Examples + + + diff --git a/help/en_US/erode.xml b/help/en_US/erode.xml new file mode 100755 index 0000000..7c62b9a --- /dev/null +++ b/help/en_US/erode.xml @@ -0,0 +1,73 @@ + + + + + + + + erode + This function Erodes an image by using a specific structuring element. + + + + + Calling Sequence + + + z=imread("lena.jpeg"); + ero=erode(inputImage,kernel,anchorX,anchorY,iterations); + + + + + + Parameters + + z: + input image which should be eroded. + ero: + the output eroded image + kernel: + structuring element used for erosion + anchorX: + x coordinate of Anchor. + anchorY: + y coordinate of Anchor. + Anchor: + position of the anchor within the element. + Iterations: + number of times erosion is applied. + + + + + Description + + + +This function Erodes an image by using a specific structuring element. + + + + + + + Examples + + + diff --git a/help/en_US/estimateFundamentalMat.xml b/help/en_US/estimateFundamentalMat.xml new file mode 100755 index 0000000..0629254 --- /dev/null +++ b/help/en_US/estimateFundamentalMat.xml @@ -0,0 +1,68 @@ + + + + + + + + estimateFundamentalMat + It returns the 3-by-3 fundamental matrix corresponding to the input points + + + + + Calling Sequence + + fundamentalMat=estimateFundamentalMatrix(matchedPoints1,matchedPoints2); + fundamentalMat=estimateFundamentalMatrix(matchedPoints1,matchedPoints2,'method','RANSAC','param1',2,'param2',0.99); + + + + + + Parameters + + matchedPoints1: + M-by-2 array of first image points. These points can be SURFPoints, MSERRegions, cornerPoints. + matchedPoints2: + M-by-2 array of the second image points of the same size and format as matchedPoints1. + method: + method for computing fundamental matrix. Possible methods are 7POINT,8POINT,RANSAC,LMEDS and RANSAC is the default one. + param1: + It indiacates maximum distance from a point to an epipolar line in pixels + param2: + It specifies a desirable level of confidence + + + + + Description + +estimateFundamentalMatrix function calculates a fundamental matrix from the corresponding points in two images. + + + + + + + Examples + + + diff --git a/help/en_US/fastNlMeansDenoising.xml b/help/en_US/fastNlMeansDenoising.xml new file mode 100644 index 0000000..37bafbd --- /dev/null +++ b/help/en_US/fastNlMeansDenoising.xml @@ -0,0 +1,90 @@ + + + + + + + + fastNlMeansDenoising + Removes gaussian white noise from images + + + + + Calling Sequence + + outputImage=fastNlMeansDenoising(src, strengthFilter, tempWindowSize, searchWindowSize, choice) + + + + + + Parameters + + src : + Input 8-bit 1-channel, 2-channel, 3-channel or 4-channel image. + strengthFilter : + Parameter regulating filter strength. + templateWindowSize : + Size in pixels of the template patch that is used to compute weights. Should be odd. + searchWindowSize : + Size in pixels of the window that is used to compute weighted average for given pixel. Should be odd. + choice : + Chooses the method + + + + + Description + +Perform image denoising using Non-local Means Denoising algorithm with several computational optimizations. Noise expected to be a gaussian white noise. + + + + + + + Examples + + + + + Examples + + + + + Authors + + Shubham Lohakare, NITK Surathkal + Ashish Mantosh, NIT Rourkela + + + diff --git a/help/en_US/findContours.xml b/help/en_US/findContours.xml new file mode 100644 index 0000000..5a84e7d --- /dev/null +++ b/help/en_US/findContours.xml @@ -0,0 +1,92 @@ + + + + + + + + findContours + Finds contours in an image + + + + + Calling Sequence + + outputMat = findContours(inputImage, Mode, method, point_x, point_y) + + + + + + Parameters + + inputImage : + The input image + Mode : + Contour retrieval mode (Enter 1 for CV_RETR_EXTERNAL, 2 for CV_RETR_LIST, 3 for CV_RETR_CCOMP, 4 for CV_RETR_TREE) + method : + Contour approximation method (Enter 1 for CV_CHAIN_APPROX_NONE, 2 for CV_CHAIN_APPROX_SIMPLE, 3 for CV_CHAIN_APPROX_TC89_L1, 4 for CV_CHAIN_APPROX_TC89_KCOS) + point_x : + x-coordinate for point offset + point_y : + y-coordinate for point offset + + + + + Description + +The function retrieves contours from the images using the algorithm [Suzuki85]. The contours are a useful tool for shape analysis and object detection and recognition. + + + + + + + Examples + + + + + Examples + + + + + Examples + + + + + Authors + + Abhilasha Sancheti + Shubham Lohakare + Sukul Bagai + + + diff --git a/help/en_US/findHomography.xml b/help/en_US/findHomography.xml new file mode 100755 index 0000000..97fa2cf --- /dev/null +++ b/help/en_US/findHomography.xml @@ -0,0 +1,76 @@ + + + + + + + + findHomography + This Function Finds a perspective transformation between two planes. + + + + + Calling Sequence + + homographyMatrix=findHomography(points1,points2); + homographyMatrix=findHomography(points1,points2,method); + homographyMatrix=findHomography(points1,points2,method,threshold); + + + + + + Parameters + + homographyMatrix: + perspective transformation H between the source and the destination planes + points1: + Coordinates of the points in the original plane + points2: + Coordinates of the points in the target plane + method: + Method used to computed a homography matrix. + threshold: + Maximum allowed reprojection error to treat a point pair as an inlier. + Note: + the number of points should be same in the points1 and points2 + + + + + Description + +The function finds and returns the perspective transformation H between the source and the destination planes + + + + + + + Examples + + + diff --git a/help/en_US/fitellipse.xml b/help/en_US/fitellipse.xml new file mode 100755 index 0000000..6355085 --- /dev/null +++ b/help/en_US/fitellipse.xml @@ -0,0 +1,66 @@ + + + + + + + + fitellipse + The function calculates the ellipse that fits (in a least-squares sense) a set of 2D points best of all. + + + + + Calling Sequence + + + felli=fitellipse(points); + + + + + + Parameters + + felli: + a struct containing all the details about the ellipse Params. + points: + Input 2D point set + + + + + Description + + + +The function calculates the ellipse that fits (in a least-squares sense) a set of 2D points best of all. + + + + + + + Examples + + + diff --git a/help/en_US/graycoprops.xml b/help/en_US/graycoprops.xml new file mode 100755 index 0000000..b85f0c3 --- /dev/null +++ b/help/en_US/graycoprops.xml @@ -0,0 +1,79 @@ + + + + + + + + graycoprops + + + + + + Calling Sequence + + z=imread("lena.jpeg"); //in grayscale or color + //Note: z can be a image or simply a Matrix. + gray=graycoprops(z) //get all 4 properties + gray=graycoprops(z,"contrast") //compute only contrast + gray=graycoprops(z,["contrast" "energy"]) //compute contrast and energy.the properties can be passed in any order + gray=graycoprops(z,["contrast" "correlation" "energy"]) + gray=graycoprops(z,["contrast" "correlation" "energy" "homogeneity"]) + + + + + + Parameters + + gray: + A struct containing all the parameters + z: + A image or a matrix + contrast: + a measure of the intensity contrast between a pixel and its neighbor over the whole image. + energy: + the sum of squared elements + homogeneity: + a value that measures the closeness of the distribution of elements. + correlation: + a measure of how correlated a pixel is to its neighbor over the whole image + + + + + Description + +This function computes the Properties of gray-level co-occurrence matrix.The properties being "correlation","contrast","energy" and "homogeneity". + + + + + + + + + Examples + + + diff --git a/help/en_US/histeq.xml b/help/en_US/histeq.xml new file mode 100644 index 0000000..455b596 --- /dev/null +++ b/help/en_US/histeq.xml @@ -0,0 +1,86 @@ + + + + + + + + histeq + Equalizes the histogram of an image + + + + + Calling Sequence + + outputImage = histeq (inputImage) + + + + + + Parameters + + inputImage : + The input image for which the histogram has to be equalised + + + + + Description + +The function equalizes the histogram of the input image using the following algorithm: 1. Calculate the histogram H for src. 2. Normalize the histogram so that the sum of histogram bins is 255. 3. Compute the integral of the histogram. 4. Transform the image using H' as a look-up table: dst(x,y) = H'(src(x,y)). The algorithm normalizes the brightness and increases the contrast of the image. + + + + + + + Examples + + + + + Examples + + + + + Examples + + + + + Authors + + Shubham Lohakare, NITK Surathkal + Priyanka Hiranandani, NIT Surat + + + diff --git a/help/en_US/imadd.xml b/help/en_US/imadd.xml new file mode 100644 index 0000000..aaa4d44 --- /dev/null +++ b/help/en_US/imadd.xml @@ -0,0 +1,79 @@ + + + + + + + + imadd + Add the contents of 2 matrices or images and store it in another + + + + + Calling Sequence + + outputMat = imadd(input1, input2) + + + + + + Parameters + + input1 : + First input matrix or an image + input2 : + Second input matrix or image + + + + + Description + +Z = imadd(X,Y) adds each element in array X with the corresponding element in array Y and returns the sum in the corresponding element of the output array Z. X and Y are real, nonsparse numeric arrays with the same size and class, or Y is a scalar double. Z has the same size and class as X, unless X is logical, in which case Z is double. + + + + + + + Examples + + + + + Examples + + + + + Authors + + Tess Zacharias + Shubham Lohakare + + + diff --git a/help/en_US/imcomplement.xml b/help/en_US/imcomplement.xml new file mode 100644 index 0000000..c4353c8 --- /dev/null +++ b/help/en_US/imcomplement.xml @@ -0,0 +1,76 @@ + + + + + + + + imcomplement + Computes the complement of the image + + + + + Calling Sequence + + compMat = imcomplement(srcImg) + + + + + + Parameters + + srcImg : + Input image + + + + + Description + +In the complement of a binary image, zeros become ones and ones become zeros; black and white are reversed. In the complement of an intensity or RGB image, each pixel value is subtracted from the maximum pixel value supported by the class (or 1.0 for double-precision images) and the difference is used as the pixel value in the output image. In the output image, dark areas become lighter and light areas become darker. + + + + + + + Examples + + + + + Examples + + + + + Authors + + Tess Zacharias + Shubham Lohakare + + + diff --git a/help/en_US/imcontour.xml b/help/en_US/imcontour.xml new file mode 100644 index 0000000..3c6533e --- /dev/null +++ b/help/en_US/imcontour.xml @@ -0,0 +1,86 @@ + + + + + + + + imcontour + Draws a contour plot for the input image + + + + + Calling Sequence + + contourMat = imcontour(srcImg) + + + + + + Parameters + + srcImg : + THe input image + + + + + Description + +The function draws contour outlines in the image. + + + + + + + Examples + + + + + Examples + + + + + Examples + + + + + Authors + + Tess zacharias + Shubham Lohakare + + + diff --git a/help/en_US/imdecolor.xml b/help/en_US/imdecolor.xml new file mode 100644 index 0000000..48d6b21 --- /dev/null +++ b/help/en_US/imdecolor.xml @@ -0,0 +1,85 @@ + + + + + + + + imdecolor + Decolors and color boosts an image giving 2 outputs for the same respectively. + + + + + Calling Sequence + + [outImg1, outImg2] = imdecolor(srcImg1) + + + + + + Parameters + + srcImg1 : + It is a 3-channel input image. + outImg1 : + It is a grayscale image of the image passed as input. + outImg2 : + It is a color boosted image of the image passed as input. + + + + + Description + +This function is used to decolor an image and also add a boost to it's color +The output are 2 images, one is a grayscale and the other is a color boosted image + + + + + + + Examples + + + + + Examples + + + + + Authors + + Shubham Lohakare, NITK Surathkal + Ashish Mantosh, NIT Rourkela + + + diff --git a/help/en_US/imfill.xml b/help/en_US/imfill.xml new file mode 100644 index 0000000..106c15d --- /dev/null +++ b/help/en_US/imfill.xml @@ -0,0 +1,89 @@ + + + + + + + + imfill + Fills in the regions and holes in an image. + + + + + Calling Sequence + + [outputImage] = imfill(srcImg) + [outputImage] = imfill(srcImg,locations) + + + + + + Parameters + + srcImg : + It is the input image + locations : + If locations is a P-by-1 vector, it contains the linear indices of starting locations. If locations is P-by-ndims(BW) matrix, each row contains the array indices of one of the starting locations. + + + + + Description + +The function performs a flood-fill operation on the pixels of the input image. + + + + + + + Examples + + + + + Examples + + + + + Examples + + + + + Authors + + Vinay Bhat + Shubham Lohakare + + + diff --git a/help/en_US/iminpaint.xml b/help/en_US/iminpaint.xml new file mode 100644 index 0000000..6c54ef6 --- /dev/null +++ b/help/en_US/iminpaint.xml @@ -0,0 +1,86 @@ + + + + + + + + iminpaint + Inpaints the unwanted area in an image using the neighboring pixel points + + + + + Calling Sequence + + pImg = iminpaint(srcImg1,maskedRectangle,radius,methodNum) + + + + + + Parameters + + srcImg : + It is the input image + maskedRectangle: + It is a vector of double used which contains the co-ordinates of the masking rectangle + radius : + Radius of a circular neighborhood of each point inpainted that is considered by the algorithm. + methodNum : + Inpainting method that could be one of the following,INPAINT_NS Navier-Stokes based method or INPAINT_TELEA Method by Alexandru Telea + + + + + Description + +The function reconstructs the selected image area from the pixel near the area boundary. The function may be used to remove dust and scratches from a scanned photo, or to remove undesirable objects from still images. + + + + + + + Examples + + + + + Examples + + + + + Authors + + Shubham Lohakare, NITK Surathkal + Ashish Mantosh, NIT Rourkela + + + diff --git a/help/en_US/immultiply.xml b/help/en_US/immultiply.xml new file mode 100644 index 0000000..29895ad --- /dev/null +++ b/help/en_US/immultiply.xml @@ -0,0 +1,89 @@ + + + + + + + + immultiply + Multiply the contents of 2 matrices and store it in another + + + + + Calling Sequence + + multiplyMat = immultiply(input1, input2) + + + + + + Parameters + + input1 : + First input matrix or an image + input2 : + Second input matrix or image + + + + + Description + +p=immultiply(a,b) multiplies each of the element in the first argument's array with the corrresponding element in the second argument's array and the answer is stored in p. + + + + + + + Examples + + + + + Examples + + + + + Examples + + + + + Authors + + Tess Zacharias + Shubham Lohakare + + + diff --git a/help/en_US/imread.xml b/help/en_US/imread.xml new file mode 100755 index 0000000..5368203 --- /dev/null +++ b/help/en_US/imread.xml @@ -0,0 +1,90 @@ + + + + + + + + imread + + + + + + Calling Sequence + + image=imread("image_path"); + image=imread("image_path",options) + + + + + + Parameters + + image_path: + a String which contains the path of the image that is to be read. + options: + an Integer, containing the option for user to specify. See below for details. + 0 : + convert image to the single channel grayscale image. + 1 : + convert image to the 3 channel BGR color image. + 2 : + load 16-bit/32-bit image when the input image has the corresponding depth, otherwise convert it to 8-bit. + 4 : + the image is read in any possible color format. + 8 : + use the gdal driver for loading the image. + 16 : + convert image to the single channel grayscale image and the image size reduced 1/2. + 17 : + convert image to the 3 channel BGR color image and the image size reduced 1/2. + 32 : + convert image to the single channel grayscale image and the image size reduced 1/4. + 33 : + convert image to the 3 channel BGR color image and the image size reduced 1/4. + 64 : + convert image to the single channel grayscale image and the image size reduced 1/8. + 65 : + convert image to the 3 channel BGR color image and the image size reduced 1/8. + 128 : + do not rotate the image according to EXIF's orientation flag. + + + + + Description + +This function is used to Read/Load an image from the disk + + + + + + + + + Examples + + + diff --git a/help/en_US/imresize.xml b/help/en_US/imresize.xml new file mode 100755 index 0000000..ad5855d --- /dev/null +++ b/help/en_US/imresize.xml @@ -0,0 +1,67 @@ + + + + + + + + imresize + This function is used to resize the image + + + + + Calling Sequence + + + newImage=imresize(inputImage,alpha,beta); + + + + + + Parameters + + newImage: + the new resized image + inputImage: + the image which should be resized. + alpha: + new number of rows. + beta: + new number of columns. + + + + + Description + + + +This function is used to resize the image + + + + + + + Examples + + + diff --git a/help/en_US/imrotate.xml b/help/en_US/imrotate.xml new file mode 100644 index 0000000..08d66e0 --- /dev/null +++ b/help/en_US/imrotate.xml @@ -0,0 +1,91 @@ + + + + + + + + imrotate + Rotates an image by the specified angle + + + + + Calling Sequence + + outputImage = imrotate(srcImg, angle) + outputImage = imrotate(srcImg, angle, BoundingBoxType) + + + + + + Parameters + + srcImg : + The input image which is to be rotated + angle : + The angle by which the image is to be rotated + BoundingBoxType : + The type of the bounding box for the image displayed, whether a cropped one or one displaying full image. + + + + + Description + +The function rotates the input image in the anticlockwise direction by the angle specified around the centre point of the image. The bounding box determines whether the complete image or a cropped image will be displayed based on the BoundingBoxType i.e. 'loose' will display the complete image and 'crop' will display the cropped image. + + + + + + + Examples + + + + + Examples + + + + + Examples + + + + + Authors + + Shubham Lohakare, NITK Surathkal + Priyanka Hiranandani, NIT Surat + + + diff --git a/help/en_US/imsubtract.xml b/help/en_US/imsubtract.xml new file mode 100644 index 0000000..4a28c2e --- /dev/null +++ b/help/en_US/imsubtract.xml @@ -0,0 +1,90 @@ + + + + + + + + imsubtract + Subtract the contents of 2 matrices or images and store it inn another + + + + + Calling Sequence + + outputMat = imsubtract(input1, input2) + + + + + + Parameters + + input1 : + First input matrix or an image + input2 : + Second input matrix or image + + + + + Description + +p=imsubtract(a,b) subtracts each of the element in the first argument's array with the corrresponding element in the second argument's array and the answer is stored in p. + + + + + + + Examples + + + + + Examples + + + + + Examples + + + + + Authors + + Tess Zacharias + Shubham Lohakare + + + diff --git a/help/en_US/indexImages.xml b/help/en_US/indexImages.xml new file mode 100755 index 0000000..14359b9 --- /dev/null +++ b/help/en_US/indexImages.xml @@ -0,0 +1,79 @@ + + + + + + + + indexImages + This function creates image search index + + + + + Calling Sequence + + imageIndex = indexImages(imgSet, bagOfFeatures, Name, Value... ); + + + + + + Parameters + + imgSet: + Collection of images with their location and labels + bagOfFeatures: + Bag of Visual Words + Verbose [Optional Input Argument]: + Enable Progress display to Screen + SaveFeatureLocations [Optional Input Argument]: + A boolean value indicating whether feature locations has to be saved or not. Values: [True(default)|False] + imageIndex: + Search Index Object containing the mapping of visual vocabulary to each image in the image set + + + + + Description + +Creates a search Index Object that has been mapped to visual words that can be used for retrieve Images + + + + + + + Examples + + + + + Authors + + Umang Agrawal + Rohit Suri + Sridhar Reddy + + + diff --git a/help/en_US/integralImage.xml b/help/en_US/integralImage.xml new file mode 100644 index 0000000..de48242 --- /dev/null +++ b/help/en_US/integralImage.xml @@ -0,0 +1,83 @@ + + + + + + + + integralImage + The function calculates the integral of the source image passed. + + + + + Calling Sequence + + [outputImage,squaredImage,rotatedImage] = integralImage(srcImg) + [outputImage,squaredImage,rotatedImage] = integralImage(srcImg,method) + + + + + + Parameters + + srcImg : + The input image + method : + The type of output frame in which the image is to be returned. 'upright' gives the original output whereas 'rotated' gives the output rotated by 45 degrees. + + + + + Description + +The function can be used to calculate integral images for the provided input image. These integrals can be used to calculate the sum or mean or even standard deviation. It makes it feasible to apply fast blurring or fast block co-relation. + + + + + + + Examples + + + + + Examples + + + + + Authors + + Samiran Roy + Shubham Lohakare + + + diff --git a/help/en_US/integralKernel.xml b/help/en_US/integralKernel.xml new file mode 100755 index 0000000..373ba90 --- /dev/null +++ b/help/en_US/integralKernel.xml @@ -0,0 +1,69 @@ + + + + + + + + integralKernel + This function creates a filter to be used with integral images. + + + + + Calling Sequence + + results = intergralKernel(bbox, weight); + + + + + + Parameters + + results: + A structure kernel which contains bounding boxes, weights, filter coefficients, center of filter, size of filter, orientation of filter + bboxes: + bounding boxes that define the filter + weights: + weights corresponding to each of the bbox + + + + + Description + +Integral kernel creates box filter which can be used with integral images. + + + + + + + Examples + + + + + Authors + + Tanmay Chaudhari + + + diff --git a/help/en_US/master_help.xml b/help/en_US/master_help.xml new file mode 100755 index 0000000..b3d446e --- /dev/null +++ b/help/en_US/master_help.xml @@ -0,0 +1,59 @@ + + + + + + + + + + + + + + + + + + + + + + +]> + + + blur[en_US] + + + +blur[en_US] +&a1c783313efc44b1ff24d7f67ed09f9fa; +&a6057a2931c9ba06bf69b0718253a7f43; +&a249387f1e2010a0af784c47d1a0593d6; +&ae75ca7637710d4e262b1f0b51673fa51; +&af663a9ccea5b2ef374b470f5c0fbf78f; +&a1a4bf079dfff742308b6e99c80cab145; +&a9621c4caec3cf66d0796544955a72b9f; +&a5d5e4694041f56c7a8ea0dbae2fc2080; +&a52a2afd0b74f2cf38c69ad333f1e6e80; +&ae6f9cd868ae117193f4a61e921e7ecf4; +&ad1291297f626147a8f547efc784a53d8; +&a0a00d9bf5355279f3501f57a068f271c; +&ae07678a0d7b13b0c1e4a706af7cba772; +&a7e03210de8e0700e2b8afec91945f6fe; +&a90378f8702bbd352e1c43c65fc0e74a5; +&a9764533c75b7404fda073b3573d6fbd2; +&a7980cae396dfbb28f16e9aa428dcf8d0; +&a8087f56e69588df90bf4ba21cc3827da; +&a63c8d02f85102ddf8ccb4695c7599141; + + diff --git a/help/en_US/matMulDeriv.xml b/help/en_US/matMulDeriv.xml new file mode 100755 index 0000000..d438a45 --- /dev/null +++ b/help/en_US/matMulDeriv.xml @@ -0,0 +1,59 @@ + + + + + + + + matMulDeriv + this function Computes partial derivatives of the matrix product for each multiplied matrix + + + + + Calling Sequence + + [da db]=matMulDeriv(A,B); + + + + + + Parameters + + + + + + Description + +this function Computes partial derivatives of the matrix product for each multiplied matrix + + + + + Examples + + + diff --git a/help/en_US/multiDenoise.xml b/help/en_US/multiDenoise.xml new file mode 100644 index 0000000..e7ca926 --- /dev/null +++ b/help/en_US/multiDenoise.xml @@ -0,0 +1,129 @@ + + + + + + + + multiDenoise + Removes gaussian white noise from an image taking reference images of the same captured in small intervals + + + + + Calling Sequence + + out = multiDenoise(imgToDenoiseIndex, temporalWindowSize, filterStrength, templateWindowSize, searchWindowSize, n, choice, srcImg1, srcImg2, srcImg3) + out = multiDenoise(imgToDenoiseIndex, temporalWindowSize, filterStrength, templateWindowSize, searchWindowSize, n, choice, srcImg1, srcImg2, srcImg3, srcImg4) + out = multiDenoise(imgToDenoiseIndex, temporalWindowSize, filterStrength, templateWindowSize, searchWindowSize, n, choice, srcImg1, srcImg2, srcImg3, srcImg4, srcImg5) + + + + + + Parameters + + imgToDenoiseIndex : + Target image to denoise index in srcImgs sequence + temporalWindowSize : + Number of surrounding images to use for target image denoising. Should be odd. + filterStrength : + Parameter regulating filter strength. Bigger h value perfectly removes noise but also removes image details, smaller h value preserves details but also preserves some noise. + templateWindowSize : + Size in pixels of the template patch that is used to compute weights. Should be odd. + searchWindowSize : + Size in pixels of the window that is used to compute weighted average for given pixel. Should be odd. + n : + number of images passed. + choice : + chooses which type of method to use + srcImgs : + The input images which are passed. They are variable arguments. + + + + + Description + +Modification of fastNlMeansDenoising function for images sequence where consequtive images have been captured in small period of time. It removes gaussian white noise.The output is a denoised image + + + + + + + Examples + + + + + Examples + + + + + Examples + + + + + Authors + + Shubham Lohakare, NITK Surathkal + Ashish Mantosh, NIT Rourkela + + + diff --git a/help/en_US/multiDenoiseColor.xml b/help/en_US/multiDenoiseColor.xml new file mode 100644 index 0000000..beb4ccd --- /dev/null +++ b/help/en_US/multiDenoiseColor.xml @@ -0,0 +1,131 @@ + + + + + + + + multiDenoiseColor + Removes gaussian white noise from an image taking reference images of the same captured in small intervals + + + + + Calling Sequence + + out = multiDenoiseColor(imgToDenoiseIndex, temporalWindowSize, filterStrength, filterStrengthColor,templateWindowSize, searchWindowSize, n, srcImg1, srcImg2, srcImg3) + out = multiDenoiseColor(imgToDenoiseIndex, temporalWindowSize, filterStrength,filterStrengthColor, templateWindowSize, searchWindowSize, n, srcImg1, srcImg2, srcImg3,srcImg4) + out = multiDenoiseColor(imgToDenoiseIndex, temporalWindowSize, filterStrength,filterStrengthColor, templateWindowSize, searchWindowSize, n,srcImg1, srcImg2, srcImg3,srcImg4,srcImg5) + + + + + + Parameters + + imgToDenoiseIndex : + Target image to denoise index in srcImgs sequence + temporalWindowSize : + Number of surrounding images to use for target image denoising. Should be odd. + filterStrength : + Parameter regulating filter strength. Bigger h value perfectly removes noise but also removes image details, smaller h value preserves details but also preserves some noise. + filterStrengthColor : + same as filterStrength but for color components of noise. + templateWindowSize : + Size in pixels of the template patch that is used to compute weights. Should be odd. + searchWindowSize : + Size in pixels of the window that is used to compute weighted average for given pixel. Should be odd. + n : + number of images passed. + srcImgs : + The input images which are passed. They are variable arguments. + + + + + Description + +Modification of fastNlMeansDenoising function for images sequence where consequtive images have been captured in small period of time. It removes gaussian white noise.The output is a denoised image + + + + + + + Examples + + + + + Examples + + + + + Examples + + + + + Authors + + Shubham Lohakare, NITK Surathkal + Ashish Mantosh, NIT Rourkela + + + diff --git a/help/en_US/rgb2xyz.xml b/help/en_US/rgb2xyz.xml new file mode 100755 index 0000000..69bc795 --- /dev/null +++ b/help/en_US/rgb2xyz.xml @@ -0,0 +1,62 @@ + + + + + + + + rgb2xyz + This function is used to convert rgb values of an image to their CIE 1931 xyz. + + + + + Calling Sequence + + image=imread("lena.jpeg"); + xyz=imread(image); + + + + + + Parameters + + xyz: + the converted image + image: + Input Image. + + + + + Description + + + +This function is used to convert rgb values of an image to their CIE 1931 xyz. + + + + + + + Examples + + + diff --git a/help/en_US/scilab_en_US_help/CascadeObjectDetector.html b/help/en_US/scilab_en_US_help/CascadeObjectDetector.html new file mode 100755 index 0000000..4c6335f --- /dev/null +++ b/help/en_US/scilab_en_US_help/CascadeObjectDetector.html @@ -0,0 +1,119 @@ + + + CascadeObjectDetector + + + +

+ +

Description

+

+

This function is used to detect objects in an image.

+

+ +

Examples

+ 
// A example detecting all faces,eyes in an image.
+//read the input image.
+z=imread("oscarSelfie.jpg");
+//increase stacksize of scilab
+stacksize('max')
+declare string martrix with the xml locations.Here the general opencv's .xml files are used.
+s=["/home/nihar/Desktop/opencv/data/haarcascades/haarcascade_eye_tree_eyeglasses.xml" "/home/nihar/Desktop/opencv/data/haarcascades/haarcascade_frontalface_alt.xml"];
+//call function
+//Note:-the value of scale and other optional inputs must be adjusted to get proper/desired detection.
+p=CascadeObjectDetector(z,s,1.05);
+//show the detection
+imshow(p);
+
+Detect only faces.
+
+//read the input image.
+z=imread("oscarSelfie.jpg");
+//increase stacksize of scilab
+stacksize('max')
+declare string martrix with the xml locations.Here the general opencv's .xml files are used.
+s=["/home/nihar/Desktop/opencv/data/haarcascades/haarcascade_frontalface_alt.xml"];
+//call function
+//Note:-the value of scale and other optional inputs must be adjusted to get proper/desired detection.
+p=CascadeObjectDetector(z,s,1.05);
+//show the detection
+imshow(p);
+
+ +
+ + + + + + +
Report an issue
+ << Calibrate + + + FOSSEE_Image_Processing_Toolbox + + + arrowedline >> + +
+
+
+ + diff --git a/help/en_US/scilab_en_US_help/JavaHelpSearch/DOCS b/help/en_US/scilab_en_US_help/JavaHelpSearch/DOCS new file mode 100755 index 0000000..ef46423 --- /dev/null +++ b/help/en_US/scilab_en_US_help/JavaHelpSearch/DOCS @@ -0,0 +1 @@ + \ No newline at end of file diff --git a/help/en_US/scilab_en_US_help/JavaHelpSearch/DOCS.TAB b/help/en_US/scilab_en_US_help/JavaHelpSearch/DOCS.TAB new file mode 100755 index 0000000..e3c71bf --- /dev/null +++ b/help/en_US/scilab_en_US_help/JavaHelpSearch/DOCS.TAB @@ -0,0 +1 @@ +eÿÐjª` \ No newline at end of file diff --git a/help/en_US/scilab_en_US_help/JavaHelpSearch/OFFSETS b/help/en_US/scilab_en_US_help/JavaHelpSearch/OFFSETS new file mode 100755 index 0000000..1324712 --- /dev/null +++ b/help/en_US/scilab_en_US_help/JavaHelpSearch/OFFSETS @@ -0,0 +1 @@ +ÐÊ \ No newline at end of file diff --git a/help/en_US/scilab_en_US_help/JavaHelpSearch/POSITIONS b/help/en_US/scilab_en_US_help/JavaHelpSearch/POSITIONS new file mode 100755 index 0000000..60477b1 --- /dev/null +++ b/help/en_US/scilab_en_US_help/JavaHelpSearch/POSITIONS @@ -0,0 +1 @@ +eÿ×ãbÙñ.³d \ No newline at end of file diff --git a/help/en_US/scilab_en_US_help/JavaHelpSearch/SCHEMA b/help/en_US/scilab_en_US_help/JavaHelpSearch/SCHEMA new file mode 100755 index 0000000..a646b00 --- /dev/null +++ b/help/en_US/scilab_en_US_help/JavaHelpSearch/SCHEMA @@ -0,0 +1,2 @@ +JavaSearch 1.0 +TMAP bs=2048 rt=0 fl=-1 id1=10 id2=1 diff --git a/help/en_US/scilab_en_US_help/JavaHelpSearch/TMAP b/help/en_US/scilab_en_US_help/JavaHelpSearch/TMAP new file mode 100755 index 0000000000000000000000000000000000000000..fced7c73a3c9bb4dee2d0dc86a18a1b79e89453f GIT binary patch literal 2048 zcmZQzU|?uqVCV!=oIF5+fl*ICGcP5zLNB8vH%A^M!s+H89PH|<;F+74o~jT~l%Jeh zT%4Jgt`L%+pOchd!30voo|wl5qM6e2i;GiJSwU>(Opp#1Mj(@;xVSWx3na)=05<@v ofvqUDAit=D9VEwE0x=Q99tEQzFd71*Aut*OqaiRF0yGN&04Q@I?*IS* literal 0 HcmV?d00001 diff --git a/help/en_US/scilab_en_US_help/ScilabCaution.png b/help/en_US/scilab_en_US_help/ScilabCaution.png new file mode 100755 index 0000000000000000000000000000000000000000..231159a5c9f0c716517f1938a758d389664f9479 GIT binary patch literal 507 zcmeAS@N?(olHy`uVBq!ia0vp^0wB!63?wyl`GbMfy#SvOS0G)00~Inblrk`sGcc5a zNgxBl1`2jFF!V7nOkiM`#K15G%f+$IF{pL|h-!7BBy>0T}{1=kt zcK?{~moB@^x4`$@bIw=q9GCFNrkq)~t8VV!-Q`nc+^xR-JN75--uq{{|6c!d`zFsH zfA35Ev8GK;*R?mSIJ%uZTD7OZhHL8E2bb5XCaW7d9_c)*6D^;-`mLNbbj7>9eta!yKNWabXO}K->_$eSE+rI=yS8L$A1>w-EoIYZ%@OK_=FmziGGjE YZ|O^O>$mev2fCcW)78&qol`;+06Qz+e*gdg literal 0 HcmV?d00001 diff --git a/help/en_US/scilab_en_US_help/ScilabEdit.png b/help/en_US/scilab_en_US_help/ScilabEdit.png new file mode 100755 index 0000000000000000000000000000000000000000..ff0cca7261415d91d549698cf54fa37af653bf55 GIT binary patch literal 413 zcmeAS@N?(olHy`uVBq!ia0vp^0wB!63?wyl`GbMf#sHrXS0D`m{gF&Z7BB$Gj;>Z9 zTG$*46!&pbOHNMC4mT@^wk#|xEG;cKCVzJ14z9eeidIkdV9XzYC>mroH=uDS;qNQndjFQ zURslN`SRs!*RI{Vb?f%++b>_feD&(p>y5UrU%!6y=FQuuN8Ua=`tH@SckkZ4e|`Mt zi(~))|6g#0PXy>P&XOR%US!bs&Z|koOaE-W3k@K*A8^qtVmI~+Mb$t zx>Zj{{=;=4wxrV2Mb0q-n$`iIf`#pz9yVBNYdJ-oc~`w=`jn@W3Jm5YCCh29tn>K8 zF?njn+?V;TKi0keu}*%DwvuJI)!fxd4%WOJl?+OAB;5oKZ&n8dvZt$`%Q~loCIE!y Bz-<5k literal 0 HcmV?d00001 diff --git a/help/en_US/scilab_en_US_help/ScilabExecute.png b/help/en_US/scilab_en_US_help/ScilabExecute.png new file mode 100755 index 0000000000000000000000000000000000000000..4acd4b93668e93bd9b2cff9a33d64f4059cc4ccd GIT binary patch literal 535 zcmV+y0_gpTP)r#}QAt}{o3OX+9USER{C&U%eER(1|BDyT z{x4p#=vP3X-xoIz*QL6;x-t$9_KY|U2n`LD3keMb8}RMh*Z;qM|N8&)=gF^xxEJ zQ~u=SW$uoRjnV?D=Rh%_zP>>&E;8$|!BeM9m7F?d3M+;eR;^kko0**sG~gE`41WFmzij!EKb6(x-{&uyUAAV;8abdE zcASB@fByklpe?_D0yS>ly76CYd*km(Q~NjV+__T=D924O8n0ZvB3n^a{HwF8^-ol3#v1yD{WN9ehFB^=%MnSJwO9$#dJ`xv_zKI*QKw1SeARZGSMT6694K zeLn^ZHU_+C0H;lC!XqSzw+haXax1WJ-CF*GD`oF;GM3z ze0@Oio4zUtPDf{Z@G7IKSDH}h$J3u&0uN_Yf5d~2Q6QqT&P0*x`ONAH%P1qJ`PH;- zy6Wov>D3?c?7#eGJL|hs*P~%{`TD?;u17O!u(#$qSq^I*?=yWJ>EX;;@6Puwc8h;M z_c8bfn0nCI9U*k`csMyuN0OIc?b}1>l%YF~r~kowyand^1_)Uc00000NkvXXu0mjf DODZyl literal 0 HcmV?d00001 diff --git a/help/en_US/scilab_en_US_help/ScilabNote.png b/help/en_US/scilab_en_US_help/ScilabNote.png new file mode 100755 index 0000000000000000000000000000000000000000..6607ece63f86c6036dc5af54e9688bdd42fbef52 GIT binary patch literal 663 zcmV;I0%-k-P)ycciq)qXY=g$V%v7Is$-kA-Nv?UYdjN-ZTs|2-M;u+UH!g$F0jM6=9X4^ z)isTA*(Ke4*)_v*)h&&6!~KIA>?AI`q`h*@J)K$CJ_{0=8q8)3=nN)c@?`K${RG_f z%n;o0_~6YW1=l^&xmyG}X!J$`U#4zh3RQI!mb3|XAnGAAC6wVgBHZ!Gk{=pI=33j% zC`^>8bU&$e#ves;?Joy>WdoirX_>*X8|MieT+MewaL*_0m-_^_y)z}YviUMin+k=E zX3O_th3@AAp0aLhPgFO(!>&*Ney(zUhXIZOdD{B~SI}h{O%|XFl=V`Tz6but^crb8 zqA0Zkg7Y__rVYkKigAL}de!A!*#_DH;JGl53XfT=CitmAUkB$NI;9g#$Uu zMBZP5r~V^w@XuA#ITBc<@Y|P2{2u@@wZ;0fe}(?V_rt`G!Yf9yqHD*h`xj~899(3; 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+ + + + +
+ << FOSSEE Image Processing Toolbox + + + FOSSEE Image Processing Toolbox + + + boxfilter >> + +
+
+
+ + + + FOSSEE Image Processing Toolbox >> FOSSEE Image Processing Toolbox > adaptHistEq + +

+

adaptHistEq

+

Performs Contrast Limited Adaptive Histogram Equalisation

+ + +

Calling Sequence

+ 
outputImage = adaptHistEq(inputImage)
+outputImage = adaptHistEq(inputImage, clip_limit)
+ +

Parameters

+
inputImage : +

The input image on which histogram equalisation is to be implemented

+
clip_limit : +

The target hgram bins.

+ +

Description

+

As an alternative to using histeq, you can perform contrast-limited adaptive histogram equalization (CLAHE) using the adapthisteq function. While histeq works on the entire image, adapthisteq operates on small regions in the image, called tiles. Each tile's contrast is enhanced, so that the histogram of the output region approximately matches a specified histogram. After performing the equalization, adapthisteq combines neighboring tiles using bilinear interpolation to eliminate artificially induced boundaries.

+

+ +

Examples

+ 
a=imread("lena.jpeg");
+k=adaptHistEq(a);
+ +

Examples

+ 
a=imread("photo.jpg");
+k=adaptHistEq(a,64);
+ +

Authors

+
  • Shubham Lohakare, NITK Surathkal
    • +
  • Yash Balghat
+
+ +
+ + + + + + +
Report an issue
+ << FOSSEE Image Processing Toolbox + + + FOSSEE Image Processing Toolbox + + + boxfilter >> + +
+
+
+ + diff --git a/help/en_US/scilab_en_US_help/arrowedline.html b/help/en_US/scilab_en_US_help/arrowedline.html new file mode 100755 index 0000000..46c4d00 --- /dev/null +++ b/help/en_US/scilab_en_US_help/arrowedline.html @@ -0,0 +1,59 @@ + + + arrowedline + + + +
+ + + + +
+ << CascadeObjectDetector + + + FOSSEE_Image_Processing_Toolbox + + + blur >> + +
+
+
+ + + + FOSSEE_Image_Processing_Toolbox >> FOSSEE_Image_Processing_Toolbox > arrowedline + +

+

arrowedline

+

+
+ +
+ + + + + + +
Report an issue
+ << CascadeObjectDetector + + + FOSSEE_Image_Processing_Toolbox + + + blur >> + +
+
+
+ + diff --git a/help/en_US/scilab_en_US_help/blur.html b/help/en_US/scilab_en_US_help/blur.html new file mode 100755 index 0000000..5cefd26 --- /dev/null +++ b/help/en_US/scilab_en_US_help/blur.html @@ -0,0 +1,86 @@ + + + blur + + + +
+ + + + +
+ << arrowedline + + + FOSSEE_Image_Processing_Toolbox + + + boundingRect >> + +
+
+
+ + + + FOSSEE_Image_Processing_Toolbox >> FOSSEE_Image_Processing_Toolbox > blur + +

+

blur

+

This function is used to blur an image using the normalized box filter.

+ + +

Calling Sequence

+ 
B = blur(input_image ,ksize_width,ksize_height,anchorX,anchorY);
+ +

Parameters

+
A: +

image matrix of the source image.

+
ksize_width : +

Defines the width of the kernel to be used in pixels.

+
ksize_width : +

Defines the height of the kernel to be used in pixels.

+
anchorX : +

Indicates where the x coordinate of the anchor point (the pixel evaluated) is located with respect to the neighborhood. If there is a negative value, then the center of the kernel is considered the anchor point.

+
anchorY : +

Indicates where the y coordinate of the anchor point (the pixel evaluated) is located with respect to the neighborhood. If there is a negative value, then the center of the kernel is considered the anchor point.

+
B : +

output image with the applied blur fucntion.

+ +

Description

+

The function smoothes an image using the kernel specified with its dimesnsions.

+

+ +

Examples

+ 
i = imread('right1.jpg',0);
+i2 =blur(i,5,5,1,1)
+imshow(i2);
+
+ +
+ + + + + + +
Report an issue
+ << arrowedline + + + FOSSEE_Image_Processing_Toolbox + + + boundingRect >> + +
+
+
+ + diff --git a/help/en_US/scilab_en_US_help/boundingRect.html b/help/en_US/scilab_en_US_help/boundingRect.html new file mode 100755 index 0000000..090d97e --- /dev/null +++ b/help/en_US/scilab_en_US_help/boundingRect.html @@ -0,0 +1,80 @@ + + + boundingRect + + + +
+ + + + +
+ << blur + + + FOSSEE_Image_Processing_Toolbox + + + circle >> + +
+
+
+ + + + FOSSEE_Image_Processing_Toolbox >> FOSSEE_Image_Processing_Toolbox > boundingRect + +

+

boundingRect

+

this function Calculates the up-right bounding rectangle of a point set.

+ + +

Calling Sequence

+ 
z=imread("lena.jpeg",0);
+rect=boundingRect(points);
+ +

Parameters

+
rect: +

the rectangle coordinates

+
points: +

the set of 2D points. It must be N*2.

+ +

Description

+

+

Calculates the up-right bounding rectangle of a point set.

+

+ +

Examples

+ 
z=imread("lena.jpeg",0);
+kaze=detectKAZEFeatures(z)x
+rect=boundingRect(kaze.KeyPoints);
+
+ +
+ + + + + + +
Report an issue
+ << blur + + + FOSSEE_Image_Processing_Toolbox + + + circle >> + +
+
+
+ + diff --git a/help/en_US/scilab_en_US_help/boxfilter.html b/help/en_US/scilab_en_US_help/boxfilter.html new file mode 100644 index 0000000..be5985d --- /dev/null +++ b/help/en_US/scilab_en_US_help/boxfilter.html @@ -0,0 +1,95 @@ + + + boxfilter + + + +
+ + + + +
+ << adaptHistEq + + + FOSSEE Image Processing Toolbox + + + denoiseColor >> + +
+
+
+ + + + FOSSEE Image Processing Toolbox >> FOSSEE Image Processing Toolbox > boxfilter + +

+

boxfilter

+

Blurs an image using the box filter.

+ + +

Calling Sequence

+ 
outputImage = boxfilter(InputArraysrc, intddepth,size1x,size1y,pointx,pointy, bool_normalize)
+ +

Parameters

+
InputArraysrc : +

Input image to be blurred

+
intddepth : +

The output image depth (-1 to use src.depth())

+
size1x : +

Width for the blurring kernel size

+
size1y : +

Height for the blurring kernel size

+
pointx : +

x-coordinate for anchor point (Default value -1)

+
pointy : +

y-coordinate for anchor point (Default value -1)

+
bool_normalize : +

flag, specifying whether the kernel is normalized by its area or not

+ +

Description

+

Unnormalized box filter is useful for computing various integral characteristics over each pixel neighborhood, such as covariance matrices of image derivatives (used in dense optical flow algorithms, and so on).

+

+ +

Examples

+ 
a = imread("lena.jpeg");
+k=boxfilter(a,-1,40,80,-1,-1,"False");
+ +

Examples

+ 
a = imread("photo.jpg");
+k=boxfilter(a,-1,8,8,-1,-1,"True");
+ +

Authors

+
  • Shubham Lohakare, NITK Surathkal
    • +
  • Priyanka Hiranandani, NIT Surat
+
+ +
+ + + + + + +
Report an issue
+ << adaptHistEq + + + FOSSEE Image Processing Toolbox + + + denoiseColor >> + +
+
+
+ + diff --git a/help/en_US/scilab_en_US_help/c_code.css b/help/en_US/scilab_en_US_help/c_code.css new file mode 100755 index 0000000..948d2ee --- /dev/null +++ b/help/en_US/scilab_en_US_help/c_code.css @@ -0,0 +1,54 @@ +.ccomment { + font-style: italic; + color: #b22222 +} + +.cdefault { + font-style: normal; + color: #000000 +} + +.copenclose { + font-style: normal; + color: #000000 +} + +.coperator { + font-style: normal; + color: #000000 +} + +.cstring { + font-style: normal; + color: #a6557a +} + +.ctype { + font-style: normal; + color: #55a655 +} + +.cpreprocessor { + font-style: normal; + color: #9965a6 +} + +.cid { + font-style: normal; + color: #000000 +} + +.ckeyword { + font-style: normal; + color: #ad3ff2 +} + +.cmodifier { + font-style: normal; + color: #ad3ff2 +} + +.cnumber { + font-style: normal; + color: #008b8b +} diff --git a/help/en_US/scilab_en_US_help/circle.html b/help/en_US/scilab_en_US_help/circle.html new file mode 100755 index 0000000..9ef9447 --- /dev/null +++ b/help/en_US/scilab_en_US_help/circle.html @@ -0,0 +1,101 @@ + + + circle + + + +
+ + + + +
+ << boundingRect + + + FOSSEE_Image_Processing_Toolbox + + + correctMatches >> + +
+
+
+ + + + FOSSEE_Image_Processing_Toolbox >> FOSSEE_Image_Processing_Toolbox > circle + +

+

circle

+

This function circle draws a simple or filled circle on an image with a given center and radius.

+ + +

Calling Sequence

+ 
cir=circle(inputImage,xcor,ycor,radius,r,g,b);
+cir=circle(inputImage,xcor,ycor,radius,r,g,b,thickness);
+cir=circle(inputImage,xcor,ycor,radius,r,g,b,thickness,linetype);
+cir=circle(inputImage,xcor,ycor,radius,r,g,b,thickness,linetype,shift);
+ +

Parameters

+
cir: +

The output image with the circle drawn in it.

+
inputImage: +

The input image on which the circle should be drawn.

+
xcor: +

X-coordinate of the center

+
ycor: +

Y-coordinate of the center

+
r: +

red color value of the circle.It should be in the range 0-255.

+
b: +

blue color value of the circle.It should be in the range 0-255.

+
g: +

green color value of the circle.It should be in the range 0-255.

+
thickness: +

Line thickness.

+
linetype: +

Type of the circle boundary.It can be 0 or 4 or 8.

+
shift: +

Number of fractional bits in the point coordinates.

+ +

Description

+

This function circle draws a simple or filled circle on an image with a given center and radius.

+

+

+ +

Examples

+ 
//read the input image
+z=imread("lena.jpeg");
+//call the function
+cir=circle(z,100,100,15,255,0,0,1,8,0);
+finally show the circle drawn
+imshow(cir)
+
+ +
+ + + + + + +
Report an issue
+ << boundingRect + + + FOSSEE_Image_Processing_Toolbox + + + correctMatches >> + +
+
+
+ + diff --git a/help/en_US/scilab_en_US_help/correctMatches.html b/help/en_US/scilab_en_US_help/correctMatches.html new file mode 100755 index 0000000..b6ce5b0 --- /dev/null +++ b/help/en_US/scilab_en_US_help/correctMatches.html @@ -0,0 +1,84 @@ + + + correctMatches + + + +
+ + + + +
+ << circle + + + FOSSEE_Image_Processing_Toolbox + + + cvtColor >> + +
+
+
+ + + + FOSSEE_Image_Processing_Toolbox >> FOSSEE_Image_Processing_Toolbox > correctMatches + +

+

correctMatches

+

This function Refines coordinates of corresponding points using openCV's functions.

+ + +

Calling Sequence

+ 
[newPoints1, newPoints2] = correctMatches(F, points1, points2)
+ +

Parameters

+
+ +

Description

+

The function implements the Optimal Triangulation Method (see Multiple View Geometry for details). For each given point correspondence points1[i] <-> points2[i], and a fundamental matrix F, it computes the corrected correspondences newPoints1[i] <-> newPoints2[i] that minimize the geometric error d(points1[i], newPoints1[i])^2 + d(points2[i],newPoints2[i])^2 (where d(a,b) is the geometric distance between points a and b ) subject to the epipolar constraint newPoints2^T * F * newPoints1 = 0 .

+

+ +

Examples

+ 
//read first image
+I=imread("oscarSelfie.jpg",0);
+//increase stack size of scilab
+stacksize('max')
+// get points from first image
+cornerPoints1=detectMSERFeatures(I);
+//read second image
+I2=imread("oscarSelfie.jpg",0);
+//get points for 2nd image
+cornerPoints2=detectMSERFeatures(I2);
+fundamentalMat=estimateFundamentalMat(cornerPoints1.Location,cornerPoints2.Location);
+[new1 new2]=correctMatches(fundamentalMat,cornerPoints2.Location,cornerPoints1.Location);
+
+ +
+ + + + + + +
Report an issue
+ << circle + + + FOSSEE_Image_Processing_Toolbox + + + cvtColor >> + +
+
+
+ + diff --git a/help/en_US/scilab_en_US_help/cvtColor.html b/help/en_US/scilab_en_US_help/cvtColor.html new file mode 100755 index 0000000..f14a99f --- /dev/null +++ b/help/en_US/scilab_en_US_help/cvtColor.html @@ -0,0 +1,137 @@ + + + cvtColor + + + +
+ + + + +
+ << correctMatches + + + FOSSEE_Image_Processing_Toolbox + + + dctmtx >> + +
+
+
+ + + + FOSSEE_Image_Processing_Toolbox >> FOSSEE_Image_Processing_Toolbox > cvtColor + +

+

cvtColor

+

This function is used to transform a image from one space to other like rgb to gray and vice versa.

+ + +

Calling Sequence

+ 
inputImage=imread("lena.jpeg");
+outputImage=cvtColor(inputImage,codeString);
+outputImage=cvtColor(inputImage,codeString,dstCn);
+ +

Parameters

+
dstCn: +

number of channels in the destination image; if the parameter is 0, the number of the channels is derived automatically from src and code

+
codeString: +

A string which specifies the type of conversion.The different types are listed below.

+
"CV_BGR2GRAY": +

Conversion is from BGR(blue-green-red) space to GRAY.

+
"CV_RGB2GRAY": +

Conversion is from RGB(red-green-blue) space to GRAY.

+
"CV_GRAY2BGR": +

Conversion is from BGR(blue-green-red) space.

+
"CV_GRAY2RGB": +

Conversion is from to GRAY to RGB(blue-green-red) space.

+
"CV_BGR2XYZ" : +

Conversion is from BGR(blue-green-red) space to CIE XYZ.

+
"CV_RGB2XYZ" : +

Conversion is from RGB(red-green-blue) space to CIE XYZ.

+
"CV_XYZ2BGR" : +

Conversion is from to CIE XYZ to BGR space.

+
"CV_XYZ2RGB" : +

Conversion is from to CIE XYZ to RGB(red-green-blue) space.

+
"CV_BGR2YCrCb": +

Conversion is from BGR(blue-green-red) space to luma-chroma.

+
"CV_RGB2YCrCb" : +

Conversion is from RGB(red-green-blue) space to luma chroma.

+
"CV_YCrCb2BGR" : +

Conversion is from luma-chroma to BGR(blue-green-red) space.

+
"CV_YCrCb2RGB" : +

Conversion is from luma-chroma to RGB(red-green-blue) space.

+
"CV_BGR2HSV": +

Conversion is from BGR(blue-green-red) space to HSV.

+
"CV_RGB2HSV": +

Conversion is from RGB space to HSV.

+
"CV_HSV2BGR": +

Conversion is from to HSV to BGR(blue-green-red) space.

+
"CV_HSV2RGB": +

Conversion is from to HSV to RGB(red-green-blue) space.

+
"CV_BGR2HLS": +

Conversion is from BGR(blue-green-red) space to HLS.

+
"CV_RGB2HLS": +

Conversion is from RGB space to HSV.

+
"CV_HLS2BGR": +

Conversion is from HLS to BGR(blue-green-red) space.

+
"CV_HLS2RGB": +

Conversion is from HLS to RGB(red-green-blue) space.

+
"CV_BGR2Lab": +

Conversion is from BGR(blue-green-red) space to CIE Lab.

+
"CV_RGB2Lab": +

Conversion is from RGB space to CIE Lab.

+
"CV_Lab2BGR": +

Conversion is from CIE Lab to BGR(blue-green-red) space.

+
"CV_Lab2RGB": +

Conversion is from CIE Lab to RGB space.

+
"CV_BGR2Luv": +

Conversion is from BGR(blue-green-red) space to CIE Luv.

+
"CV_RGB2Luv": +

Conversion is from RGB space to CIE Luv.

+
"CV_Luv2BGR": +

Conversion is from CIE Luv to BGR(blue-green-red) space.

+
"CV_Luv2RGB": +

Conversion is from CIE Luv to RGB space.

+ +

Description

+

+

This function is used to transform a image from one space to other like rgb to gray and vice versa.

+

+ +

Examples

+ 
z=imread("lena.jpeg",0);
+ss=cvtColor(z,"CV_GRAY2BGR");
+imshow(ss)
+
+ +
+ + + + + + +
Report an issue
+ << correctMatches + + + FOSSEE_Image_Processing_Toolbox + + + dctmtx >> + +
+
+
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z-H64tpx;H%VYYZR;^eNRrH00A7=$yDy-U0_PmpGW-cvdZQtft&QuKM05U4hIml|NDYn@z* zs8KYSk^r+z^RIH1z(n;uHkRSQ(I}XDE=Ktljj;Gt0$gq2a5rfLAHL9$FiJ+A3m!2G zn%t-w0ViMC2y|i>Yy{l@{a)vq+i-A?DQ+c}+|<~2s7#~biESr)Fo?_uni zuQ%O(MRw~lsdnzQ+JM%yrR=&Qx#kLe0ttI=ZDo0LvE0kuPu3b*T#GuR1=kycH}6!` zrqA`Iq6WbiS>IqTx6+ciu88H`Dtj?;fA=<_ZUne}ia&okLTVr7XDGY#kAac=% z%;i#W5WCwr3#?Agb}o%+4H4~d+Li&2MuxJ2tT(_|%~WA)X)T$PBK6i3K$a%rGmJ0naQSeZQLz0(GVc4Y+Sd4S=rdi#^0uFtVCmx%uiIP zlNJ0@lMTtFW-B&ZvDw5HpYnzM4=AyB& z_uqQ#{WqMerjY-Ig_sP(M9P=KRa5_`cXDx7%>UB8=yf_a|H~$>b?1K(BxO^+7*F|< zl#2JzMPPovDLk|rO)>FVX@%J&4_fI%o90EOc~Ofwhk#a@T~v2XlDRy`SE9_Brax2m z7n;<+a0r|kKyaMm!GSQ3;WTbX%9hfTRr<8_keCZCSazIWh)qb&N~MiF=2v^fmu5{( zpZ+;vL!Dvjl32jhH%CT3ZX-{M)#zA)PdwzeEes@`5LW(YsapOPAZQom> znOA$c0lY4i2%759TPncy%3LH?t8>+)tkOl&=2UC2ieeXy>~UMwjoznQjlb3SZ%*TH dRWG}#dijR6{Pwb!z3jDk{eK9$Yghm*0|2 + + deconvlucy + + + +
+ + + + +
+ << dctmtx + + + FOSSEE_Image_Processing_Toolbox + + + demosaic >> + +
+
+
+ + + + FOSSEE_Image_Processing_Toolbox >> FOSSEE_Image_Processing_Toolbox > deconvlucy + +

+

deconvlucy

+

This function is used to Deblur image using Lucy-Richardson method

+ + +

Calling Sequence

+ 
J = deconvlucy(I1, I2);
+J = deconvlucy(I1, I2, NUMIT)
+ +

Parameters

+
I1: +

image matrix of the source image .

+
I2: +

image matrix of the source image from last iteraion.

+
NUMIT: +

The number if iterations specified to achieve the desired result.

+
B : +

output image in the deconvoluted form.

+ +

Description

+

J = deconvlucy(I, PSF, NUMIT) specifies the number of iterations the deconvlucy function performs. If this value is not specified, the default is 10.

+

+ +

Examples

+ 
i = imread("lena.jpeg",0);
+i1 = imread("lena.jpeg",0);
+rs = deconvlucy(i,i1);
+
+ +
+ + + + + + +
Report an issue
+ << dctmtx + + + FOSSEE_Image_Processing_Toolbox + + + demosaic >> + +
+
+
+ + diff --git a/help/en_US/scilab_en_US_help/demosaic.html b/help/en_US/scilab_en_US_help/demosaic.html new file mode 100755 index 0000000..a8265a4 --- /dev/null +++ b/help/en_US/scilab_en_US_help/demosaic.html @@ -0,0 +1,83 @@ + + + demosaic + + + +
+ + + + +
+ << deconvlucy + + + FOSSEE_Image_Processing_Toolbox + + + detectAgastFeatures >> + +
+
+
+ + + + FOSSEE_Image_Processing_Toolbox >> FOSSEE_Image_Processing_Toolbox > demosaic + +

+

demosaic

+

This function converts the Bayer pattern encoded image to the truecolor image, RGB.

+ + +

Calling Sequence

+ 
image=imread("lena.jpeg",0)
+dem=demosaic(image,"gbrg");
+dem=demosaic(image,"bggr");
+dem=demosaic(image,"rggb");
+dem=demosaic(image,"grbg");
+ +

Parameters

+
dem: +

the output image

+
image: +

the image which should be converted.

+ +

Description

+

+

This function converts the Bayer pattern encoded image to the truecolor image, RGB.

+

+ +

Examples

+ 
z=imread("lena.jpeg");
+dem=demosaic(z,"rggb");
+imshow(dem);
+
+ +
+ + + + + + +
Report an issue
+ << deconvlucy + + + FOSSEE_Image_Processing_Toolbox + + + detectAgastFeatures >> + +
+
+
+ + diff --git a/help/en_US/scilab_en_US_help/denoiseColor.html b/help/en_US/scilab_en_US_help/denoiseColor.html new file mode 100644 index 0000000..690eaa6 --- /dev/null +++ b/help/en_US/scilab_en_US_help/denoiseColor.html @@ -0,0 +1,100 @@ + + + denoiseColor + + + +
+ + + + +
+ << boxfilter + + + FOSSEE Image Processing Toolbox + + + fastNlMeansDenoising >> + +
+
+
+ + + + FOSSEE Image Processing Toolbox >> FOSSEE Image Processing Toolbox > denoiseColor + +

+

denoiseColor

+

Removes colored noise from the image

+ + +

Calling Sequence

+ 
outputImage = denoiseColor(src, strengthFilter,strengthFilterColor, tempWindowSize, searchWindowSize)
+ +

Parameters

+
src : +

The input image with colored noise.

+
strengthFilter : +

The noise filter for white gaussian noise.

+
strengthFilterColor : +

The noise filter for colored noise.

+
tempWindowSize : +

Size in pixels of the template patch that is used to compute weights. Should be odd.

+
searchWindowSize : +

Size in pixels of the window that is used to compute weighted average for given pixel. Should be odd.

+ +

Description

+

The function is used to remove colored noise from an image. It is the modification of fasNlmeansDenoising function +The output is a denoised image

+

+ +

Examples

+ 
a = imread("taj.jpg");
+strengthFilter = 200;
+strengthFilterColor = 40;
+tempWindowSize = 7;
+searchWindowSize =21;
+p = denoiseColor(a,strengthFilter,strengthFilterColor,tempWindowSize,searchWindowSize);
+ +

Examples

+ 
a = imread("cnoise1.jpg");
+strengthFilter = 20;
+strengthFilterColor = 100;
+tempWindowSize = 7;
+searchWindowSize =21;
+p = denoiseColor(a,strengthFilter,strengthFilterColor,tempWindowSize,searchWindowSize);
+ +

Authors

+
  • Shubham Lohakare, NITK Surathkal
    • +
  • Ashish Mantosh Barik, NIT Rourkela
+
+ +
+ + + + + + +
Report an issue
+ << boxfilter + + + FOSSEE Image Processing Toolbox + + + fastNlMeansDenoising >> + +
+
+
+ + diff --git a/help/en_US/scilab_en_US_help/detectGFTTFeatures.html b/help/en_US/scilab_en_US_help/detectGFTTFeatures.html new file mode 100755 index 0000000..29ae319 --- /dev/null +++ b/help/en_US/scilab_en_US_help/detectGFTTFeatures.html @@ -0,0 +1,98 @@ + + + detectGFTTFeatures + + + +
+ + + + +
+ << detectAkazeFeatures + + + FOSSEE_Image_Processing_Toolbox + + + detectKAZEFeatures >> + +
+
+
+ + + + FOSSEE_Image_Processing_Toolbox >> FOSSEE_Image_Processing_Toolbox > detectGFTTFeatures + +

+

detectGFTTFeatures

+

This function is used to detect GFTT Features in a grayscale Image.

+ + +

Calling Sequence

+ 
result = detectGFTTFeatures(Image);
+result = detectGFTTFeatures(Image,Name,Value,....)
+ +

Parameters

+
result: +

a struct containing features and keypoints

+
Image: +

a grayscale image whose GFTT features is to be found

+
blocksize: +

the blocksize to be used for detecting the keypoints

+
minDistance: +

the minimum distance between the points for feature computation

+
useHarrisDetector: +

an option to use the HarrisDetector.default value is false.

+
maxCorners: +

the maximum number of corners that should be used for feature computation.

+
ROI or Mask : +

(Optional) Region Of Interest. This is taken as a vector [u v width height]. When specified, the function detects the key points within region of area width*height with u and v being the top left corner coordinates.

+ +

Description

+

This function is used to detect GFTT Features in a grayscale Image.

+ +

Examples

+ 
//read image in grayscale
+z=imread("people.jpg",0);
+image=imread("pls.jpg",0);
+stacksize('max')
+//call the function to detect features for image- z
+pls=detectGFTTFeatures(z,"minDistance",4);
+// call the function to detect features for image- image
+pls1=detectGFTTFeatures(image);
+//match features using the features detected using the above function
+[op ir]=matchFeatures(pls.Features,pls1.Features);
+//finally draw those matches
+final=drawMatch(z,image,pls.KeyPoints,pls1.KeyPoints,op,ir);
+imshow(final)
+
+ +
+ + + + + + +
Report an issue
+ << detectAkazeFeatures + + + FOSSEE_Image_Processing_Toolbox + + + detectKAZEFeatures >> + +
+
+
+ + diff --git a/help/en_US/scilab_en_US_help/detectKAZEFeatures.html b/help/en_US/scilab_en_US_help/detectKAZEFeatures.html new file mode 100755 index 0000000..d4a1f4f --- /dev/null +++ b/help/en_US/scilab_en_US_help/detectKAZEFeatures.html @@ -0,0 +1,91 @@ + + + detectKAZEFeatures + + + +
+ + + + +
+ << detectGFTTFeatures + + + FOSSEE_Image_Processing_Toolbox + + + ellipse >> + +
+
+
+ + + + FOSSEE_Image_Processing_Toolbox >> FOSSEE_Image_Processing_Toolbox > detectKAZEFeatures + +

+

detectKAZEFeatures

+

This function is used to detect KAZE Features in a grayscale Image.

+ + +

Calling Sequence

+ 
result = detectKAZEFeatures(Image);
+result = detectKAZEFeatures(Image,Name,Value,....)
+ +

Parameters

+
NumOctaves : +

(Optional)The number of Octaves that the detector uses. (Default - 4) The value must be an integer scalar in between 1 and 4.

+
diffusivity: +

-KAZE's diffusivity'

+
ROI or Mask : +

(Optional) Region Of Interest. This is taken as a vector [u v width height]. When specified, the function detects the key points within region of area width*height with u and v being the top left corner coordinates.

+ +

Description

+

This function is used to detect KAZE Features in a grayscale Image.

+

+ +

Examples

+ 
//read image in grayscale
+z=imread("people.jpg",0);
+image=imread("pls.jpg",0);
+stacksize('max')
+//call the function to detect features for image- z
+pls=detectKAZEFeatures(z,"diffusivity",2.1);
+// call the function to detect features for image- image
+pls1=detectKAZEFeatures(image);
+//match features using the features detected using the above function
+[op ir]=matchFeatures(pls.Features,pls1.Features);
+//finally draw those matches
+final=drawMatch(z,image,pls.KeyPoints,pls1.KeyPoints,op,ir);
+imshow(final)
+
+ +
+ + + + + + +
Report an issue
+ << detectGFTTFeatures + + + FOSSEE_Image_Processing_Toolbox + + + ellipse >> + +
+
+
+ + diff --git a/help/en_US/scilab_en_US_help/detectMinEigenFeatures.html b/help/en_US/scilab_en_US_help/detectMinEigenFeatures.html new file mode 100755 index 0000000..85b8387 --- /dev/null +++ b/help/en_US/scilab_en_US_help/detectMinEigenFeatures.html @@ -0,0 +1,84 @@ + + + detectMinEigenFeatures + + + +
+ + + + +
+ << detectAkazeFeatures + + + FOSSEE_Image_Processing_Toolbox + + + ellipse >> + +
+
+
+ + + + FOSSEE_Image_Processing_Toolbox >> FOSSEE_Image_Processing_Toolbox > detectMinEigenFeatures + +

+

detectMinEigenFeatures

+

This function is used to find corner points in an image using Minimum Eigen Value algorithm.

+ + +

Calling Sequence

+ 
points = detectMinEigenFeatures(I);
+points = detectMinEigenFeatures(I, Name, Value, ...);
+ +

Parameters

+
points: +

Structure of corner points

+
I: +

Input image to detectHarrisFeatures()

+
MinQuality: +

(Optional) Minimum accepted quality of corners (Default- 0.01)

+
FilterSize: +

(Optional) Dimension of Gaussian Filter (Default: 5)

+
ROI: +

(Optional) Rectangular region for corner detection

+ +

Description

+

This function detects corners in an image I. These corner points are used to extract features and hence recognize the contents of an image.

+

+ +

Examples

+ 
I = imread('sample.jpg');
+points = detectMinEigenFeatures(I);
+
+ +
+ + + + + + +
Report an issue
+ << detectAkazeFeatures + + + FOSSEE_Image_Processing_Toolbox + + + ellipse >> + +
+
+
+ + diff --git a/help/en_US/scilab_en_US_help/ellipse.html b/help/en_US/scilab_en_US_help/ellipse.html new file mode 100755 index 0000000..4ec5ea9 --- /dev/null +++ b/help/en_US/scilab_en_US_help/ellipse.html @@ -0,0 +1,111 @@ + + + ellipse + + + +
+ + + + +
+ << detectKAZEFeatures + + + FOSSEE_Image_Processing_Toolbox + + + ellipse2poly >> + +
+
+
+ + + + FOSSEE_Image_Processing_Toolbox >> FOSSEE_Image_Processing_Toolbox > ellipse + +

+

ellipse

+

This function draws a simple or thick elliptic arc or fills an ellipse sector.

+ + +

Calling Sequence

+ 
elli=ellipse(inputImage,xcor,ycor,firstAxis,secondAxis,angle,startAngle,endAngle,r,g,b);
+elli=ellipse(inputImage,xcor,ycor,firstAxis,secondAxis,angle,startAngle,endAngle,r,g,b,thickness);
+elli=ellipse(inputImage,xcor,ycor,firstAxis,secondAxis,angle,startAngle,endAngle,r,g,b,thickness,linetype);
+elli=ellipse(inputImage,xcor,ycor,firstAxis,secondAxis,angle,startAngle,endAngle,r,g,b,thickness,linetype,shift);
+ +

Parameters

+
elli: +

The output image with the ellipse drawn in it.

+
inputImage: +

The input image on which the ellipse should be drawn.

+
xcor: +

X-coordinate of the center

+
ycor: +

Y-coordinate of the center

+
firstAxis: +

the first axis of the ellipse.

+
secondAxis: +

the second axis of the ellipse.

+
angle: +

Ellipse rotation angle in degrees.

+
startAngle: +

Starting angle of the elliptic arc in degrees.

+
endAngle: +

Ending angle of the elliptic arc in degrees.

+
r: +

red color value of the ellipse.It should be in the range 0-255.

+
b: +

blue color value of the ellipse.It should be in the range 0-255.

+
g: +

green color value of the ellipse.It should be in the range 0-255.

+
thickness: +

Line thickness.

+
linetype: +

Type of the ellipse boundary.It can be 0 or 4 or 8.

+
shift: +

Number of fractional bits in the point coordinates.

+ +

Description

+

+

This function draws a simple or thick elliptic arc or fills an ellipse sector.

+

+ +

Examples

+ 
// read the input image on which the ellipse shpuld be drawn.
+z=imread("lena.jpeg",0);
+call the function
+elli=ellipse(z,0,0,45,45,45,0,45,255,0,0,1,0);
+// show the image drawn on it.
+imshow(elli)
+
+ +
+ + + + + + +
Report an issue
+ << detectKAZEFeatures + + + FOSSEE_Image_Processing_Toolbox + + + ellipse2poly >> + +
+
+
+ + diff --git a/help/en_US/scilab_en_US_help/erode.html b/help/en_US/scilab_en_US_help/erode.html new file mode 100755 index 0000000..c6061fc --- /dev/null +++ b/help/en_US/scilab_en_US_help/erode.html @@ -0,0 +1,89 @@ + + + erode + + + +
+ + + + +
+ << epipolarlines + + + FOSSEE_Image_Processing_Toolbox + + + estimateFundamentalMat >> + +
+
+
+ + + + FOSSEE_Image_Processing_Toolbox >> FOSSEE_Image_Processing_Toolbox > erode + +

+

erode

+

This function Erodes an image by using a specific structuring element.

+ + +

Calling Sequence

+ 
z=imread("lena.jpeg");
+ero=erode(inputImage,kernel,anchorX,anchorY,iterations);
+ +

Parameters

+
z: +

input image which should be eroded.

+
ero: +

the output eroded image

+
kernel: +

structuring element used for erosion

+
anchorX: +

x coordinate of Anchor.

+
anchorY: +

y coordinate of Anchor.

+
Anchor: +

position of the anchor within the element.

+
Iterations: +

number of times erosion is applied.

+ +

Description

+

+

This function Erodes an image by using a specific structuring element.

+

+ +

Examples

+ 
z=imread("lena.jpeg");
+ero=erode(z,[6 4],1,1,4);
+
+ +
+ + + + + + +
Report an issue
+ << epipolarlines + + + FOSSEE_Image_Processing_Toolbox + + + estimateFundamentalMat >> + +
+
+
+ + diff --git a/help/en_US/scilab_en_US_help/estimateFundamentalMat.html b/help/en_US/scilab_en_US_help/estimateFundamentalMat.html new file mode 100755 index 0000000..fb69a0c --- /dev/null +++ b/help/en_US/scilab_en_US_help/estimateFundamentalMat.html @@ -0,0 +1,87 @@ + + + estimateFundamentalMat + + + +
+ + + + +
+ << erode + + + FOSSEE_Image_Processing_Toolbox + + + extractHOGFeatures >> + +
+
+
+ + + + FOSSEE_Image_Processing_Toolbox >> FOSSEE_Image_Processing_Toolbox > estimateFundamentalMat + +

+

estimateFundamentalMat

+

It returns the 3-by-3 fundamental matrix corresponding to the input points

+ + +

Calling Sequence

+ 
fundamentalMat=estimateFundamentalMatrix(matchedPoints1,matchedPoints2);
+fundamentalMat=estimateFundamentalMatrix(matchedPoints1,matchedPoints2,'method','RANSAC','param1',2,'param2',0.99);
+ +

Parameters

+
matchedPoints1: +

M-by-2 array of first image points. These points can be SURFPoints, MSERRegions, cornerPoints.

+
matchedPoints2: +

M-by-2 array of the second image points of the same size and format as matchedPoints1.

+
method: +

method for computing fundamental matrix. Possible methods are 7POINT,8POINT,RANSAC,LMEDS and RANSAC is the default one.

+
param1: +

It indiacates maximum distance from a point to an epipolar line in pixels

+
param2: +

It specifies a desirable level of confidence

+ +

Description

+

estimateFundamentalMatrix function calculates a fundamental matrix from the corresponding points in two images.

+

+ +

Examples

+ 
I=imread("lena_left.jpeg");
+cornerPoints1=detectMinEigenFeatures(I);
+I2=imread("lena_right.jpeg");
+cornerPoints2=detectMinEigenFeatures(I2);
+fundamentalMat=(cornerPoints1.Location,cornerPoints2.Location);
+
+ +
+ + + + + + +
Report an issue
+ << erode + + + FOSSEE_Image_Processing_Toolbox + + + extractHOGFeatures >> + +
+
+
+ + diff --git a/help/en_US/scilab_en_US_help/fastNlMeansDenoising.html b/help/en_US/scilab_en_US_help/fastNlMeansDenoising.html new file mode 100644 index 0000000..c7f7e88 --- /dev/null +++ b/help/en_US/scilab_en_US_help/fastNlMeansDenoising.html @@ -0,0 +1,99 @@ + + + fastNlMeansDenoising + + + +
+ + + + +
+ << denoiseColor + + + FOSSEE Image Processing Toolbox + + + findContours >> + +
+
+
+ + + + FOSSEE Image Processing Toolbox >> FOSSEE Image Processing Toolbox > fastNlMeansDenoising + +

+

fastNlMeansDenoising

+

Removes gaussian white noise from images

+ + +

Calling Sequence

+ 
outputImage=fastNlMeansDenoising(src, strengthFilter, tempWindowSize, searchWindowSize, choice)
+ +

Parameters

+
src : +

Input 8-bit 1-channel, 2-channel, 3-channel or 4-channel image.

+
strengthFilter : +

Parameter regulating filter strength.

+
templateWindowSize : +

Size in pixels of the template patch that is used to compute weights. Should be odd.

+
searchWindowSize : +

Size in pixels of the window that is used to compute weighted average for given pixel. Should be odd.

+
choice : +

Chooses the method

+ +

Description

+

Perform image denoising using Non-local Means Denoising algorithm with several computational optimizations. Noise expected to be a gaussian white noise.

+

+ +

Examples

+ 
a = imread("man.jpg");
+strengthFilter = 30;
+tempWindowSize = 7;
+searchWindowSize = 40;
+choice=2;
+k = fastNlMeansDenoising(a, strengthFilter, tempWindowSize, searchWindowSize,choice);
+ +

Examples

+ 
a = imread("noise.jpg");
+strengthFilter = 100;
+tempWindowSize = 7;
+searchWindowSize = 50;
+choice = 3;
+k = fastNlMeansDenoising(a, strengthFilter, tempWindowSize, searchWindowSize,choice);
+ +

Authors

+
  • Shubham Lohakare, NITK Surathkal
    • +
  • Ashish Mantosh, NIT Rourkela
+
+ +
+ + + + + + +
Report an issue
+ << denoiseColor + + + FOSSEE Image Processing Toolbox + + + findContours >> + +
+
+
+ + diff --git a/help/en_US/scilab_en_US_help/findContours.html b/help/en_US/scilab_en_US_help/findContours.html new file mode 100644 index 0000000..43a5167 --- /dev/null +++ b/help/en_US/scilab_en_US_help/findContours.html @@ -0,0 +1,96 @@ + + + findContours + + + +
+ + + + +
+ << fastNlMeansDenoising + + + FOSSEE Image Processing Toolbox + + + histeq >> + +
+
+
+ + + + FOSSEE Image Processing Toolbox >> FOSSEE Image Processing Toolbox > findContours + +

+

findContours

+

Finds contours in an image

+ + +

Calling Sequence

+ 
outputMat = findContours(inputImage, Mode, method, point_x, point_y)
+ +

Parameters

+
inputImage : +

The input image

+
Mode : +

Contour retrieval mode (Enter 1 for CV_RETR_EXTERNAL, 2 for CV_RETR_LIST, 3 for CV_RETR_CCOMP, 4 for CV_RETR_TREE)

+
method : +

Contour approximation method (Enter 1 for CV_CHAIN_APPROX_NONE, 2 for CV_CHAIN_APPROX_SIMPLE, 3 for CV_CHAIN_APPROX_TC89_L1, 4 for CV_CHAIN_APPROX_TC89_KCOS)

+
point_x : +

x-coordinate for point offset

+
point_y : +

y-coordinate for point offset

+ +

Description

+

The function retrieves contours from the images using the algorithm [Suzuki85]. The contours are a useful tool for shape analysis and object detection and recognition.

+

+ +

Examples

+ 
a = imread("lena.jpeg");
+k = finContours(a,3,2,10,10);
+ +

Examples

+ 
a = imread("photo.jpeg");
+k = findContours(a,1,1,40,60);
+ +

Examples

+ 
a = imread("photo1.jpg");
+k = findContours(a,2,3,50,50);
+ +

Authors

+
  • Abhilasha Sancheti
    • +
  • Shubham Lohakare
    • +
  • Sukul Bagai
+
+ +
+ + + + + + +
Report an issue
+ << fastNlMeansDenoising + + + FOSSEE Image Processing Toolbox + + + histeq >> + +
+
+
+ + diff --git a/help/en_US/scilab_en_US_help/findHomography.html b/help/en_US/scilab_en_US_help/findHomography.html new file mode 100755 index 0000000..38dee6f --- /dev/null +++ b/help/en_US/scilab_en_US_help/findHomography.html @@ -0,0 +1,94 @@ + + + findHomography + + + +
+ + + + +
+ << extractLBPFeatures + + + FOSSEE_Image_Processing_Toolbox + + + fitellipse >> + +
+
+
+ + + + FOSSEE_Image_Processing_Toolbox >> FOSSEE_Image_Processing_Toolbox > findHomography + +

+

findHomography

+

This Function Finds a perspective transformation between two planes.

+ + +

Calling Sequence

+ 
homographyMatrix=findHomography(points1,points2);
+homographyMatrix=findHomography(points1,points2,method);
+homographyMatrix=findHomography(points1,points2,method,threshold);
+ +

Parameters

+
homographyMatrix: +

perspective transformation H between the source and the destination planes

+
points1: +

Coordinates of the points in the original plane

+
points2: +

Coordinates of the points in the target plane

+
method: +

Method used to computed a homography matrix.

+
threshold: +

Maximum allowed reprojection error to treat a point pair as an inlier.

+
Note: +

the number of points should be same in the points1 and points2

+ +

Description

+

The function finds and returns the perspective transformation H between the source and the destination planes

+

+ +

Examples

+ 
read first image
+z=imread("lena.jpeg",0);
+get points from first image
+yo=detectGFTTFeatures(z);
+read second image
+image=imread("lena2.jpg",0);
+yo1=detectGFTTFeatures(image);
+// call function with same number of points in both(first arg has 594 so passig 594 points from second arg)
+lou=findHomography(yo.KeyPoints,yo1.KeyPoints(1:594,:));
+
+ +
+ + + + + + +
Report an issue
+ << extractLBPFeatures + + + FOSSEE_Image_Processing_Toolbox + + + fitellipse >> + +
+
+
+ + diff --git a/help/en_US/scilab_en_US_help/fitellipse.html b/help/en_US/scilab_en_US_help/fitellipse.html new file mode 100755 index 0000000..11ebb1e --- /dev/null +++ b/help/en_US/scilab_en_US_help/fitellipse.html @@ -0,0 +1,82 @@ + + + fitellipse + + + +
+ + + + +
+ << findHomography + + + FOSSEE_Image_Processing_Toolbox + + + graycoprops >> + +
+
+
+ + + + FOSSEE_Image_Processing_Toolbox >> FOSSEE_Image_Processing_Toolbox > fitellipse + +

+

fitellipse

+

The function calculates the ellipse that fits (in a least-squares sense) a set of 2D points best of all.

+ + +

Calling Sequence

+ 
felli=fitellipse(points);
+ +

Parameters

+
felli: +

a struct containing all the details about the ellipse Params.

+
points: +

Input 2D point set

+ +

Description

+

+

The function calculates the ellipse that fits (in a least-squares sense) a set of 2D points best of all.

+

+ +

Examples

+ 
// read image
+z=imread("lena.jpeg",0);
+//get points using KAZE detector or the points can also be hardcoded.
+pio=detectKAZEFeatures(z);
+// call function
+sss=fitellipse(pio.KeyPoints)
+
+ +
+ + + + + + +
Report an issue
+ << findHomography + + + FOSSEE_Image_Processing_Toolbox + + + graycoprops >> + +
+
+
+ + diff --git a/help/en_US/scilab_en_US_help/graycoprops.html b/help/en_US/scilab_en_US_help/graycoprops.html new file mode 100755 index 0000000..3c247ce --- /dev/null +++ b/help/en_US/scilab_en_US_help/graycoprops.html @@ -0,0 +1,97 @@ + + + graycoprops + + + +
+ + + + +
+ << fitellipse + + + FOSSEE_Image_Processing_Toolbox + + + imfuse >> + +
+
+
+ + + + FOSSEE_Image_Processing_Toolbox >> FOSSEE_Image_Processing_Toolbox > graycoprops + +

+

graycoprops

+

+ + +

Calling Sequence

+ 
z=imread("lena.jpeg"); //in grayscale or color
+//Note: z can be a image or simply a Matrix.
+gray=graycoprops(z)   //get all 4 properties
+gray=graycoprops(z,"contrast") //compute only contrast
+gray=graycoprops(z,["contrast" "energy"]) //compute contrast and energy.the properties can be passed in any order
+gray=graycoprops(z,["contrast" "correlation" "energy"])
+gray=graycoprops(z,["contrast" "correlation" "energy" "homogeneity"])
+ +

Parameters

+
gray: +

A struct containing all the parameters

+
z: +

A image or a matrix

+
contrast: +

a measure of the intensity contrast between a pixel and its neighbor over the whole image.

+
energy: +

the sum of squared elements

+
homogeneity: +

a value that measures the closeness of the distribution of elements.

+
correlation: +

a measure of how correlated a pixel is to its neighbor over the whole image

+ +

Description

+

This function computes the Properties of gray-level co-occurrence matrix.The properties being "correlation","contrast","energy" and "homogeneity".

+

+

+ +

Examples

+ 
//compute for a image
+z=imread("lena.jpeg",0);
+sss=graycoprops(z,["contrast"])
+
+//compute for a matrix
+glcm = [0 1 2 3;1 1 2 3;1 0 2 0;0 0 0 3]
+sss=graycoprops(glcm,["contrast" "energy" "correlation"])
+
+ +
+ + + + + + +
Report an issue
+ << fitellipse + + + FOSSEE_Image_Processing_Toolbox + + + imfuse >> + +
+
+
+ + diff --git a/help/en_US/scilab_en_US_help/histeq.html b/help/en_US/scilab_en_US_help/histeq.html new file mode 100644 index 0000000..c81d239 --- /dev/null +++ b/help/en_US/scilab_en_US_help/histeq.html @@ -0,0 +1,90 @@ + + + histeq + + + +
+ + + + +
+ << findContours + + + FOSSEE Image Processing Toolbox + + + imadd >> + +
+
+
+ + + + FOSSEE Image Processing Toolbox >> FOSSEE Image Processing Toolbox > histeq + +

+

histeq

+

Equalizes the histogram of an image

+ + +

Calling Sequence

+ 
outputImage = histeq (inputImage)
+ +

Parameters

+
inputImage : +

The input image for which the histogram has to be equalised

+ +

Description

+

The function equalizes the histogram of the input image using the following algorithm: 1. Calculate the histogram H for src. 2. Normalize the histogram so that the sum of histogram bins is 255. 3. Compute the integral of the histogram. 4. Transform the image using H' as a look-up table: dst(x,y) = H'(src(x,y)). The algorithm normalizes the brightness and increases the contrast of the image.

+

+ +

Examples

+ 
a = imread("lena.jpeg");
+k = histeq(a);
+imshow(k);
+ +

Examples

+ 
a = imread("bryan.jpg");
+k = histeq(a);
+imshow(k);
+ +

Examples

+ 
a = imread("photo.jpg");
+k = histeq(a);
+imshow(k);
+ +

Authors

+
  • Shubham Lohakare, NITK Surathkal
    • +
  • Priyanka Hiranandani, NIT Surat
+
+ +
+ + + + + + +
Report an issue
+ << findContours + + + FOSSEE Image Processing Toolbox + + + imadd >> + +
+
+
+ + diff --git a/help/en_US/scilab_en_US_help/imadd.html b/help/en_US/scilab_en_US_help/imadd.html new file mode 100644 index 0000000..aa3865c --- /dev/null +++ b/help/en_US/scilab_en_US_help/imadd.html @@ -0,0 +1,88 @@ + + + imadd + + + +
+ + + + +
+ << histeq + + + FOSSEE Image Processing Toolbox + + + imcomplement >> + +
+
+
+ + + + FOSSEE Image Processing Toolbox >> FOSSEE Image Processing Toolbox > imadd + +

+

imadd

+

Add the contents of 2 matrices or images and store it in another

+ + +

Calling Sequence

+ 
outputMat = imadd(input1, input2)
+ +

Parameters

+
input1 : +

First input matrix or an image

+
input2 : +

Second input matrix or image

+ +

Description

+

Z = imadd(X,Y) adds each element in array X with the corresponding element in array Y and returns the sum in the corresponding element of the output array Z. X and Y are real, nonsparse numeric arrays with the same size and class, or Y is a scalar double. Z has the same size and class as X, unless X is logical, in which case Z is double.

+

+ +

Examples

+ 
a = [1 5 6;4 2 3];
+b = [8 10 15;5 1 9];
+c = imadd(a,b);
+ +

Examples

+ 
a = imread("lena.jpeg");
+b = imread("lena1.jpeg");
+c = imadd(a,b);
+imshow(c)
+ +

Authors

+
  • Tess Zacharias
    • +
  • Shubham Lohakare
+
+ +
+ + + + + + +
Report an issue
+ << histeq + + + FOSSEE Image Processing Toolbox + + + imcomplement >> + +
+
+
+ + diff --git a/help/en_US/scilab_en_US_help/imcomplement.html b/help/en_US/scilab_en_US_help/imcomplement.html new file mode 100644 index 0000000..56f1886 --- /dev/null +++ b/help/en_US/scilab_en_US_help/imcomplement.html @@ -0,0 +1,85 @@ + + + imcomplement + + + +
+ + + + +
+ << imadd + + + FOSSEE Image Processing Toolbox + + + imcontour >> + +
+
+
+ + + + FOSSEE Image Processing Toolbox >> FOSSEE Image Processing Toolbox > imcomplement + +

+

imcomplement

+

Computes the complement of the image

+ + +

Calling Sequence

+ 
compMat = imcomplement(srcImg)
+ +

Parameters

+
srcImg : +

Input image

+ +

Description

+

In the complement of a binary image, zeros become ones and ones become zeros; black and white are reversed. In the complement of an intensity or RGB image, each pixel value is subtracted from the maximum pixel value supported by the class (or 1.0 for double-precision images) and the difference is used as the pixel value in the output image. In the output image, dark areas become lighter and light areas become darker.

+

+ +

Examples

+ 
a = imread("lena.jpeg");
+k = imcomplement(a);
+imshow(k)
+ +

Examples

+ 
a = imread("photo1.jpg");
+k = imcomplement(a);
+imshow(k)
+ +

Authors

+
  • Tess Zacharias
    • +
  • Shubham Lohakare
+
+ +
+ + + + + + +
Report an issue
+ << imadd + + + FOSSEE Image Processing Toolbox + + + imcontour >> + +
+
+
+ + diff --git a/help/en_US/scilab_en_US_help/imcontour.html b/help/en_US/scilab_en_US_help/imcontour.html new file mode 100644 index 0000000..0a55514 --- /dev/null +++ b/help/en_US/scilab_en_US_help/imcontour.html @@ -0,0 +1,90 @@ + + + imcontour + + + +
+ + + + +
+ << imcomplement + + + FOSSEE Image Processing Toolbox + + + imdecolor >> + +
+
+
+ + + + FOSSEE Image Processing Toolbox >> FOSSEE Image Processing Toolbox > imcontour + +

+

imcontour

+

Draws a contour plot for the input image

+ + +

Calling Sequence

+ 
contourMat = imcontour(srcImg)
+ +

Parameters

+
srcImg : +

THe input image

+ +

Description

+

The function draws contour outlines in the image.

+

+ +

Examples

+ 
a = imread("lena.jpeg");
+k = imcontour(a);
+imshow(k)
+ +

Examples

+ 
a = imread("photo1.jpg");
+k = imcontour(a);
+imshow(k)
+ +

Examples

+ 
a = imread("bryan.jpg");
+k = imcontour(a);
+imshow(k)
+ +

Authors

+
  • Tess zacharias
    • +
  • Shubham Lohakare
+
+ +
+ + + + + + +
Report an issue
+ << imcomplement + + + FOSSEE Image Processing Toolbox + + + imdecolor >> + +
+
+
+ + diff --git a/help/en_US/scilab_en_US_help/imdecolor.html b/help/en_US/scilab_en_US_help/imdecolor.html new file mode 100644 index 0000000..a991aa5 --- /dev/null +++ b/help/en_US/scilab_en_US_help/imdecolor.html @@ -0,0 +1,94 @@ + + + imdecolor + + + +
+ + + + +
+ << imcontour + + + FOSSEE Image Processing Toolbox + + + imfill >> + +
+
+
+ + + + FOSSEE Image Processing Toolbox >> FOSSEE Image Processing Toolbox > imdecolor + +

+

imdecolor

+

Decolors and color boosts an image giving 2 outputs for the same respectively.

+ + +

Calling Sequence

+ 
[outImg1, outImg2] = imdecolor(srcImg1)
+ +

Parameters

+
srcImg1 : +

It is a 3-channel input image.

+
outImg1 : +

It is a grayscale image of the image passed as input.

+
outImg2 : +

It is a color boosted image of the image passed as input.

+ +

Description

+

This function is used to decolor an image and also add a boost to it's color +The output are 2 images, one is a grayscale and the other is a color boosted image

+

+ +

Examples

+ 
var=imread("ImageName");
+[decoloredImage,colorBoostedImage] = imdecolor(var);
+PRESS ENTER
+imshow(decoloredImage); shows the decolored Image
+imshow(colorBoostedImage); shows the color boosted image
+ +

Examples

+ 
a = imread("images.jpeg");
+[b, c] = imdecolor(a);
+PRESS ENTER
+imshow(b); shows the decolored Image
+imshow(c); shows the color boosted image
+ +

Authors

+
  • Shubham Lohakare, NITK Surathkal
    • +
  • Ashish Mantosh, NIT Rourkela
+
+ +
+ + + + + + +
Report an issue
+ << imcontour + + + FOSSEE Image Processing Toolbox + + + imfill >> + +
+
+
+ + diff --git a/help/en_US/scilab_en_US_help/imdivide.html b/help/en_US/scilab_en_US_help/imdivide.html new file mode 100644 index 0000000..da42770 --- /dev/null +++ b/help/en_US/scilab_en_US_help/imdivide.html @@ -0,0 +1,92 @@ + + + imdivide + + + +
+ + + + +
+ << imdecolor + + + FOSSEE Image Processing Toolbox + + + imfill >> + +
+
+
+ + + + FOSSEE Image Processing Toolbox >> FOSSEE Image Processing Toolbox > imdivide + +

+

imdivide

+

Divides one image with another or divide image by constant.

+ + +

Calling Sequence

+ 
outputMat = imdivide(input1, input2)
+ +

Parameters

+
input1 : +

Image or an array

+
input2 : +

Image or an array of same size or a scalar

+ +

Description

+

imdivide takes 2 inputs, either both images which should be of the same size or one image and another scalar which is used as the divisor. Also the inputs can be two arrays of the same size or one array and one scalar. The output is the quotient of the two.

+

+ +

Examples

+ 
k = imread("lena.jpeg");
+p = imdivide(k,2);
+imshow(p);
+ +

Examples

+ 
k = imread("photo.jpg");
+p = imdivide(k,0.8);
+imshow(p);
+ +

Examples

+ 
a = [10 20;50 10];
+b = 5;
+p = imdivide(a,b);
+ +

Authors

+
  • Tess Zacharias
    • +
  • Shubham Lohakare
+
+ +
+ + + + + + +
Report an issue
+ << imdecolor + + + FOSSEE Image Processing Toolbox + + + imfill >> + +
+
+
+ + diff --git a/help/en_US/scilab_en_US_help/imfill.html b/help/en_US/scilab_en_US_help/imfill.html new file mode 100644 index 0000000..b8fd6e6 --- /dev/null +++ b/help/en_US/scilab_en_US_help/imfill.html @@ -0,0 +1,93 @@ + + + imfill + + + +
+ + + + +
+ << imdecolor + + + FOSSEE Image Processing Toolbox + + + iminpaint >> + +
+
+
+ + + + FOSSEE Image Processing Toolbox >> FOSSEE Image Processing Toolbox > imfill + +

+

imfill

+

Fills in the regions and holes in an image.

+ + +

Calling Sequence

+ 
[outputImage] = imfill(srcImg)
+[outputImage] = imfill(srcImg,locations)
+ +

Parameters

+
srcImg : +

It is the input image

+
locations : +

If locations is a P-by-1 vector, it contains the linear indices of starting locations. If locations is P-by-ndims(BW) matrix, each row contains the array indices of one of the starting locations.

+ +

Description

+

The function performs a flood-fill operation on the pixels of the input image.

+

+ +

Examples

+ 
k = imread("lena.jpeg");
+im = imfill(k, [1 1; 10 10; 11 12]);
+imshow(im);
+ +

Examples

+ 
k = imread("lena1.jpeg");
+im = imfill(k, [1 1; 20 20; 11 12;50 50;]);
+imshow(im);
+ +

Examples

+ 
k = imread("penguin.jpg");
+p = imfill(k);
+imshow(p);
+ +

Authors

+
  • Vinay Bhat
    • +
  • Shubham Lohakare
+
+ +
+ + + + + + +
Report an issue
+ << imdecolor + + + FOSSEE Image Processing Toolbox + + + iminpaint >> + +
+
+
+ + diff --git a/help/en_US/scilab_en_US_help/iminpaint.html b/help/en_US/scilab_en_US_help/iminpaint.html new file mode 100644 index 0000000..a00b9e8 --- /dev/null +++ b/help/en_US/scilab_en_US_help/iminpaint.html @@ -0,0 +1,95 @@ + + + iminpaint + + + +
+ + + + +
+ << imfill + + + FOSSEE Image Processing Toolbox + + + immultiply >> + +
+
+
+ + + + FOSSEE Image Processing Toolbox >> FOSSEE Image Processing Toolbox > iminpaint + +

+

iminpaint

+

Inpaints the unwanted area in an image using the neighboring pixel points

+ + +

Calling Sequence

+ 
pImg = iminpaint(srcImg1,maskedRectangle,radius,methodNum)
+ +

Parameters

+
srcImg : +

It is the input image

+
maskedRectangle: +

It is a vector of double used which contains the co-ordinates of the masking rectangle

+
radius : +

Radius of a circular neighborhood of each point inpainted that is considered by the algorithm.

+
methodNum : +

Inpainting method that could be one of the following,INPAINT_NS Navier-Stokes based method or INPAINT_TELEA Method by Alexandru Telea

+ +

Description

+

The function reconstructs the selected image area from the pixel near the area boundary. The function may be used to remove dust and scratches from a scanned photo, or to remove undesirable objects from still images.

+

+ +

Examples

+ 
a = imread("p1.jpeg");
+b = [210,40,100,200];
+typeOfMethod = 2;
+radius = 50;
+c = iminpaint(a,b,radius,typeOfMethod);
+ +

Examples

+ 
a = imread("orig.jpg");
+b = [100,157,120,150];
+typeOfMethod = 1;
+radius = 5;
+c = iminpaint(a,b,radius,typeOfMethod);
+ +

Authors

+
  • Shubham Lohakare, NITK Surathkal
    • +
  • Ashish Mantosh, NIT Rourkela
+
+ +
+ + + + + + +
Report an issue
+ << imfill + + + FOSSEE Image Processing Toolbox + + + immultiply >> + +
+
+
+ + diff --git a/help/en_US/scilab_en_US_help/immultiply.html b/help/en_US/scilab_en_US_help/immultiply.html new file mode 100644 index 0000000..a8014ea --- /dev/null +++ b/help/en_US/scilab_en_US_help/immultiply.html @@ -0,0 +1,93 @@ + + + immultiply + + + +
+ + + + +
+ << iminpaint + + + FOSSEE Image Processing Toolbox + + + imrotate >> + +
+
+
+ + + + FOSSEE Image Processing Toolbox >> FOSSEE Image Processing Toolbox > immultiply + +

+

immultiply

+

Multiply the contents of 2 matrices and store it in another

+ + +

Calling Sequence

+ 
multiplyMat = immultiply(input1, input2)
+ +

Parameters

+
input1 : +

First input matrix or an image

+
input2 : +

Second input matrix or image

+ +

Description

+

p=immultiply(a,b) multiplies each of the element in the first argument's array with the corrresponding element in the second argument's array and the answer is stored in p.

+

+ +

Examples

+ 
a = imread("lena.jpeg");
+k = immultiply(a,2);
+imshow(k)
+ +

Examples

+ 
a = imread("photo.jpg");
+k = immultiply(a,0.5);
+imshow(k)
+ +

Examples

+ 
a = [1 2 3; 4 5 6];
+b = [10 20 30;10 20 30];
+k = immultiply(a,b);
+disp(k)
+ +

Authors

+
  • Tess Zacharias
    • +
  • Shubham Lohakare
+
+ +
+ + + + + + +
Report an issue
+ << iminpaint + + + FOSSEE Image Processing Toolbox + + + imrotate >> + +
+
+
+ + diff --git a/help/en_US/scilab_en_US_help/imread.html b/help/en_US/scilab_en_US_help/imread.html new file mode 100755 index 0000000..12094f4 --- /dev/null +++ b/help/en_US/scilab_en_US_help/imread.html @@ -0,0 +1,108 @@ + + + imread + + + +
+ + + + +
+ << impixel + + + FOSSEE_Image_Processing_Toolbox + + + imsharpen >> + +
+
+
+ + + + FOSSEE_Image_Processing_Toolbox >> FOSSEE_Image_Processing_Toolbox > imread + +

+

imread

+

+ + +

Calling Sequence

+ 
image=imread("image_path");
+image=imread("image_path",options)
+ +

Parameters

+
image_path: +

a String which contains the path of the image that is to be read.

+
options: +

an Integer, containing the option for user to specify. See below for details.

+
0 : +

convert image to the single channel grayscale image.

+
1 : +

convert image to the 3 channel BGR color image.

+
2 : +

load 16-bit/32-bit image when the input image has the corresponding depth, otherwise convert it to 8-bit.

+
4 : +

the image is read in any possible color format.

+
8 : +

use the gdal driver for loading the image.

+
16 : +

convert image to the single channel grayscale image and the image size reduced 1/2.

+
17 : +

convert image to the 3 channel BGR color image and the image size reduced 1/2.

+
32 : +

convert image to the single channel grayscale image and the image size reduced 1/4.

+
33 : +

convert image to the 3 channel BGR color image and the image size reduced 1/4.

+
64 : +

convert image to the single channel grayscale image and the image size reduced 1/8.

+
65 : +

convert image to the 3 channel BGR color image and the image size reduced 1/8.

+
128 : +

do not rotate the image according to EXIF's orientation flag.

+ +

Description

+

This function is used to Read/Load an image from the disk

+

+

+ +

Examples

+ 
Read a image as it is(Unchanged).
+//Calling imread
+image=imread("test.jpg");
+
+Read image as grayscale
+//Calling imread
+image=imread("test.jpg",0);
+
+ +
+ + + + + + +
Report an issue
+ << impixel + + + FOSSEE_Image_Processing_Toolbox + + + imsharpen >> + +
+
+
+ + diff --git a/help/en_US/scilab_en_US_help/imresize.html b/help/en_US/scilab_en_US_help/imresize.html new file mode 100755 index 0000000..b3aec70 --- /dev/null +++ b/help/en_US/scilab_en_US_help/imresize.html @@ -0,0 +1,83 @@ + + + imresize + + + +
+ + + + +
+ << imread + + + FOSSEE_Image_Processing_Toolbox + + + imsharpen >> + +
+
+
+ + + + FOSSEE_Image_Processing_Toolbox >> FOSSEE_Image_Processing_Toolbox > imresize + +

+

imresize

+

This function is used to resize the image

+ + +

Calling Sequence

+ 
newImage=imresize(inputImage,alpha,beta);
+ +

Parameters

+
newImage: +

the new resized image

+
inputImage: +

the image which should be resized.

+
alpha: +

new number of rows.

+
beta: +

new number of columns.

+ +

Description

+

+

This function is used to resize the image

+

+ +

Examples

+ 
z=imread("lena.jpeg",0);
+zz=imresize(z,35,12);
+imshow(zz)
+
+ +
+ + + + + + +
Report an issue
+ << imread + + + FOSSEE_Image_Processing_Toolbox + + + imsharpen >> + +
+
+
+ + diff --git a/help/en_US/scilab_en_US_help/imrotate.html b/help/en_US/scilab_en_US_help/imrotate.html new file mode 100644 index 0000000..7e73758 --- /dev/null +++ b/help/en_US/scilab_en_US_help/imrotate.html @@ -0,0 +1,95 @@ + + + imrotate + + + +
+ + + + +
+ << immultiply + + + FOSSEE Image Processing Toolbox + + + imsubtract >> + +
+
+
+ + + + FOSSEE Image Processing Toolbox >> FOSSEE Image Processing Toolbox > imrotate + +

+

imrotate

+

Rotates an image by the specified angle

+ + +

Calling Sequence

+ 
outputImage = imrotate(srcImg, angle)
+outputImage = imrotate(srcImg, angle, BoundingBoxType)
+ +

Parameters

+
srcImg : +

The input image which is to be rotated

+
angle : +

The angle by which the image is to be rotated

+
BoundingBoxType : +

The type of the bounding box for the image displayed, whether a cropped one or one displaying full image.

+ +

Description

+

The function rotates the input image in the anticlockwise direction by the angle specified around the centre point of the image. The bounding box determines whether the complete image or a cropped image will be displayed based on the BoundingBoxType i.e. 'loose' will display the complete image and 'crop' will display the cropped image.

+

+ +

Examples

+ 
k = imread("lena.jpeg');
+p = imrotate(k, 45);
+imshow(p)
+ +

Examples

+ 
k = imread("lena.jpeg');
+p = imrotate(k, 30, 'loose');
+imshow(p)
+ +

Examples

+ 
k = imread("photo.jpg");
+p = imrotate(k, 60, 'crop');
+imshow(p)
+ +

Authors

+
  • Shubham Lohakare, NITK Surathkal
    • +
  • Priyanka Hiranandani, NIT Surat
+
+ +
+ + + + + + +
Report an issue
+ << immultiply + + + FOSSEE Image Processing Toolbox + + + imsubtract >> + +
+
+
+ + diff --git a/help/en_US/scilab_en_US_help/imsubtract.html b/help/en_US/scilab_en_US_help/imsubtract.html new file mode 100644 index 0000000..ec90ce3 --- /dev/null +++ b/help/en_US/scilab_en_US_help/imsubtract.html @@ -0,0 +1,94 @@ + + + imsubtract + + + +
+ + + + +
+ << imrotate + + + FOSSEE Image Processing Toolbox + + + integralImage >> + +
+
+
+ + + + FOSSEE Image Processing Toolbox >> FOSSEE Image Processing Toolbox > imsubtract + +

+

imsubtract

+

Subtract the contents of 2 matrices or images and store it inn another

+ + +

Calling Sequence

+ 
outputMat = imsubtract(input1, input2)
+ +

Parameters

+
input1 : +

First input matrix or an image

+
input2 : +

Second input matrix or image

+ +

Description

+

p=imsubtract(a,b) subtracts each of the element in the first argument's array with the corrresponding element in the second argument's array and the answer is stored in p.

+

+ +

Examples

+ 
a = imread("lena.jpeg");
+k = imsubtract(a,50);
+imshow(k)
+ +

Examples

+ 
a = imread("lena.jpeg");
+b = imread("lena1.jpeg"):
+k = imsubtract(a,b);
+imshow(k)
+ +

Examples

+ 
a = [19 20 21;23 54 11];
+b = [9 10 11;3 34 -9];
+c = imsubtract(a,b);
+disp(c)
+ +

Authors

+
  • Tess Zacharias
    • +
  • Shubham Lohakare
+
+ +
+ + + + + + +
Report an issue
+ << imrotate + + + FOSSEE Image Processing Toolbox + + + integralImage >> + +
+
+
+ + diff --git a/help/en_US/scilab_en_US_help/index.html b/help/en_US/scilab_en_US_help/index.html new file mode 100755 index 0000000..651ec0d --- /dev/null +++ b/help/en_US/scilab_en_US_help/index.html @@ -0,0 +1,52 @@ + + + + + + +
+ + + + +
+ + + + + +
+
+
+ + + + +

+

FOSSEE Image Processing Toolbox

+
+
+ +
+ + + + + + +
Report an issue
+ + + + + +
+
+
+ + diff --git a/help/en_US/scilab_en_US_help/indexImages.html b/help/en_US/scilab_en_US_help/indexImages.html new file mode 100755 index 0000000..ad4089d --- /dev/null +++ b/help/en_US/scilab_en_US_help/indexImages.html @@ -0,0 +1,93 @@ + + + indexImages + + + +
+ + + + +
+ << imsharpen + + + FOSSEE_Image_Processing_Toolbox + + + integralKernel >> + +
+
+
+ + + + FOSSEE_Image_Processing_Toolbox >> FOSSEE_Image_Processing_Toolbox > indexImages + +

+

indexImages

+

This function creates image search index

+ + +

Calling Sequence

+ 
imageIndex = indexImages(imgSet, bagOfFeatures, Name, Value... );
+ +

Parameters

+
imgSet: +

Collection of images with their location and labels

+
bagOfFeatures: +

Bag of Visual Words

+
Verbose [Optional Input Argument]: +

Enable Progress display to Screen

+
SaveFeatureLocations [Optional Input Argument]: +

A boolean value indicating whether feature locations has to be saved or not. Values: [True(default)|False]

+
imageIndex: +

Search Index Object containing the mapping of visual vocabulary to each image in the image set

+ +

Description

+

Creates a search Index Object that has been mapped to visual words that can be used for retrieve Images

+

+ +

Examples

+ 
imgSet = imageSet(directory,'recursive');
+[trainingSet testSet] = partition(imgSet,[0.8]);
+bag = bagOfFeatures(trainingSet);
+imageindex = indexImages(trainingSet, bag);
+
+With Optional Arguments:
+imageindex = indexImages(trainingSet, bag, "Verbose", 1);
+ +

Authors

+
  • Umang Agrawal
    • +
  • Rohit Suri
    • +
  • Sridhar Reddy
+
+ +
+ + + + + + +
Report an issue
+ << imsharpen + + + FOSSEE_Image_Processing_Toolbox + + + integralKernel >> + +
+
+
+ + diff --git a/help/en_US/scilab_en_US_help/integralImage.html b/help/en_US/scilab_en_US_help/integralImage.html new file mode 100644 index 0000000..0915797 --- /dev/null +++ b/help/en_US/scilab_en_US_help/integralImage.html @@ -0,0 +1,92 @@ + + + integralImage + + + +
+ + + + +
+ << imsubtract + + + FOSSEE Image Processing Toolbox + + + multiDenoise >> + +
+
+
+ + + + FOSSEE Image Processing Toolbox >> FOSSEE Image Processing Toolbox > integralImage + +

+

integralImage

+

The function calculates the integral of the source image passed.

+ + +

Calling Sequence

+ 
[outputImage,squaredImage,rotatedImage] = integralImage(srcImg)
+[outputImage,squaredImage,rotatedImage] = integralImage(srcImg,method)
+ +

Parameters

+
srcImg : +

The input image

+
method : +

The type of output frame in which the image is to be returned. 'upright' gives the original output whereas 'rotated' gives the output rotated by 45 degrees.

+ +

Description

+

The function can be used to calculate integral images for the provided input image. These integrals can be used to calculate the sum or mean or even standard deviation. It makes it feasible to apply fast blurring or fast block co-relation.

+

+ +

Examples

+ 
a = imread("lena.jpeg");
+[p, q, r] = integralImage(a);
+imshow(p);
+imshow(q);
+imshow(r);
+ +

Examples

+ 
a = imread("lena1.jpeg");
+[p, q, r] = integralImage(a);
+imshow(p);
+imshow(q);
+imshow(r);
+ +

Authors

+
  • Samiran Roy
    • +
  • Shubham Lohakare
+
+ +
+ + + + + + +
Report an issue
+ << imsubtract + + + FOSSEE Image Processing Toolbox + + + multiDenoise >> + +
+
+
+ + diff --git a/help/en_US/scilab_en_US_help/integralKernel.html b/help/en_US/scilab_en_US_help/integralKernel.html new file mode 100755 index 0000000..4a57ef6 --- /dev/null +++ b/help/en_US/scilab_en_US_help/integralKernel.html @@ -0,0 +1,83 @@ + + + integralKernel + + + +
+ + + + +
+ << indexImages + + + FOSSEE_Image_Processing_Toolbox + + + isEpipoleInImage >> + +
+
+
+ + + + FOSSEE_Image_Processing_Toolbox >> FOSSEE_Image_Processing_Toolbox > integralKernel + +

+

integralKernel

+

This function creates a filter to be used with integral images.

+ + +

Calling Sequence

+ 
results = intergralKernel(bbox, weight);
+ +

Parameters

+
results: +

A structure kernel which contains bounding boxes, weights, filter coefficients, center of filter, size of filter, orientation of filter

+
bboxes: +

bounding boxes that define the filter

+
weights: +

weights corresponding to each of the bbox

+ +

Description

+

Integral kernel creates box filter which can be used with integral images.

+

+ +

Examples

+ 
bbox = [1 2 3 4; 5 6 7 8];
+weights = [10 11];
+results = integralKernel(bbox, weights);
+ +

Authors

+
  • Tanmay Chaudhari
+
+ +
+ + + + + + +
Report an issue
+ << indexImages + + + FOSSEE_Image_Processing_Toolbox + + + isEpipoleInImage >> + +
+
+
+ + diff --git a/help/en_US/scilab_en_US_help/jhelpidx.xml b/help/en_US/scilab_en_US_help/jhelpidx.xml new file mode 100755 index 0000000..aa5a66e --- /dev/null +++ b/help/en_US/scilab_en_US_help/jhelpidx.xml @@ -0,0 +1,3 @@ + + + \ No newline at end of file diff --git a/help/en_US/scilab_en_US_help/jhelpmap.jhm b/help/en_US/scilab_en_US_help/jhelpmap.jhm new file mode 100755 index 0000000..cdbcb20 --- /dev/null +++ b/help/en_US/scilab_en_US_help/jhelpmap.jhm @@ -0,0 +1,5 @@ + + + + + \ No newline at end of file diff --git a/help/en_US/scilab_en_US_help/jhelpset.hs b/help/en_US/scilab_en_US_help/jhelpset.hs new file mode 100755 index 0000000..7c93217 --- /dev/null +++ b/help/en_US/scilab_en_US_help/jhelpset.hs @@ -0,0 +1,28 @@ + + + +FOSSEE Image Processing Toolbox + +top + + + +TOC + +javax.help.TOCView +jhelptoc.xml + + +Index + +javax.help.IndexView +jhelpidx.xml + + +Search + +javax.help.SearchView +JavaHelpSearch + + \ No newline at end of file diff --git a/help/en_US/scilab_en_US_help/jhelptoc.xml b/help/en_US/scilab_en_US_help/jhelptoc.xml new file mode 100755 index 0000000..5ef8b88 --- /dev/null +++ b/help/en_US/scilab_en_US_help/jhelptoc.xml @@ -0,0 +1,6 @@ + + + + + + \ No newline at end of file diff --git a/help/en_US/scilab_en_US_help/matMulDeriv.html b/help/en_US/scilab_en_US_help/matMulDeriv.html new file mode 100755 index 0000000..e9beb04 --- /dev/null +++ b/help/en_US/scilab_en_US_help/matMulDeriv.html @@ -0,0 +1,79 @@ + + + matMulDeriv + + + +
+ + + + +
+ << line + + + FOSSEE_Image_Processing_Toolbox + + + mean1 >> + +
+
+
+ + + + FOSSEE_Image_Processing_Toolbox >> FOSSEE_Image_Processing_Toolbox > matMulDeriv + +

+

matMulDeriv

+

this function Computes partial derivatives of the matrix product for each multiplied matrix

+ + +

Calling Sequence

+ 
[da db]=matMulDeriv(A,B);
+ +

Parameters

+
+ +

Description

+

this function Computes partial derivatives of the matrix product for each multiplied matrix

+ +

Examples

+ 
Declare mattrices
+a=[1 2 ;3 4];
+b=[1 2 ;3 4];
+//call function
+[da db]=matMulDeriv(a,b);
+//view output
+da
+db
+
+ +
+ + + + + + +
Report an issue
+ << line + + + FOSSEE_Image_Processing_Toolbox + + + mean1 >> + +
+
+
+ + diff --git a/help/en_US/scilab_en_US_help/multiDenoise.html b/help/en_US/scilab_en_US_help/multiDenoise.html new file mode 100644 index 0000000..b421e9a --- /dev/null +++ b/help/en_US/scilab_en_US_help/multiDenoise.html @@ -0,0 +1,133 @@ + + + multiDenoise + + + +
+ + + + +
+ << integralImage + + + FOSSEE Image Processing Toolbox + + + multiDenoiseColor >> + +
+
+
+ + + + FOSSEE Image Processing Toolbox >> FOSSEE Image Processing Toolbox > multiDenoise + +

+

multiDenoise

+

Removes gaussian white noise from an image taking reference images of the same captured in small intervals

+ + +

Calling Sequence

+ 
out = multiDenoise(imgToDenoiseIndex, temporalWindowSize, filterStrength, templateWindowSize, searchWindowSize, n, choice, srcImg1, srcImg2, srcImg3)
+out = multiDenoise(imgToDenoiseIndex, temporalWindowSize, filterStrength, templateWindowSize, searchWindowSize, n, choice, srcImg1, srcImg2, srcImg3, srcImg4)
+out = multiDenoise(imgToDenoiseIndex, temporalWindowSize, filterStrength, templateWindowSize, searchWindowSize, n, choice, srcImg1, srcImg2, srcImg3, srcImg4, srcImg5)
+ +

Parameters

+
imgToDenoiseIndex : +

Target image to denoise index in srcImgs sequence

+
temporalWindowSize : +

Number of surrounding images to use for target image denoising. Should be odd.

+
filterStrength : +

Parameter regulating filter strength. Bigger h value perfectly removes noise but also removes image details, smaller h value preserves details but also preserves some noise.

+
templateWindowSize : +

Size in pixels of the template patch that is used to compute weights. Should be odd.

+
searchWindowSize : +

Size in pixels of the window that is used to compute weighted average for given pixel. Should be odd.

+
n : +

number of images passed.

+
choice : +

chooses which type of method to use

+
srcImgs : +

The input images which are passed. They are variable arguments.

+ +

Description

+

Modification of fastNlMeansDenoising function for images sequence where consequtive images have been captured in small period of time. It removes gaussian white noise.The output is a denoised image

+

+ +

Examples

+ 
a= imread("img1.jpg");
+b= imread("img2.jpg");
+c= imread("img3.jpg");
+imgToDenoiseIndex=1;
+temporalWindowSize =1;
+templateWindowSize =7;
+searchWindowSize =21;
+filterStrength = 10;
+n = 3;
+choice = 1;
+k=multiDenoise(imgToDenoiseIndex,temporalWindowSize,filterStrength,templateWindowSize,searchWindowSize,n,choice,a,b,c);
+ +

Examples

+ 
a= imread("img1.jpg");
+b= imread("img2.jpg");
+c= imread("img3.jpg");
+d= imread("img4.jpg");
+imgToDenoiseIndex=1;
+temporalWindowSize =1;
+templateWindowSize =7;
+searchWindowSize =21;
+filterStrength = 100;
+n = 4;
+choice = 1;
+k=multiDenoise(imgToDenoiseIndex,temporalWindowSize,filterStrength,templateWindowSize,searchWindowSize,n,choice,a,b,c,d);
+ +

Examples

+ 
a= imread("pic.jpeg");
+b= imread("pic1.jpeg");
+c= imread("pic2.jpeg");
+d= imread("pic3.jpeg");
+e= imread("pic4.jpeg");
+imgToDenoiseIndex=3;
+temporalWindowSize =3;
+templateWindowSize =7;
+searchWindowSize =21;
+filterStrength = 75;
+n = 5;
+choice = 2;
+k=multiDenoise(imgToDenoiseIndex,temporalWindowSize,filterStrength,templateWindowSize,searchWindowSize,n,choice,a,b,c,d,e);
+ +

Authors

+
  • Shubham Lohakare, NITK Surathkal
    • +
  • Ashish Mantosh, NIT Rourkela
+
+ +
+ + + + + + +
Report an issue
+ << integralImage + + + FOSSEE Image Processing Toolbox + + + multiDenoiseColor >> + +
+
+
+ + diff --git a/help/en_US/scilab_en_US_help/multiDenoiseColor.html b/help/en_US/scilab_en_US_help/multiDenoiseColor.html new file mode 100644 index 0000000..5ad8371 --- /dev/null +++ b/help/en_US/scilab_en_US_help/multiDenoiseColor.html @@ -0,0 +1,133 @@ + + + multiDenoiseColor + + + +
+ + + + +
+ << multiDenoise + + + FOSSEE Image Processing Toolbox + + + +
+
+
+ + + + FOSSEE Image Processing Toolbox >> FOSSEE Image Processing Toolbox > multiDenoiseColor + +

+

multiDenoiseColor

+

Removes gaussian white noise from an image taking reference images of the same captured in small intervals

+ + +

Calling Sequence

+ 
out = multiDenoiseColor(imgToDenoiseIndex, temporalWindowSize, filterStrength, filterStrengthColor,templateWindowSize, searchWindowSize, n, srcImg1, srcImg2, srcImg3)
+out = multiDenoiseColor(imgToDenoiseIndex, temporalWindowSize, filterStrength,filterStrengthColor, templateWindowSize, searchWindowSize, n, srcImg1, srcImg2, srcImg3,srcImg4)
+out = multiDenoiseColor(imgToDenoiseIndex, temporalWindowSize, filterStrength,filterStrengthColor, templateWindowSize, searchWindowSize, n,srcImg1, srcImg2, srcImg3,srcImg4,srcImg5)
+ +

Parameters

+
imgToDenoiseIndex : +

Target image to denoise index in srcImgs sequence

+
temporalWindowSize : +

Number of surrounding images to use for target image denoising. Should be odd.

+
filterStrength : +

Parameter regulating filter strength. Bigger h value perfectly removes noise but also removes image details, smaller h value preserves details but also preserves some noise.

+
filterStrengthColor : +

same as filterStrength but for color components of noise.

+
templateWindowSize : +

Size in pixels of the template patch that is used to compute weights. Should be odd.

+
searchWindowSize : +

Size in pixels of the window that is used to compute weighted average for given pixel. Should be odd.

+
n : +

number of images passed.

+
srcImgs : +

The input images which are passed. They are variable arguments.

+ +

Description

+

Modification of fastNlMeansDenoising function for images sequence where consequtive images have been captured in small period of time. It removes gaussian white noise.The output is a denoised image

+

+ +

Examples

+ 
a= imread("img1.jpg");
+b= imread("img2.jpg");
+c= imread("img3.jpg");
+imgToDenoiseIndex=1;
+temporalWindowSize =1;
+templateWindowSize =7;
+searchWindowSize =21;
+filterStrength = 10;
+filterStrengthColor = 10;
+n = 3;
+k=multiDenoiseColor(imgToDenoiseIndex,temporalWindowSize,filterStrength,filterStrengthColor,templateWindowSize,searchWindowSize,n,a,b,c);
+ +

Examples

+ 
a= imread("img1.jpg");
+b= imread("img2.jpg");
+c= imread("img3.jpg");
+d= imread("img4.jpg");
+imgToDenoiseIndex=1;
+temporalWindowSize =1;
+templateWindowSize =7;
+searchWindowSize =21;
+filterStrength = 100;
+filterStrengthColor=30;
+n = 4;
+choice = 1;
+k=multiDenoiseColor(imgToDenoiseIndex,temporalWindowSize,filterStrength,filterStrengthColor,templateWindowSize,searchWindowSize,n,a,b,c,d);
+ +

Examples

+ 
a= imread("pic.jpeg");
+b= imread("pic1.jpeg");
+c= imread("pic2.jpeg");
+d= imread("pic3.jpeg");
+e= imread("pic4.jpeg");
+imgToDenoiseIndex=3;
+temporalWindowSize =3;
+templateWindowSize =7;
+searchWindowSize =21;
+filterStrength = 75;
+filterStrengthColor = 50;
+n = 5;
+choice = 2;
+k=multiDenoiseColor(imgToDenoiseIndex,temporalWindowSize,filterStrength,filterStrengthColor,templateWindowSize,searchWindowSize,n,a,b,c,d,e);
+ +

Authors

+
  • Shubham Lohakare, NITK Surathkal
    • +
  • Ashish Mantosh, NIT Rourkela
+
+ +
+ + + + + + +
Report an issue
+ << multiDenoise + + + FOSSEE Image Processing Toolbox + + + +
+
+
+ + diff --git a/help/en_US/scilab_en_US_help/rgb2xyz.html b/help/en_US/scilab_en_US_help/rgb2xyz.html new file mode 100755 index 0000000..c5524c2 --- /dev/null +++ b/help/en_US/scilab_en_US_help/rgb2xyz.html @@ -0,0 +1,80 @@ + + + rgb2xyz + + + +
+ + + + +
+ << rgb2ntsc + + + FOSSEE_Image_Processing_Toolbox + + + sobel >> + +
+
+
+ + + + FOSSEE_Image_Processing_Toolbox >> FOSSEE_Image_Processing_Toolbox > rgb2xyz + +

+

rgb2xyz

+

This function is used to convert rgb values of an image to their CIE 1931 xyz.

+ + +

Calling Sequence

+ 
image=imread("lena.jpeg");
+xyz=imread(image);
+ +

Parameters

+
xyz: +

the converted image

+
image: +

Input Image.

+ +

Description

+

+

This function is used to convert rgb values of an image to their CIE 1931 xyz.

+

+ +

Examples

+ 
z=imread("lena.jpeg");
+xyz=rgb2xyz(z);
+imshow(xyz);
+
+ +
+ + + + + + +
Report an issue
+ << rgb2ntsc + + + FOSSEE_Image_Processing_Toolbox + + + sobel >> + +
+
+
+ + diff --git a/help/en_US/scilab_en_US_help/scilab_code.css b/help/en_US/scilab_en_US_help/scilab_code.css new file mode 100755 index 0000000..658f42e --- /dev/null +++ b/help/en_US/scilab_en_US_help/scilab_code.css @@ -0,0 +1,96 @@ +.scilabcomment { + font-style: italic; + color: #01a801 +} + +.scilabdefault { + font-style: normal; + color: #000000 +} + +.scilabspecial { + font-style: normal; + color: #ffaa00 +} + +.scilabconstants { + font-style: normal; + color: #da70d6 +} + +.scilaboperator { + font-style: normal; + color: #5c5c5c +} + +.scilabnumber { + font-style: normal; + color: #bc8f8f +} + +.scilabfkeyword { + font-style: normal; + color: #b01813 +} + +.scilabskeyword { + font-style: normal; + color: #a020f0 +} + +.scilabckeyword { + font-style: normal; + color: #5f9ea0 +} + +.scilabcommand { + font-style: normal; + color: #32b9b9 +} + +.scilabmacro { + font-style: normal; + color: #ae5cb0 +} + +a.scilabcommand { + font-style: normal; + text-decoration: underline; + color: #32b9b9 +} + +a.scilabmacro { + font-style: normal; + text-decoration: underline; + color: #ae5cb0 +} + +.scilabstring { + font-style: normal; + color: #bc8f8f +} + +.scilabid { + font-style: normal; + color: #000000 +} + +.scilabinputoutputargs { + font-weight: bold; + color: #834310 +} + +.scilabfunctionid { + font-weight: bold; + color: #000000 +} + +.scilabfield { + font-style: normal; + color: #aaaaaa +} + +.scilabopenclose { + font-style: normal; + color: #4a55db +} diff --git a/help/en_US/scilab_en_US_help/stereoCalibrate.html b/help/en_US/scilab_en_US_help/stereoCalibrate.html new file mode 100755 index 0000000..2df02e9 --- /dev/null +++ b/help/en_US/scilab_en_US_help/stereoCalibrate.html @@ -0,0 +1,132 @@ + + + stereoCalibrate + + + +
+ + + + +
+ << sobel + + + FOSSEE_Image_Processing_Toolbox + + + threshold >> + +
+
+
+ + + + FOSSEE_Image_Processing_Toolbox >> FOSSEE_Image_Processing_Toolbox > stereoCalibrate + +

+

stereoCalibrate

+

this function Performs stereo calibration for the fisheye model.

+ + +

Calling Sequence

+ 
stereo=stereoCalibrate(objectpoints,imagepoints1,imagepoints2);
+stereo=stereoCalibrate(objectpoints,imagepoints1,imagepoints2,cameraMatrix1,distCoeffs1,cameraMatrix2,distCoeffs2);
+ +

Parameters

+
stereo: +

a Struct containing all the camera Params

+
objectpoints: +

a 2d set of actual object points.

+
imagepoints1: +

a list of imagepoints of image1.

+
imagepoints2: +

a list of imagepoints of image2.

+
cameraMatrix1: +

camera matrix of first camera.

+
distCoeffs1: +

distortion coefficients of first camera.it should be 4*1 or 1*4.

+
cameraMatrix2: +

camera matrix of second camera.

+
distCoeffs2: +

distortion coefficients of second camera.it should be 4*1 or 1*4.

+ +

Description

+

+

this function Performs stereo calibration for the fisheye model.

+

+ +

Examples

+ 
// A example to show calibration, using the traditional chessboard/checkerboard example.
+
+//generate checkerboardpoints for calibration
+yo=genCheckerboardPoints([7 10],8);
+//read first image
+z=imread("left1.jpg",0);
+//read second image
+image=imread("right1.jpg",0);
+//detect checkerboardpoints for image 1
+ii=detectCheckerboardCorner(z,[7 10]);
+//detect checkerboardpoints for image 2
+ii2=detectCheckerboardCorner(image,[7 10]);
+//convert imagepoints to list
+ii=list(ii);
+ii2=list(ii2);
+// call function
+final=stereoCalibrate(yo,ii,ii2);
+// show the struct
+final
+// use the above calibration further
+uu = undistortImage(image,final.cameraMatrix2);
+imshow(uu);
+
+//generate checkerboardpoints for calibration
+yo=genCheckerboardPoints([7 10],8);
+//read first image
+z=imread("left1.jpg",0);
+//read second image
+image=imread("right1.jpg",0);
+//detect checkerboardpoints for image 1
+ii=detectCheckerboardCorner(z,[7 10]);
+//detect checkerboardpoints for image 2
+ii2=detectCheckerboardCorner(image,[7 10]);
+//convert imagepoints to list
+ii=list(ii);
+ii2=list(ii2);
+// call function
+final=stereoCalibrate(yo,ii,ii2);
+// show the struct
+final
+// use the above calibration further
+uu = undistortImage(image,final.cameraMatrix2,'distCoeffs',final.distortionCoefficients2);
+imshow(uu);
+
+ +
+ + + + + + +
Report an issue
+ << sobel + + + FOSSEE_Image_Processing_Toolbox + + + threshold >> + +
+
+
+ + diff --git a/help/en_US/scilab_en_US_help/style.css b/help/en_US/scilab_en_US_help/style.css new file mode 100755 index 0000000..0fe8923 --- /dev/null +++ b/help/en_US/scilab_en_US_help/style.css @@ -0,0 +1,350 @@ +body { + color:#000000; + background-color:#ffffff; + font-family:sans-serif; + font-size:100%; + margin:5px; + padding:0; + background : url("/img/body.png"); + background-repeat : repeat-x; +} + +.para { + padding-left: 10px; +} + +.refname { + color: #ff6c0a; +} +.refpurpose { + font-size: 110%; +} + +.synopsis { + border: 1px solid black; + width:80%; + padding: 0.5em; +} + +.editbar { + text-align: right; +} + +.term { + color:#800000; + font-size:100%; +} + +h3 { + color: #000063; + font-weight: bold; + font-size:130%; + margin-bottom: 10px; +} + +.programlisting { + font-family: monospace; + font-size: 100%; + background-color:#EEEEFF; + border-color:#CCCCCC; + border-style:solid; + border-width:2px medium; + width:80%; + color:#333333; + line-height:120%; + padding:10px; +} + +.literal { + font-family: monospace; + font-size: 100%; +} + +.option { + font-family: monospace; + font-style: italic; + font-size: 100%; +} + +.command { + font-family: monospace; + font-size: 100%; + color: #32b9b9; +} + +.function { + font-family: monospace; + font-size: 100%; + color: #32b9b9; +} + +.varname { + font-family: monospace; + font-weight: bold; + font-size: 100%; +} + +.constant { + font-family: monospace; + font-size: 100%; + color: #da70d6; +} + +a { + color: blue; + text-decoration:none; +} + +a:hover { + text-decoration:underline; +} + +.itemizedlist { + list-style-type: disk; +} + +.inline-list li { + display: inline; + list-style-type: disk; +} + +.vert-list { + list-style-type: disk; +} + +pre { + margin-bottom: 0px; + margin-top: 0px; +} + +.leftpart { + position:absolute; + float:left; + width: 186px; + padding: 5px; + font-size: smaller; +} + +.content { + margin-top: 100px; + margin-left: 196px +} + +.container { + margin: 0 auto; + width:1024px; +} + +ul.toc li.list-active { + list-style-type:disc; + font-weight:bold; +} + +ul.toc li.parent { + font-size: 115%; + padding: 5px 0px 5px 11px; + border-bottom: 1px solid #cccccc; + margin-bottom: 5px; +} + +ul.toc li.root { + font-size: 135%; + padding: 5px 0px 5px 11px; + border-bottom: 1px solid #cccccc; + margin-bottom: 5px; +} + +ul.toc li { + font-size: 85%; + margin: 1px 0 1px 1px; + padding: 1px 0 1px 11px; + background-repeat: no-repeat; + background-position: center left; + list-style-type: circle; +} + +.next { + float:right; + text-align: right; +} + +.center { + text-align: center; +} + +.screen { + font-family: monospace; + font-size: 100%; + background-color:#FFFFFF; + border-color:#CCCCCC; + border-style:solid; + border-width:2px medium; + width:80%; + color:#333333; + line-height:120%; + padding:10px; +} + +/* Top and bottom navigation controls on manual pages --------------------- */ +div.manualnavbar { + background-color: #E0E0E0; + color: inherit; + padding: 4px; + margin-bottom: 10px; +} +div.manualnavbar .prev { + padding-right: 4px; +} +div.manualnavbar .next { + text-align: right; + padding-left: 4px; +} + +div.manualnavbar .top { + text-align: center; + display: block; +} + +div.manualnavbar hr { + color: #cccccc; + background-color: #cccccc; +} + +/* Footer navigation area ------------------------------------------------- */ + +#pagefooter { + position: relative; + font-size: 75%; + color: inherit; + background-color: #e5e5e5; + width: 100%; +} + +#pagefooterleft { + top: 0px; + left: 0px; + padding: 6px; + margin-right: 30%; +} + +#pagefooterright { + text-align: right; + margin-left: 50%; + padding: 6px; +} +#footnav { + color: inherit; + background-color: #9999cc; + border-width: 1px 0px; + border-color: #333366; + border-style: solid; + text-align: right; + padding-right: 6px; +} + + + + + #global{ +/* width: 90%; */ + max-width: 90em; +/* min-width: 850px; */ + margin-left: auto; + margin-right: auto; + } + + #myHeader{ + background-color:#000000; + color:white; + margin-bottom : 10px; + position : relative; + text-align: center; +/* width : 1024px;*/ + height : 100px; + padding-left : 20px; + background : url("http://atoms.scilab.org/images/homepage/cadre_head.png"); + background-repeat : no-repeat; + background-position : 0px 0px; + + } + + #myFooter{ + background-color:#E5E5E5; + font-color:black; +/* width: 90%;*/ + max-width: 90em; +/* min-width: 850px; + margin-left: 5%; + margin-right: 5%;*/ + margin-top:10px; + padding:10px; + } + + #mainArea{ + width: 100%; + overflow: hidden; + } + + #myLeftArea{ + color:white; + float: left; + width: 180px; + padding:5px; + } + + #myMiddleArea{ + color:black; + margin-left: 200px; + padding: 10px 20px; + } + + #myRightArea{ + color:white; + float: right; + width: 200px; + padding: 12px 20px; + } + + +div#cadre_head +{ + position : relative; + text-align: center; +/* width : 1024px;*/ + height : 100px; + padding-left : 20px; + background : url("/img/cadre_head.png"); + background-repeat : no-repeat; + background-position : 0px 0px; +} + + +div#slogan{ + position: absolute; + top : 50px; + left:251px; + color:#0000AA; + font: 120%, Georgia,Serif; +} +div#cadre_help +{ + position: absolute; + top:45px; + right:0px; + font-size:0.8em; + color:#0000AA; +} + +table.revhistory +{ + width:80%; + border-color:#CCCCCC; + border-style:solid; + border-width:2px medium; + margin-bottom: 10px; +} + +table.revhistory tr.title td +{ + background-color: #9999CC; +} \ No newline at end of file diff --git a/help/en_US/scilab_en_US_help/trainSVMClassifier.html b/help/en_US/scilab_en_US_help/trainSVMClassifier.html new file mode 100755 index 0000000..c84a288 --- /dev/null +++ b/help/en_US/scilab_en_US_help/trainSVMClassifier.html @@ -0,0 +1,136 @@ + + + trainSVMClassifier + + + +
+ + + + +
+ << trainBoostClassifier + + + FOSSEE_Image_Processing_Toolbox + + + trainSVMSGDClassifier >> + +
+
+
+ + + + FOSSEE_Image_Processing_Toolbox >> FOSSEE_Image_Processing_Toolbox > trainSVMClassifier + +

+

trainSVMClassifier

+

This function is used to train an image classifier using the SVM(Support Vector Machines) Model.

+ + +

Calling Sequence

+ 
imgSet = imageSet(directory,'recursive');
+'or'
+imgSet = imageSet(image);
+bag = bagOfFeatures(imgSet);
+classifier = trainSVMClassifier(imgSets, bag);
+classifier = trainSVMClassifier(imgSets, bag,'nameclass')
+classifier = trainSVMClassifier(imgSets, bag,'nameclass')
+classifier = trainSVMClassifier(imgSets, bag,'nameclass',C)
+classifier = trainSVMClassifier(imgSets, bag,'nameclass',C,coeff)
+classifier = trainSVMClassifier(imgSets, bag,'nameclass',C,coeff,degree)
+classifier = trainSVMClassifier(imgSets, bag,'nameclass',C,coeff,degree,gamma)
+classifier = trainSVMClassifier(imgSets, bag,'nameclass',C,coeff,degree,gamma,kernelType,Nu)
+classifier = trainSVMClassifier(imgSets, bag,'nameclass',C,coeff,degree,gamma,kernelType,Nu,P)
+classifier = trainSVMClassifier(imgSets, bag,'nameclass',C,coeff,degree,gamma,kernelType,Nu,P,setType)
+ +

Parameters

+
classifier: +

Image category classifier location

+
BagofFeaturesLocation : +

location of the xml or yml file.

+
Description : +

features obtained after training.

+
imgSets: +

Input imageSet to train the classifier on

+
bag: +

The bagOfFeatures of the imageSet provided

+
image: +

The set of images used for creating the imageset used for training

+
nameclass: +

Name of the classifier one wants for their trained model .xml or .yml file

+
C: +

Parameter C of a SVM optimization problem that should be used to train the model

+
coef: +

Parameter coef0 of a kernel function that should be used to train the model

+
degree: +

Parameter degree of a kernel function that should be used to train the model

+
gamma: +

Parameter γ of a kernel function that should be used to train the model.

+
kernelType: +

Type of a SVM kernel that should be used to train the model.it should be [-1,5].

+
Nu: +

Parameter ν of a SVM optimization problem that should be used to train the model.

+
P: +

Parameter ϵ of a SVM optimization problem that should be used to train the model.

+
type: +

Type of a SVM formulation that should be used to train the model.it should be [100,104].

+ +

Description

+

this function is used to train an image classifier using the SVM(Support Vector Machines) Model.

+

+

+ +

Examples

+ 
//get imageset from 'images2' folder
+image=imageSet('images2','recursive');
+//get bag of features
+x=bagOfFeatures(image);
+//train thew model and name the saved .yml file as "SVM"
+d=trainSVMClassifier(image,x,"SVM");
+//read image to get prediction from mthe above trained data
+z=imread("fish.jpg");
+//finally predict the class using SVM's prediction function for the input image
+resp=predict(d,z,"SVM");
+
+//get imageset from 'images2' folder
+image=imageSet('images2','recursive');
+//get bag of features
+x=bagOfFeatures(image);
+//train the model with the given parameters  and name  the saved .yml file as "SVM"
+d=trainSVMClassifier(image,x,"SVM",1.1,0.2);
+//read image to get prediction from mthe above trained data
+z=imread("fish.jpg");
+//finally predict the class for the input image
+resp=predict(d,z,"SVM");
+
+ +
+ + + + + + +
Report an issue
+ << trainBoostClassifier + + + FOSSEE_Image_Processing_Toolbox + + + trainSVMSGDClassifier >> + +
+
+
+ + diff --git a/help/en_US/scilab_en_US_help/trainSVMSGDClassifier.html b/help/en_US/scilab_en_US_help/trainSVMSGDClassifier.html new file mode 100755 index 0000000..0315f73 --- /dev/null +++ b/help/en_US/scilab_en_US_help/trainSVMSGDClassifier.html @@ -0,0 +1,130 @@ + + + trainSVMSGDClassifier + + + +
+ + + + +
+ << trainSVMClassifier + + + FOSSEE_Image_Processing_Toolbox + + + traindtreeClassifier >> + +
+
+
+ + + + FOSSEE_Image_Processing_Toolbox >> FOSSEE_Image_Processing_Toolbox > trainSVMSGDClassifier + +

+

trainSVMSGDClassifier

+

This function is used to train an image classifier using the SVMSGD(Stochastic Gradient Descent SVM) Model.

+ + +

Calling Sequence

+ 
imgSet = imageSet(directory,'recursive');
+'or'
+imgSet = imageSet(image);
+bag = bagOfFeatures(imgSet);
+classifier = trainSVMSGDClassifier(imgSets, bag);`
+classifier = trainSVMSGDClassifier(imgSets, bag,'nameclass')
+classifier = trainSVMSGDClassifier(imgSets, bag,'nameclass')
+classifier = trainSVMSGDClassifier(imgSets, bag,'nameclass',initialStepSize)
+classifier = trainSVMSGDClassifier(imgSets, bag,'nameclass',initialStepSize,marginReg)
+classifier = trainSVMSGDClassifier(imgSets, bag,'nameclass',initialStepSize,marginReg,marginType)
+classifier = trainSVMSGDClassifier(imgSets, bag,'nameclass',initialStepSize,marginReg,marginType,optimalParams)
+classifier = trainSVMSGDClassifier(imgSets, bag,'nameclass',initialStepSize,marginReg,marginType,optimalParams,stepDecreasingPower)
+classifier = trainSVMSGDClassifier(imgSets, bag,'nameclass',initialStepSize,marginReg,marginType,optimalParams,stepDecreasingPower,svmsgdType)
+ +

Parameters

+
classifier: +

Image category classifier location

+
BagofFeaturesLocation : +

location of the xml or yml file.

+
Description : +

features obtained after training.

+
imgSets: +

Input imageSet to train the classifier on

+
bag: +

The bagOfFeatures of the imageSet provided

+
image: +

The set of images used for creating the imageset used for training

+
nameclass: +

Name of the classifier one wants for their trained model .xml or .yml file

+
initialStepSize: +

Parameter initialStepSize of a SVMSGD optimization problem that should be used to train the model.

+
marginReg: +

Parameter marginRegularization of a SVMSGD optimization problem that should be used to train the model

+
marginType: +

Parameter marginType of a SVMSGD optimization problem that should be used to train the model.it should be either 0 or 1.

+
optimalParams: +

sets optimal parameters values for chosen SVM SGD model.

+
stepDecreasingPower: +

Parameter stepDecreasingPower of a SVMSGD optimization problem that should be used to train the model.

+
svmsgdType: +

Algorithm type of SVMSGD that should be used to train the model.it should be either 0 or 1.

+ +

Description

+

This function is used to train an image classifier using the SVMSGD(Stochastic Gradient Descent SVM) Model.

+

+ +

Examples

+ 
//get imageset from 'images2' folder
+image=imageSet('images2','recursive');
+//get bag of features
+x=bagOfFeatures(image);
+//train thew model and name the saved .yml file as "pbrr" using the given parameters
+r=trainSVMSGDClassifier(image,x,"pbrr",0,0,0,1,0,1);
+//read image to get prediction from the above trained data
+z=imread("fish.jpg");
+//finally predict the class using SVMSGD's prediction function for the input image
+resp=predict(r,z,"SVMSGD");
+
+//get imageset from 'images2' folder
+image=imageSet('images2','recursive');
+//get bag of features
+x=bagOfFeatures(image);
+//train the model and name the saved .yml file as "pbrr"
+r=trainSVMSGDClassifier(image,x,"pbrr");
+//read image to get prediction from the above trained data
+z=imread("fish.jpg");
+//finally predict the class using SVMSGD's prediction function for the input image
+resp=predict(r,z,"SVMSGD");
+
+ +
+ + + + + + +
Report an issue
+ << trainSVMClassifier + + + FOSSEE_Image_Processing_Toolbox + + + traindtreeClassifier >> + +
+
+
+ + diff --git a/help/en_US/scilab_en_US_help/undistortPoints.html b/help/en_US/scilab_en_US_help/undistortPoints.html new file mode 100755 index 0000000..097ad48 --- /dev/null +++ b/help/en_US/scilab_en_US_help/undistortPoints.html @@ -0,0 +1,87 @@ + + + undistortPoints + + + +
+ + + + +
+ << undistortImage + + + FOSSEE_Image_Processing_Toolbox + + + +
+
+
+ + + + FOSSEE_Image_Processing_Toolbox >> FOSSEE_Image_Processing_Toolbox > undistortPoints + +

+

undistortPoints

+

Returns the ideal point coordinates from the observed point coordinates

+ + +

Calling Sequence

+ 
[idealPoints] = undistortPoints(observedPoints, camMat, disCoefMat, rectMat, newCamMat)
+ +

Parameters

+
observedPoints: +

1xN or Nx1 2-channel (CV_32FC2 or CV_64FC2).

+
camMat: +

\vecthreethree{f_x}{0}{c_x}{0}{f_y}{c_y}{0}{0}{1}

+
disCoefMat: +

Input vector of distortion coefficients (k_1, k_2, p_1, p_2[, k_3[, k_4, k_5, k_6]]) of 4, 5, or 8 elements. If the vector is NULL/empty, the zero distortion coefficients are assumed.

+
rectMat: +

Rectification transformation in the object space (3x3 matrix). If the matrix is empty, the identity transformation is used.

+
newCamMat: +

New camera matrix (3x3) or new projection matrix (3x4. If the matrix is empty, the identity new camera matrix is used.

+
idealPoints: +

ideal point coordinates matrix. If matrix newCamMat is identity or omitted, idealPoints will contain normalized point coordinates.

+ +

Description

+

Returns the ideal points coordinates from the observed point coordinates after undistortion and reverse perpective transformation.

+

+ +

Examples

+ 
[observedPoints] = [1 2 3 4; 4 3 2 1]
+[camMat] = [450 0 231; 0 876.3 87.1; 0 0 1]
+[disCoefMat] = [3 2 0 9]
+[rectMat] = [1 0 0; 0 1 0; 0 0 1]
+[newCamMat] = []
+[idealPoints] = undistortPoints(observedPoints, camMat, disCoefMat, rectMat, newCamMat)
+
+ +
+ + + + + + +
Report an issue
+ << undistortImage + + + FOSSEE_Image_Processing_Toolbox + + + +
+
+
+ + diff --git a/help/en_US/scilab_en_US_help/xml_code.css b/help/en_US/scilab_en_US_help/xml_code.css new file mode 100755 index 0000000..9e4c27f --- /dev/null +++ b/help/en_US/scilab_en_US_help/xml_code.css @@ -0,0 +1,94 @@ +.xmlcomment { + font-style: italic; + color: #01a801 +} + +.xmldefault { + font-style: normal; + color: #000000 +} + +.xmlentity { + font-style: normal; + color: #ffaa00 +} + +.xmlopeninstr { + font-style: normal; + color: #000000 +} + +.xmlcloseinstr { + font-style: normal; + color: #000000 +} + +.xmlinstrname { + font-style: normal; + color: #9965a6 +} + +.xmllowtag { + font-style: normal; + color: #000000 +} + +.xmltagname { + font-style: normal; + color: #0303ff +} + +.xmllowclose { + font-style: normal; + color: #000000 +} + +.xmlopencomment { + font-style: italic; + color: #01a801 +} + +.xmlcommentend { + font-style: italic; + color: #01a801 +} + +.xmlcomment { + font-style: italic; + color: #01a801 +} + +.xmlopencdata { + font-style: normal; + color: #c45555 +} + +.xmlcdataend { + font-style: normal; + color: #c45555 +} + +.xmlcdata { + font-style: normal; + color: #000000 +} + +.xmlattributename { + font-style: normal; + color: #9965a6 +} + +.xmlequal { + font-style: normal; + color: #000000 +} + +.xmlattributevalue { + font-style: normal; + color: #973964 +} + +.xmlautoclose { + font-style: normal; + color: #000000 +} diff --git a/help/en_US/stereoCalibrate.xml b/help/en_US/stereoCalibrate.xml new file mode 100755 index 0000000..dc83117 --- /dev/null +++ b/help/en_US/stereoCalibrate.xml @@ -0,0 +1,116 @@ + + + + + + + + stereoCalibrate + this function Performs stereo calibration for the fisheye model. + + + + + Calling Sequence + + + stereo=stereoCalibrate(objectpoints,imagepoints1,imagepoints2); + stereo=stereoCalibrate(objectpoints,imagepoints1,imagepoints2,cameraMatrix1,distCoeffs1,cameraMatrix2,distCoeffs2); + + + + + + Parameters + + stereo: + a Struct containing all the camera Params + objectpoints: + a 2d set of actual object points. + imagepoints1: + a list of imagepoints of image1. + imagepoints2: + a list of imagepoints of image2. + cameraMatrix1: + camera matrix of first camera. + distCoeffs1: + distortion coefficients of first camera.it should be 4*1 or 1*4. + cameraMatrix2: + camera matrix of second camera. + distCoeffs2: + distortion coefficients of second camera.it should be 4*1 or 1*4. + + + + + Description + + + +this function Performs stereo calibration for the fisheye model. + + + + + + + Examples + + + diff --git a/help/en_US/trainSVMClassifier.xml b/help/en_US/trainSVMClassifier.xml new file mode 100755 index 0000000..fb20ded --- /dev/null +++ b/help/en_US/trainSVMClassifier.xml @@ -0,0 +1,118 @@ + + + + + + + + trainSVMClassifier + This function is used to train an image classifier using the SVM(Support Vector Machines) Model. + + + + + Calling Sequence + + imgSet = imageSet(directory,'recursive'); + 'or' + imgSet = imageSet(image); + bag = bagOfFeatures(imgSet); + classifier = trainSVMClassifier(imgSets, bag); + classifier = trainSVMClassifier(imgSets, bag,'nameclass') + classifier = trainSVMClassifier(imgSets, bag,'nameclass') + classifier = trainSVMClassifier(imgSets, bag,'nameclass',C) + classifier = trainSVMClassifier(imgSets, bag,'nameclass',C,coeff) + classifier = trainSVMClassifier(imgSets, bag,'nameclass',C,coeff,degree) + classifier = trainSVMClassifier(imgSets, bag,'nameclass',C,coeff,degree,gamma) + classifier = trainSVMClassifier(imgSets, bag,'nameclass',C,coeff,degree,gamma,kernelType,Nu) + classifier = trainSVMClassifier(imgSets, bag,'nameclass',C,coeff,degree,gamma,kernelType,Nu,P) + classifier = trainSVMClassifier(imgSets, bag,'nameclass',C,coeff,degree,gamma,kernelType,Nu,P,setType) + + + + + + Parameters + + classifier: + Image category classifier location + BagofFeaturesLocation : + location of the xml or yml file. + Description : + features obtained after training. + imgSets: + Input imageSet to train the classifier on + bag: + The bagOfFeatures of the imageSet provided + image: + The set of images used for creating the imageset used for training + nameclass: + Name of the classifier one wants for their trained model .xml or .yml file + C: + Parameter C of a SVM optimization problem that should be used to train the model + coef: + Parameter coef0 of a kernel function that should be used to train the model + degree: + Parameter degree of a kernel function that should be used to train the model + gamma: + Parameter γ of a kernel function that should be used to train the model. + kernelType: + Type of a SVM kernel that should be used to train the model.it should be [-1,5]. + Nu: + Parameter ν of a SVM optimization problem that should be used to train the model. + P: + Parameter ϵ of a SVM optimization problem that should be used to train the model. + type: + Type of a SVM formulation that should be used to train the model.it should be [100,104]. + + + + + Description + +this function is used to train an image classifier using the SVM(Support Vector Machines) Model. + + + + + + + + + Examples + + + diff --git a/help/en_US/trainSVMSGDClassifier.xml b/help/en_US/trainSVMSGDClassifier.xml new file mode 100755 index 0000000..f30584c --- /dev/null +++ b/help/en_US/trainSVMSGDClassifier.xml @@ -0,0 +1,111 @@ + + + + + + + + trainSVMSGDClassifier + This function is used to train an image classifier using the SVMSGD(Stochastic Gradient Descent SVM) Model. + + + + + Calling Sequence + + imgSet = imageSet(directory,'recursive'); + 'or' + imgSet = imageSet(image); + bag = bagOfFeatures(imgSet); + classifier = trainSVMSGDClassifier(imgSets, bag);` + classifier = trainSVMSGDClassifier(imgSets, bag,'nameclass') + classifier = trainSVMSGDClassifier(imgSets, bag,'nameclass') + classifier = trainSVMSGDClassifier(imgSets, bag,'nameclass',initialStepSize) + classifier = trainSVMSGDClassifier(imgSets, bag,'nameclass',initialStepSize,marginReg) + classifier = trainSVMSGDClassifier(imgSets, bag,'nameclass',initialStepSize,marginReg,marginType) + classifier = trainSVMSGDClassifier(imgSets, bag,'nameclass',initialStepSize,marginReg,marginType,optimalParams) + classifier = trainSVMSGDClassifier(imgSets, bag,'nameclass',initialStepSize,marginReg,marginType,optimalParams,stepDecreasingPower) + classifier = trainSVMSGDClassifier(imgSets, bag,'nameclass',initialStepSize,marginReg,marginType,optimalParams,stepDecreasingPower,svmsgdType) + + + + + + Parameters + + classifier: + Image category classifier location + BagofFeaturesLocation : + location of the xml or yml file. + Description : + features obtained after training. + imgSets: + Input imageSet to train the classifier on + bag: + The bagOfFeatures of the imageSet provided + image: + The set of images used for creating the imageset used for training + nameclass: + Name of the classifier one wants for their trained model .xml or .yml file + initialStepSize: + Parameter initialStepSize of a SVMSGD optimization problem that should be used to train the model. + marginReg: + Parameter marginRegularization of a SVMSGD optimization problem that should be used to train the model + marginType: + Parameter marginType of a SVMSGD optimization problem that should be used to train the model.it should be either 0 or 1. + optimalParams: + sets optimal parameters values for chosen SVM SGD model. + stepDecreasingPower: + Parameter stepDecreasingPower of a SVMSGD optimization problem that should be used to train the model. + svmsgdType: + Algorithm type of SVMSGD that should be used to train the model.it should be either 0 or 1. + + + + + Description + +This function is used to train an image classifier using the SVMSGD(Stochastic Gradient Descent SVM) Model. + + + + + + + Examples + + + diff --git a/help/en_US/undistortPoints.xml b/help/en_US/undistortPoints.xml new file mode 100755 index 0000000..4f9c08d --- /dev/null +++ b/help/en_US/undistortPoints.xml @@ -0,0 +1,70 @@ + + + + + + + + undistortPoints + Returns the ideal point coordinates from the observed point coordinates + + + + + Calling Sequence + + [idealPoints] = undistortPoints(observedPoints, camMat, disCoefMat, rectMat, newCamMat) + + + + + + Parameters + + observedPoints: + 1xN or Nx1 2-channel (CV_32FC2 or CV_64FC2). + camMat: + \vecthreethree{f_x}{0}{c_x}{0}{f_y}{c_y}{0}{0}{1} + disCoefMat: + Input vector of distortion coefficients (k_1, k_2, p_1, p_2[, k_3[, k_4, k_5, k_6]]) of 4, 5, or 8 elements. If the vector is NULL/empty, the zero distortion coefficients are assumed. + rectMat: + Rectification transformation in the object space (3x3 matrix). If the matrix is empty, the identity transformation is used. + newCamMat: + New camera matrix (3x3) or new projection matrix (3x4. If the matrix is empty, the identity new camera matrix is used. + idealPoints: + ideal point coordinates matrix. If matrix newCamMat is identity or omitted, idealPoints will contain normalized point coordinates. + + + + + Description + +Returns the ideal points coordinates from the observed point coordinates after undistortion and reverse perpective transformation. + + + + + + + Examples + + + diff --git a/images/dog.jpg b/images/dog.jpg new file mode 100644 index 0000000000000000000000000000000000000000..1eac69ae759bd1ef9bbe7633c6372cbca5ed8b81 GIT binary patch literal 17504 zcmbT6Wl&sE)8~hvK|=_x0RjYf*AU#@-5J~&EI@!jU~mZTZb1f@po0XL!GpUEIuK;@ zyzka-)qdLDK6USxbL!On)j4&$|K0tv__6_bqbRE&3qV2w0FeF-z{?6i8i0X@hK`1c zfsT&;`ZWe7_B$MGEG%r&w*+|aD9Na)D9I=&Xz1A)X=qvLC@7c&KC*Ih@$&LgGYW|b za*ML_@N)lW6QtL#Ut?ooli=WxaKEQ`&;9>wFTViz7yvjDD>4!-;1xa+GCtDF0D$`6 zccLQwmjV8#A-zIIK}AEyc#VnmZvo^D;1v=w@+%Z%R8$m{f2)K3%>z*IQQyAjl0qZU zut2AEf5#n~Sb#zIslJy`bNYgw$I>J0H6{@;2`SkJ21cfj%)EU30)j%q(w}8y<>VC< zwX}6~_4Ex4t*mWq?d%;KJ-xhreEs}E;a?*nqrOGQBqgV$rltSL$Sf=>E-5W5uc&Nj 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[a,bbox]=raw_CascadeObjectDetector(input_image1,classifierList,varargin(1),varargin(2),varargin(3),varargin(4),varargin(5)); + end + dimension=size(a) + for i = 1:dimension + out(:,:,i)=a(i); + end + +endfunction; diff --git a/macros/adaptHistEq.sci b/macros/adaptHistEq.sci new file mode 100644 index 0000000..edc9af9 --- /dev/null +++ b/macros/adaptHistEq.sci @@ -0,0 +1,52 @@ +// Copyright (C) 2015 - IIT Bombay - FOSSEE +// +// This file must be used under the terms of the CeCILL. +// This source file is licensed as described in the file COPYING, which +// you should have received as part of this distribution. The terms +// are also available at +// http://www.cecill.info/licences/Licence_CeCILL_V2-en.txt +// Author: Shubham Lohakare, Yash Balghat +// Organization: FOSSEE, IIT Bombay +// Email: toolbox@scilab.in +// +function [outputImg]=adaptHistEq(inputImage,varargin) +//Performs Contrast Limited Adaptive Histogram Equalisation +// +//Calling Sequence +//outputImage = adaptHistEq(inputImage) +//outputImage = adaptHistEq(inputImage, clip_limit) +// +//Parameters +//inputImage : The input image on which histogram equalisation is to be implemented +//clip_limit : The target hgram bins. +// +//Description +//As an alternative to using histeq, you can perform contrast-limited adaptive histogram equalization (CLAHE) using the adapthisteq function. While histeq works on the entire image, adapthisteq operates on small regions in the image, called tiles. Each tile's contrast is enhanced, so that the histogram of the output region approximately matches a specified histogram. After performing the equalization, adapthisteq combines neighboring tiles using bilinear interpolation to eliminate artificially induced boundaries. +// +//Examples +//a=imread("lena.jpeg"); +//k=adaptHistEq(a); +// +//Examples +//a=imread("photo.jpg"); +//k=adaptHistEq(a,64); +// +//Authors +//Shubham Lohakare, NITK Surathkal +//Yash Balghat + + [lhs rhs]=argn(0); + if rhs>2 + error(msprintf(" Too many input arguments")); + end + inputList=mattolist(inputImage); + select rhs + case 1 then + outputList=raw_adaptHistEq(inputList); + case 2 then + outputList=raw_adaptHistEq(inputList,varargin(1)); + end + for i=1:size(outputList) + outputImg(:,:,i)=outputList(i) + end +endfunction diff --git a/macros/arrowedline.bin b/macros/arrowedline.bin new file mode 100644 index 0000000000000000000000000000000000000000..3a7b2a0ea9f4b18f9adec0be30fd9b97c29d75ec GIT binary patch literal 8732 zcmeI2?QR=I6oxmYKv1b!qoX_{1nVns^?)NvEmE~@yx3V37%T-k^h?WP# zr|YY6W`F#a<_7(x?A+$UL3ub^1^(u_f_#Dh;7t|ms-2ESXJ*R zze}RqqHWQmy}i9PT|1&d%lkvTiyHStOQNBO`3(^~^!}1eU)NgHh^)&!^IVyS&}&5S zky{b1iq_jPHu1sydm`lVXTHbiAVUteiw$__lLxjfgC27DoMqqo`1Ls2a?D_14Co_d zeUIPIM8;Rc$rxM6{w>VFrQ1@P*JI6N=Y0|QGj0IFv3-Nv~+7z)K8E=I# z{Bwct@e{>{>~4E~mWh>k{;#nTyL%N(=&1`L>IgRU8kFL{Bi^f?6S=3o02b8U{g>u_ z>x|?LHq_mFG3yR&Qar?(tjV`ErYC;U8u0q#>U|Y`dWyA*ZLehwC*!X)#s=&0dOP-7 zr6%k{*g*z9w(-F}fo=HS0~t3W=Rj|J@52UT>p0%Hk9bc_djz}224BR4jOD?>cHv&W@1vDzp6!(xJO@Uks(@Yu2DFksGk<#5R5m)5|3W8RJIBFDbEAabtU z!>3l{34tGe+y}%-?2a25dI>$Q$e}}xkb@6S$k_&b_g|wiGT!eU3-_lTi}UBoGsdx) ze^gw+0=%qGAG)ryu=!SUV8Cy6*k7kLmLSj7E9x78;i@PECf*t_3}hdrM8#)LJW=6Tj|`M$-4Gmvos zSN98b1Z%K6YuJE6>_Pex402~JWB0pobpL|gVfACLe%xvxWAmw@D|03`R}wc-Y>v_eV_cD^RLR8 z7&%M$+3kA8+|h$ijKqo!>>)#b@WI)!GlvYm;TeC%@Zl>Y zo^RN|7VpU5i7Y&FAtrpMx%k<5TXX2n-^=%L04HjZt0B08uWRO>N7g;Ue5p=+>p}KU z)rsdl{X|bvANtC*b8W<$)Y$v#NxygBluu$LHu?u5w?@QVj!)e5ZMp}=_imoG{_*aS z-Yw;KofmQD^1==_QXAsO7pk>$BQ|6q`i$#cQGacaemWc9YpUwbm~&jjgRRnc#OI0uTga@}!{J7^ zGZ-cwb8!+kadIV2+5fFh6=g?L6O6#|fgDjU#`v6-pQgvUVDl2wX7q#ZIa|1nA;)YC zF~`z((*h+G`4&xm7lkKv0c-Z6 zw7we`GsO+{ovzW==ttS0Mjwml#d(dY>fdSvMlbt(_Z!wn>HB$UO^(;pj5B zC(>{9nEQ=$^zr&_d-Stx&~H9-&!0i3^9-8qm80!V(>9LQZ__qbPo!t*Q}-=>Kh|MPUk~kPPh>*>N1;h~{fy9v`cmD6q0VHk+@pVFk`X%$M z_IT`QCA8wOkxEnDUG=K!b#;$3dq-y{7XyF$J3BkOC9|{n!0N@tgIb$RAD_+7C zgB6=cr;{fK=Zneyd^|8eKA0SiS3pP8hvV7F^+zklHMpC9zBd1$g1=qy-z)jH+YN_@oE>tJ2~9S@xdKx^bVgk83_WJT4uke9yc2)ZOy;S*<-Pu{SLj zd=}lD{eq*eZT8_Cju^)L_+&5DWae$Mb%T5gY;;B{~ zw)>^VV0>6QzrV`ws?+5?#8Kv8!DpA=PzOv{;YeI#@vNt(v#-{MVzvGBb=k0ck-cG` zT7Iv((nDhDD`Ppa>*u#=xY^X#a`->;bKUW??aawNy+Z$``o$jF6a4E{{y9JCn?=oq5Br{d?e|m8 z2OJy`_Q4mc#lMfsO||gTGw{<#axw2d?B_MqUu@OkohOc-)2D5I^1du#D^B=eD|Vl+ z^!B3G*e4JE;SGj-#O9y8Jz=tqUwFDQ%pbBQNb z_z)Xc$*Iqqd3Sn0e^~uFW3}_Ku3oyltf^xtZ)@A`pLUPZgYa=~4L6D7nf>bXt!92O z!fkRJ>bv%yy6+r%x2fZ*#FPBj=kS9LHyor-)QbnTWnb|ihi#m{C?D`%ox@k>P#>fR zU-mitr0eVae$IK*=lPB7EJv5CvytC@?eFD9x0ZW?ZS@m)~o7AyeBCmH! z#IwfM``F)Q$NylUze z2bQzKX45y3zl-NuzO^|X&F8bD$?3{Rkow;7Pua*%?yq;Y#^DSn4gPNXy`+|Ia~a5E z#jed`(|4M6oAqxtt<9$IH|sX*-*Q@;lhNXQZ{T|rUT_j#-YC7#%cv!z(fhn?vTO73 z`Kp0fs`u^B4;5^Ga(pm7oy?|7uRA4qyjhBVSHs=kuV3n$ZGP<3epSL&?O&8kdNDFg zKk9|=In*B?=W=N7wr}Iyd-CPrG5CvcZVv*Pm!Ti|4aR`J(2q;L9T`rJ&UbtRb2K zi3J-hJx#f~`qiuInx5foZ#te#w=c${#bN6=9t;N8g89~H@nPearB#%*o!Ml%*llfU z%*!m^%KF3LELa4$gGsO(90u0+f@v@c#8{sNd}6*Xm&?sO?*(GSv-!kt1;tl6`0N$C z6C4Ng0QYu4hgdPgK)%wUW^wY16=N^X(kOSW(^C2HsL38Np7Qe-XXT~YKL1|@)vK6m zn@$|<9>`Z*rSENegzG_|4tDjF-Nj88?t|cEfb)J(wbHK_PlMOtuR8HsqxnvNM-E!V zo#g3v6g&$mH(vRQzj`V6pU&W-sjv3X)YVr#y_z?!wFY@;co#l3(Bi3XH8=}Teq5zJ z=Gxwm-Bri)#*f3f;pvK#uWNSHW==r<_8i(%+S!I1hT|WJ;KDpk z==)#pj*X@VU((A*v1`utu-@hNEXBRZhyj yOXuS~>HD^R4@Z_)G4sv+C&P~K_m9N*KHm&(G_n56=P6g;cRfq1{^-$pWB&veEu$&` literal 0 HcmV?d00001 diff --git a/macros/boundingRect.sci b/macros/boundingRect.sci new file mode 100644 index 0000000..400828e --- /dev/null +++ b/macros/boundingRect.sci @@ -0,0 +1,34 @@ +// Copyright (C) 2015 - IIT Bombay - FOSSEE +// +// This file must be used under the terms of the CeCILL. +// This source file is licensed as described in the file COPYING, which +// you should have received as part of this distribution. The terms +// are also available at +// http://www.cecill.info/licences/Licence_CeCILL_V2-en.txt +// Author: Sukul Bagai +// Organization: FOSSEE, IIT Bombay +// Email: toolbox@scilab.in +function [rectMat]=boundingRect(points) +//this function Calculates the up-right bounding rectangle of a point set. +// +// Calling Sequence +// +// z=imread("lena.jpeg",0); +// rect=boundingRect(points); +// +// Parameters +// +// rect: the rectangle coordinates +// points: the set of 2D points. It must be N*2. +// +// Description +// +// Calculates the up-right bounding rectangle of a point set. +// +// Examples +// +// z=imread("lena.jpeg",0); +// kaze=detectKAZEFeatures(z)x +// rect=boundingRect(kaze.KeyPoints); + rectMat=raw_boundingRect(points); +endfunction diff --git a/macros/boxfilter.sci b/macros/boxfilter.sci new file mode 100644 index 0000000..f1b4d27 --- /dev/null +++ b/macros/boxfilter.sci @@ -0,0 +1,50 @@ +// Copyright (C) 2015 - IIT Bombay - FOSSEE +// +// This file must be used under the terms of the CeCILL. +// This source file is licensed as described in the file COPYING, which +// you should have received as part of this distribution. The terms +// are also available at +// http://www.cecill.info/licences/Licence_CeCILL_V2-en.txt +// Author: Shubham Lohakare, Yash Balghat +// Organization: FOSSEE, IIT Bombay +// Email: toolbox@scilab.in +// +function [out]=boxfilter(InputArraysrc, intddepth,size1x,size1y,pointx,pointy, bool_normalize) +//Blurs an image using the box filter. +// +//Calling Sequence +//outputImage = boxfilter(InputArraysrc, intddepth,size1x,size1y,pointx,pointy, bool_normalize) +// +//Parameters +//InputArraysrc : Input image to be blurred +//intddepth : The output image depth (-1 to use src.depth()) +//size1x : Width for the blurring kernel size +//size1y : Height for the blurring kernel size +//pointx : x-coordinate for anchor point (Default value -1) +//pointy : y-coordinate for anchor point (Default value -1) +//bool_normalize : flag, specifying whether the kernel is normalized by its area or not +// +//Description +//Unnormalized box filter is useful for computing various integral characteristics over each pixel neighborhood, such as covariance matrices of image derivatives (used in dense optical flow algorithms, and so on). +// +//Examples +//a = imread("lena.jpeg"); +//k=boxfilter(a,-1,40,80,-1,-1,"False"); +// +//Examples +//a = imread("photo.jpg"); +//k=boxfilter(a,-1,8,8,-1,-1,"True"); +// +//Authors +//Shubham Lohakare, NITK Surathkal +//Priyanka Hiranandani, NIT Surat + + + input_image1=mattolist(InputArraysrc) + a=raw_boxfilter(input_image1, intddepth,size1x,size1y,pointx,pointy, bool_normalize) + dimension=size(a) + for i = 1:dimension + out(:,:,i)=(a(i)) + end + +endfunction diff --git a/macros/circle.bin b/macros/circle.bin new file mode 100644 index 0000000000000000000000000000000000000000..090afe52fee598f5bca6612252be7bc720e4badb GIT binary patch literal 9544 zcmeI2%WfP+6o$v#GU<%RPJ=yTdd40*BM3=Iz<^K`BEm(8JsTueQC3L201IA$7h=Vl zcOVOp5JEx-SOVt%+Wng|HC>Z&f+L92(ouJvI@kZ4s_MD)%Br`~zc_cTb~>FE(Qtb_ zHwUAuxpJ_zJ)V}E#rmv)-Dz()tX9iGG44-?YtvqTFs>xB7x`w&R#mK)+oO3m)pV!W z*q*hG)Ov=0F2mm`s-jvi2dRhhY^SrPJa$C4MHfZi9UL5-*S!>t8Xhv+qJgL<8jF}8 zir}FKA70fwZ|L3^F$b3L3(-VmyNsD@gC)T!G+#-uYm

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z`6!zI^ojKYe?-{^jfGfLV8)-(~H;^sHZrT>mSC$KB-P{|WcMfIoTc$#XBcC!aj$ z`+0@i$t55Eef&TqBJDrq_8)Tl{Q3O*U(uFUEbX6i`=<@t|2=Cj?_ueD(a-;JMgaNv z|3-V_9U1>Izc1(U3%>nbe{sBz$7=o)I{YE-#q+=P;!E^c=hBP5;Zu)JchBADPco0E z_#U_KT=wldmwo$3B;2Ea(oU|QK;yXmqnCaAM=$&KKaJYb$IIFGXV94XlJ(1bI9Ffs z?cdFwmvQCxvpoK)+~BLU-^lLMT +#include "opencv2/core/core.hpp" +#include "opencv2/objdetect.hpp" +#include "opencv2/highgui/highgui.hpp" +#include "opencv2/opencv.hpp" +#include +#include "opencv2/videoio.hpp" +#include +using namespace cv; +using namespace std; + +extern "C" +{ + #include "api_scilab.h" + #include "Scierror.h" + #include "BOOL.h" + #include + #include "sciprint.h" + #include "../common.h" + double readdoublec_from_scilab(int cnt) + { + + SciErr sciErr; + int *piAddr=NULL; + double val=0; + int intErr; + + sciErr = getVarAddressFromPosition(pvApiCtx,cnt,&piAddr); + if (sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + intErr = getScalarDouble(pvApiCtx, piAddr ,&val); + + if(isDoubleType(pvApiCtx, piAddr)) + return val; + else + { + Scierror(999,"Error: the input argument is not of type double"); + return 0; + + + } + + + } + bool file_existsindirectory_check(const std::string& name) { + struct stat buffer; + return (stat (name.c_str(), &buffer) == 0); + } + + int opencv_CascadeObjectDetector(char *fname, unsigned long fname_len) + { + SciErr sciErr; + int intErr = 0; + int iRows=0,iCols=0; + int iRows1,iCols1; + int *piAddr = NULL; + int *piAddrNew = NULL; + int *piAddr2 = NULL; + int *piAddr3 = NULL; + int *piLen = NULL; + char **object = NULL; + int i; + double minX,minY,maxX,maxY; + double *bboxes = NULL; + double *minSize,*maxSize; + double scale=1.05;//all optional arguments are set to their default values + int minNeighbors=2,flags=2; + + CheckInputArgument(pvApiCtx, 2, 7); + CheckOutputArgument(pvApiCtx, 1, 2) ; + Mat image,new_image,image_gray; + //get no. of input arguments + int n=*getNbInputArgument(pvApiCtx); + retrieveImage(image, 1); + + ///resize(image,image,Size(800,600),0,0,cv::INTER_AREA); + + sciErr = getVarAddressFromPosition(pvApiCtx,2, &piAddr2); + + if (sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + + sciErr = getMatrixOfString(pvApiCtx, piAddr2, &iRows, &iCols, NULL, NULL); + if(sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + piLen = (int*)malloc(sizeof(int) * iRows * iCols); + //second call to retrieve length of each string + sciErr = getMatrixOfString(pvApiCtx, piAddr2, &iRows, &iCols, piLen, NULL); + if(sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + object= (char**)malloc(sizeof(char*) * iRows * iCols); + for(i = 0 ; i < iRows * iCols ; i++) + { + object[i] = (char*)malloc(sizeof(char) * (piLen[i] + 1));//+ 1 for null termination + } + //third call to retrieve data + sciErr = getMatrixOfString(pvApiCtx, piAddr2, &iRows, &iCols, piLen,object); + if(sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + + ///Reading optional arguments + int cnt=3; + switch(n) + { + case 3: + + scale=readdoublec_from_scilab(cnt); + cnt++; + break; + case 4: + + scale=readdoublec_from_scilab(cnt); + cnt++; + minNeighbors=(int)readdoublec_from_scilab(cnt); + cnt++; + break; + case 5: + + scale=readdoublec_from_scilab(cnt); + cnt++; + minNeighbors=(int)readdoublec_from_scilab(cnt); + cnt++; + flags=(int)readdoublec_from_scilab(cnt); + if(flags!=2 && flags!=1 && flags!=4 && flags!=8) + { + Scierror(999,"Error: the flag should be {1,2,4,8}\n"); + return 0; + + } + + cnt++; + break; + case 6: + + scale=readdoublec_from_scilab(cnt); + cnt++; + minNeighbors=(int)readdoublec_from_scilab(cnt); + cnt++; + flags=(int)readdoublec_from_scilab(cnt); + cnt++; + if(flags!=2 && flags!=1 && flags!=4 && flags!=8) + { + Scierror(999,"Error: the flag should be {1,2,4,8}\n"); + return 0; + + } + + sciErr = getVarAddressFromPosition(pvApiCtx,cnt,&piAddr); + if (sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + sciErr = getMatrixOfDouble(pvApiCtx, piAddr, &iRows1, &iCols1, &minSize); + if(sciErr.iErr) + { + printError(&sciErr,0); + return 0; + } + + //check dimensions + if(iCols1!=2 || iRows1!=1) + { + Scierror(999,"The minSize argument must have dimensions 1*2"); + return -1; + } + + cnt++; + + + break; + case 7: + + scale=readdoublec_from_scilab(cnt); + cnt++; + minNeighbors=(int)readdoublec_from_scilab(cnt); + cnt++; + flags=(int)readdoublec_from_scilab(cnt); + cnt++; + if(flags!=2 && flags!=1 && flags!=4 && flags!=8) + { + Scierror(999,"Error: the flag should be {1,2,4,8}\n"); + return 0; + + } + + sciErr = getVarAddressFromPosition(pvApiCtx,cnt,&piAddr); + if (sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + sciErr = getMatrixOfDouble(pvApiCtx, piAddr, &iRows1, &iCols1, &minSize); + if(sciErr.iErr) + { + printError(&sciErr,0); + return 0; + } + + //check dimensions + if(iCols1!=2 || iRows1!=1) + { + Scierror(999,"The minSize argument must have dimensions 1*2 "); + return -1; + } + cnt++; + + sciErr = getVarAddressFromPosition(pvApiCtx,cnt,&piAddr); + if (sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + sciErr = getMatrixOfDouble(pvApiCtx, piAddr, &iRows1, &iCols1, &maxSize); + if(sciErr.iErr) + { + printError(&sciErr,0); + return 0; + } + + //check dimensions + if(iCols1!=2 || iRows1!=1) + { + Scierror(999,"The maxSize argument must have dimensions 1*2 "); + return -1; + } + + break; + + } + + + /* Actual Processing*/ + try{ + if(image.channels()==1) + { + image.convertTo(image,CV_8U); + image.copyTo(image_gray); + + equalizeHist( image_gray, image_gray ); + + + + } + else + { + //Converting image from rgb to gray scale image. + image.convertTo(image,CV_8U); + cvtColor( image, image_gray, CV_BGR2GRAY ); + //equalizing the histrogram of gray scale image + equalizeHist( image_gray, image_gray ); + } + + + + vector found; + + //set minSize and maxSize if passed + if(n==6) + { + minX=minSize[0]; + minY=minSize[1]; + + } + else if(n==7) + { + minX=minSize[0]; + minY=minSize[1]; + + maxX=maxSize[0]; + maxY=maxSize[1]; + + + + } + + + + int j; + for(j=0;j +#include "opencv2/core/core.hpp" +#include "opencv2/highgui/highgui.hpp" +#include "opencv2/opencv.hpp" +#include +#include // std::max + +using namespace cv; +using namespace std; + +extern "C" +{ + #include "api_scilab.h" + #include "Scierror.h" + #include "BOOL.h" + #include + #include + #include "../common.h" + + + + int opencv_adaptHistEq(char *fname, unsigned long fname_len) + { + + //DEclaring variables + SciErr sciErr; + int intErr = 0; + int iRows=0,iCols=0; + int *piAddr2 = NULL; + int i,j,k; + double clip_limit; + + //Default clip limit + clip_limit = 0.001; + + //checking input argument + CheckInputArgument(pvApiCtx, 1, 2); + CheckOutputArgument(pvApiCtx, 1, 1);//Checking output argument + + int inputarg = *getNbInputArgument(pvApiCtx);//Storing the number of input arguments + + + Mat input_img; + retrieveImage(input_img,1);//Retrieving the image + input_img.convertTo(input_img,CV_8U);//Converting the image to 8-bit image + + if(inputarg == 2){ + //for value of clip_limit + sciErr = getVarAddressFromPosition(pvApiCtx,2,&piAddr2); + if (sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + intErr = getScalarDouble(pvApiCtx, piAddr2, &clip_limit);//Getting the value of clip_limit + if(intErr) + return intErr; + } + + float C[256]; + + //Getting the number of rows and columns from the image + int row = input_img.rows; + int col = input_img.cols; + + int window_x = 90; + int window_y = 90; + + int min_x, min_y, max_x, max_y; + Mat window_matrix; + + int histSize = 256; //from 0 to 255 + float range[] = { 0, 256 } ; + const float* histRange = { range }; + + Mat H; + Mat output_img = Mat::zeros(input_img.size(), input_img.type()); + + if(input_img.channels()==1){ + for(int i=0; i(i,j)==0) + output_img.at(i,j) =0; + else + { + calcHist(&window_matrix, 1, 0, Mat(), H, 1, &histSize, &histRange);//Calculating hist + + int N = window_matrix.rows; + int M = window_matrix.cols; + H=H/(N*M); + + for(int z=0; z<256; z++){ + if(H.at(0,z) > clip_limit) + H.at(0,z) = clip_limit; + } + + float contrastArea = 1.0 - cv::sum(H).val[0]; + float height = contrastArea / 256.00; + + H = H + height; + C[0] = H.at(0,0)*255; + for(int k=1; k<256; k++){ + C[k]= C[k-1] + H.at(0,k)*255; + } + + output_img.at(i,j) = C[input_img.at(i,j)]; + } + } + } + } + else if(input_img.channels()==3){ + vector Ichannels; + split(input_img, Ichannels); + + for(int d=0; d<3; d++){ + for(int i=0; i(i,j)==0) + output_img.at(i,j)[d] =0; + else + { + calcHist(&window_matrix, 1, 0, Mat(), H, 1, &histSize, &histRange); + + int N = window_matrix.rows; + int M = window_matrix.cols; + H=H/(N*M); + + for(int z=0; z<256; z++){ + if(H.at(0,z) > clip_limit) + H.at(0,z) = clip_limit; + } + + float contrastArea = 1.0 - cv::sum(H).val[0]; + float height = contrastArea / 256.00; + + H = H + height; + C[0] = H.at(0,0)*255; + for(int k=1; k<256; k++){ + C[k]= C[k-1] + H.at(0,k)*255; + } + + output_img.at(i,j)[d] = C[Ichannels[d].at(i,j)]; + } + } + } + } + + + } + + + + //returning image + string tempstring = type2str(output_img.type()); + char *checker; + checker = (char *)malloc(tempstring.size() + 1); + memcpy(checker, tempstring.c_str(), tempstring.size() + 1); + returnImage(checker,output_img,1); + free(checker); + + //Assigning the list as the Output Variable + AssignOutputVariable(pvApiCtx, 1) = nbInputArgument(pvApiCtx) + 1; + //Returning the Output Variables as arguments to the Scilab environment + ReturnArguments(pvApiCtx); + return 0; + + } +/* ==================================================================== */ +} + diff --git a/sci_gateway/cpp/opencv_arrowedline.cpp b/sci_gateway/cpp/opencv_arrowedline.cpp new file mode 100644 index 0000000..9344f87 --- /dev/null +++ b/sci_gateway/cpp/opencv_arrowedline.cpp @@ -0,0 +1,217 @@ +/******************************************************** + Author: Abhilasha Sancheti & Sukul Bagai +********************************************************* + return_image = arrowedline(image , x1 , y1 , x2,y2,r_value,g_value,b_value,thickness,linetype,shift,tiplength); +********************************************************/ + +#include +#include "opencv2/core/core.hpp" +#include "opencv2/highgui/highgui.hpp" +#include "opencv2/opencv.hpp" +#include +using namespace cv; +using namespace std; +extern "C" +{ + #include "api_scilab.h" + #include "Scierror.h" + #include "BOOL.h" + #include + #include + #include "../common.h" + + int opencv_arrowedline(char *fname, unsigned long fname_len) + { + + SciErr sciErr; + int intErr=0; + int iRows=0,iCols=0; + int *piAddr2 = NULL; + int *piAddr3 = NULL; + int *piAddr4 = NULL; + int *piAddr5 = NULL; + int *piAddr6 = NULL; + int *piAddr7 = NULL; + int *piAddr8 = NULL; + int *piAddr9 = NULL; + int *piAddr10 = NULL; + int *piAddr11 = NULL; + int *piAddr12 = NULL; + int i,j,k; + double thickness=1 , linetype=8,shift =0 ,tiplength=0.1; + double x1,y1,x2,y2,r_value,g_value,b_value; + + + //checking input argument + CheckInputArgument(pvApiCtx, 8, 12); + CheckOutputArgument(pvApiCtx, 1, 1) ; + int n=*getNbInputArgument(pvApiCtx); + + Mat src; + retrieveImage(src,1); + + //for value of x coordinate of first point + sciErr = getVarAddressFromPosition(pvApiCtx,2,&piAddr2); + if (sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + intErr = getScalarDouble(pvApiCtx, piAddr2 ,&x1); + if(intErr) + return intErr; + + //for value of y coordinate of first point + sciErr = getVarAddressFromPosition(pvApiCtx,3,&piAddr3); + if (sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + intErr = getScalarDouble(pvApiCtx, piAddr3,&y1); + if(intErr) + return intErr; + + //for value of x coordinate of second point + sciErr = getVarAddressFromPosition(pvApiCtx,4,&piAddr4); + if (sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + intErr = getScalarDouble(pvApiCtx, piAddr4 ,&x2); + if(intErr) + return intErr; + + ///for value of y coordinate of second point + sciErr = getVarAddressFromPosition(pvApiCtx,5,&piAddr5); + if (sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + intErr = getScalarDouble(pvApiCtx, piAddr5 ,&y2); + if(intErr) + return intErr; + + //for value of R value of colour + sciErr = getVarAddressFromPosition(pvApiCtx,6,&piAddr6); + if (sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + intErr = getScalarDouble(pvApiCtx, piAddr6,&r_value); + if(intErr) + return intErr; + + // for G value of colour + sciErr = getVarAddressFromPosition(pvApiCtx,7,&piAddr7); + if (sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + intErr = getScalarDouble(pvApiCtx, piAddr7,&g_value); + if(intErr) + return intErr; + + // for B value of colour + sciErr = getVarAddressFromPosition(pvApiCtx,8,&piAddr8); + if (sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + intErr = getScalarDouble(pvApiCtx, piAddr8,&b_value); + if(intErr) + return intErr; + + + //Reading optional arguments + if(n>8) + { + for(int i=9;i<=n;i++) + { + + double r; + sciErr = getVarAddressFromPosition(pvApiCtx,i,&piAddr12); + if (sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + + intErr = getScalarDouble(pvApiCtx, piAddr12,&r); + if(intErr) + return intErr; + //assign value + if(i==9) + thickness=r; + else if(i==10) + linetype=r; + else if(i==11) + shift=r; + else + tiplength=r; + + } + } + //temporary pt variable, to use in function as centre + Point pt1(x1,y1); + Point pt2(x2,y2); + + + /// checking the parmeters for correct values + if( r_value <0 || r_value >255) + { + r_value=0; + sciprint(" r value of colour should be between 0 and 255 , using 0 instead\n"); + } + if( g_value <0 || g_value >255) + { + g_value=0; + sciprint(" g value of colour should be between 0 and 255 , using 0 instead\n"); + } + if( b_value <0 || b_value >255) + { + b_value=0; + sciprint(" b value of colour should be between 0 and 255 , using 0 instead\n"); + } + if ((linetype!=0) && (linetype!=4)&& (linetype!=8)) + { + linetype=8; + sciprint("Only 0/4/8 allowed , using 8 instead"); + } + //calling the opencv function + try + { + arrowedLine( src, pt1, pt2, Scalar(b_value,g_value,r_value), thickness, linetype, shift, tiplength); + } + catch(cv::Exception& e) + { + + Scierror(999,e.what()); + return 0;; + + } + + + string tempstring = type2str(src.type()); + char *checker; + checker = (char *)malloc(tempstring.size() + 1); + memcpy(checker, tempstring.c_str(), tempstring.size() + 1); + returnImage(checker,src,1); + free(checker); + + //Assigning the list as the Output Variable + AssignOutputVariable(pvApiCtx, 1) = nbInputArgument(pvApiCtx) + 1; + //Returning the Output Variables as arguments to the Scilab environment + ReturnArguments(pvApiCtx); + return 0; + + + } + +} + diff --git a/sci_gateway/cpp/opencv_blur.cpp b/sci_gateway/cpp/opencv_blur.cpp new file mode 100644 index 0000000..62f5db7 --- /dev/null +++ b/sci_gateway/cpp/opencv_blur.cpp @@ -0,0 +1,143 @@ +/*************************************************** +Author : Sukul Bagai +***************************************************/ + +#include +#include "opencv2/core/core.hpp" +#include "opencv2/highgui/highgui.hpp" +#include "opencv2/opencv.hpp" +#include +using namespace cv; +using namespace std; +extern "C" +{ + #include "api_scilab.h" + #include "Scierror.h" + #include "BOOL.h" + #include + #include + #include "../common.h" + + + + int opencv_blur(char *fname, unsigned long fname_len) + { + + SciErr sciErr; + int intErr=0; + int iRows=0,iCols=0; + int *piAddr2 = NULL; + int *piAddr3 = NULL; + int *piAddr4 = NULL; + int *piAddr5 = NULL; + double ksize_width,ksize_height,anchorX,anchorY; + + //checking input argument + CheckInputArgument(pvApiCtx, 5, 5); + CheckOutputArgument(pvApiCtx, 1, 1) ; + + Mat image; + retrieveImage(image,1); + + //for value of ksize_height + sciErr = getVarAddressFromPosition(pvApiCtx,2,&piAddr2); + if (sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + intErr = getScalarDouble(pvApiCtx, piAddr2, &ksize_height); + if(intErr) + return intErr; + + //for value of ksize_width + sciErr = getVarAddressFromPosition(pvApiCtx,3,&piAddr3); + if (sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + intErr = getScalarDouble(pvApiCtx, piAddr3 ,&ksize_width); + if(intErr) + return intErr; + + //for value of anchorX + sciErr = getVarAddressFromPosition(pvApiCtx,4,&piAddr4); + if (sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + intErr = getScalarDouble(pvApiCtx, piAddr4, &anchorX); + if(intErr) + return intErr; + + //for value of anchorY + sciErr = getVarAddressFromPosition(pvApiCtx,5,&piAddr5); + if (sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + intErr = getScalarDouble(pvApiCtx, piAddr5, &anchorY); + if(intErr) + return intErr; + + //applying checks on input parameters + Mat new_image(image.rows,image.cols,image.type()); + + //error checks + if(ksize_height<0) + { + sciprint("Positive Value Required for Height. 1 value was used instead"); + ksize_height=1; + } + if(ksize_width<0) + { + sciprint("Positive Value Required for Width. 1 value was used instead"); + ksize_width=1; + } + if(ksize_width != ksize_height) + { + sciprint("Blurring Kernel Size not equal. Value of ksize_height used for ksize_width as well"); + ksize_width = ksize_height; + } + if(anchorX >= ksize_height || anchorY >= ksize_width) + { + sciprint("Invalid anchor points. Default point (-1,-1) used instead"); + anchorY=-1; + anchorX=-1; + } + + //defining temporary size and point type variables to use in the function + Size sz(ksize_height,ksize_width); + Point pt(anchorX,anchorY); + + //void blur(InputArray src, OutputArray dst, Size ksize, Point anchor=Point(-1,-1), int borderType=BORDER_DEFAULT ) + try + { + blur(image,new_image,sz,pt); + } + catch(cv::Exception& e) + { + sciprint("%s",e.what()); + return 0; + + } + + string tempstring = type2str(new_image.type()); + char *checker; + checker = (char *)malloc(tempstring.size() + 1); + memcpy(checker, tempstring.c_str(), tempstring.size() + 1); + returnImage(checker,new_image,1); + free(checker); + + //Assigning the list as the Output Variable + AssignOutputVariable(pvApiCtx, 1) = nbInputArgument(pvApiCtx) + 1; + //Returning the Output Variables as arguments to the Scilab environment + ReturnArguments(pvApiCtx); + return 0; + + } +/* ==================================================================== */ +} \ No newline at end of file diff --git a/sci_gateway/cpp/opencv_boundingRect.cpp b/sci_gateway/cpp/opencv_boundingRect.cpp new file mode 100644 index 0000000..a016501 --- /dev/null +++ b/sci_gateway/cpp/opencv_boundingRect.cpp @@ -0,0 +1,92 @@ +/******************************************************** + Author: Sukul Bagai +********************************************************* + rectangle_dimensions_arry(height, width, x, y) = boundingRect ( vector ) +********************************************************/ + +#include +#include "opencv2/core/core.hpp" +#include "opencv2/highgui/highgui.hpp" +#include "opencv2/opencv.hpp" +#include +using namespace cv; +using namespace std; +extern "C" +{ + #include "api_scilab.h" + #include "Scierror.h" + #include "BOOL.h" + #include + #include + #include "../common.h" + + int opencv_boundingRect(char *fname, unsigned long fname_len) + { + SciErr sciErr; + int intErr=0; + int iRows=0,iCols=0; + int *piAddr1 = NULL; + int *piAddrNew = NULL; + int i,j,k ; + double *points; + + //checking input argument + CheckInputArgument(pvApiCtx, 1, 1); + CheckOutputArgument(pvApiCtx, 1, 1); + +//retreive the points + sciErr = getVarAddressFromPosition(pvApiCtx,1,&piAddr1); + if (sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + sciErr = getMatrixOfDouble(pvApiCtx, piAddr1, &iRows, &iCols,&points); + if(sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + + vector actualPoints; + for(int i=0;i +#include "opencv2/core/core.hpp" +#include "opencv2/highgui/highgui.hpp" +#include "opencv2/opencv.hpp" +#include +using namespace cv; +using namespace std; +extern "C" +{ + #include "api_scilab.h" + #include "Scierror.h" + #include "BOOL.h" + #include + #include "../common.h" + int opencv_boxfilter(char *fname, unsigned long fname_len) + { + // Error management variable + SciErr sciErr; + + //Declaration of variables + int iRows = 0; + int iCols = 0; + int piRows = 0; + int piCols = 0; + int* piAddr = NULL; + int* piAddr2 = NULL; + int* piAddr3 = NULL; + int* piAddr4 = NULL; + int* piAddr5 = NULL; + int* piAddr6 = NULL; + int* piAddr7 = NULL; + int* piAddrNew = NULL; + int* piLen = NULL; + double* pstData = NULL; + char** pstData2 = NULL; + double *rrows; + double *rcols; + int noofitem; + double ddepth; + bool normalize; + int borderType,i; + int error; + double sz1,sz2; + double pi1,pi2; + + // checking input argument + CheckInputArgument(pvApiCtx,7,7); + //checking output argument + CheckOutputArgument(pvApiCtx, 1, 1); + + //for first argument + Mat img; + retrieveImage(img,1); + img.convertTo(img,CV_8U); + //second argument + sciErr = getVarAddressFromPosition(pvApiCtx,2,&piAddr2); + if (sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + //this function will fetch value of second argument + error=getScalarDouble(pvApiCtx,piAddr2,&ddepth); + if(error!=0) + { + printf("error in retrieving second argument"); + return 0; + } + //third argument + sciErr = getVarAddressFromPosition(pvApiCtx,3,&piAddr3); + if (sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + //this function will fetch value of third argument + error=getScalarDouble(pvApiCtx,piAddr3,&sz1); + if(error!=0) + { + printf("error in retrieving second argument"); + return 0; + } + + //fourth argument + sciErr = getVarAddressFromPosition(pvApiCtx,4,&piAddr4); + if (sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + //this function will fetch value of fourth argument + error=getScalarDouble(pvApiCtx,piAddr4,&sz2); + if(error!=0) + { + printf("error in retrieving second argument"); + } + //fifth argument + sciErr = getVarAddressFromPosition(pvApiCtx,5,&piAddr5); + if (sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + //this function will fetch value of fifth argument + error=getScalarDouble(pvApiCtx,piAddr5,&pi1); + if(error!=0) + { + printf("error in retrieving second argument"); + } + //sixth argument + sciErr = getVarAddressFromPosition(pvApiCtx,6,&piAddr6); + if (sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + //this function will fetch value of sixth argument + error=getScalarDouble(pvApiCtx,piAddr6,&pi2); + if(error!=0) + { + printf("error in retrieving second argument"); + } + //seventh argument + sciErr = getVarAddressFromPosition(pvApiCtx,7,&piAddr7); + if (sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + //this function will fetch value of seventh argument + sciErr = getMatrixOfString(pvApiCtx, piAddr7, &iRows, &iCols, NULL, NULL); + if(sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + piLen = (int*)malloc(sizeof(int) * iRows * iCols); + //second call to retrieve length of each string + sciErr = getMatrixOfString(pvApiCtx, piAddr7, &iRows, &iCols, piLen, NULL); + if(sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + + pstData2 = (char**)malloc(sizeof(char*) * iRows * iCols); + for(i = 0 ; i < iRows * iCols ; i++) + { + pstData2[i] = (char*)malloc(sizeof(char) * (piLen[i] + 1));//+ 1 for null termination + } + //third call to retrieve data + sciErr = getMatrixOfString(pvApiCtx, piAddr7, &iRows, &iCols, piLen, pstData2); + if(sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + if(!strcmp(pstData2[0],"True")) + { + normalize=true; + } + else if(!strcmp(pstData2[0],"False")) + { + normalize=true; + + } + + //size constructor + Size ksize=Size(sz1,sz2); + //anchor constructor + Point anchor=Point(pi1,pi2); + Mat dst; + try{ + //call to open cv boxfilter + boxFilter(img,dst,ddepth,ksize,anchor,normalize,BORDER_DEFAULT); + } + catch(Exception& e) + { + const char* err=e.what(); + printf("%s",err); + } + + //returning variable to scilab console + string tempstring = type2str(dst.type()); + char* checker = (char *)malloc(tempstring.size() + 1); + memcpy(checker, tempstring.c_str(), tempstring.size() + 1); + returnImage(checker,dst,1); + //returning output variable + AssignOutputVariable(pvApiCtx, 1) = nbInputArgument(pvApiCtx) + 1; + ReturnArguments(pvApiCtx); + return 0; + + + } +} diff --git a/sci_gateway/cpp/opencv_circle.cpp b/sci_gateway/cpp/opencv_circle.cpp new file mode 100644 index 0000000..96f1bc4 --- /dev/null +++ b/sci_gateway/cpp/opencv_circle.cpp @@ -0,0 +1,250 @@ +/******************************************************** + Author: Abhilasha Sancheti +********************************************************* + return_image = circle(input_image , x_coordinate_of_centre , y_coordinate_centre , radius, r_value,g_value,b_value,thickness,linetype,shift); +********************************************************/ + +#include +#include "opencv2/core/core.hpp" +#include "opencv2/highgui/highgui.hpp" +#include "opencv2/opencv.hpp" +#include +using namespace cv; +using namespace std; +extern "C" +{ + #include "api_scilab.h" + #include "Scierror.h" + #include "BOOL.h" + #include + #include + #include "../common.h" + + int opencv_circle(char *fname, unsigned long fname_len) + { + + SciErr sciErr; + int intErr=0; + int iRows=0,iCols=0; + int *piAddrNew = NULL; + int *piAddr2 = NULL; + int *piAddr3 = NULL; + int *piAddr4 = NULL; + int *piAddr5 = NULL; + int *piAddr6 = NULL; + int *piAddr7 = NULL; + int *piAddr8 = NULL; + int *piAddr9 = NULL; + int *piAddr10 = NULL; + int i,j,k; + double thickness=1 , linetype=8,shift =0 ,centre_x ,centre_y,radius,r_value,g_value,b_value; + + + //checking input argument + CheckInputArgument(pvApiCtx, 10, 10); + CheckOutputArgument(pvApiCtx, 1, 1) ; + + Mat src; + retrieveImage(src,1); + int n=*getNbInputArgument(pvApiCtx); + + //for value of x coordinate of centre + sciErr = getVarAddressFromPosition(pvApiCtx,2,&piAddr2); + if (sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + intErr = getScalarDouble(pvApiCtx, piAddr2,¢re_x); + if(intErr) + return intErr; + + + //for value of y coordinate of centre + sciErr = getVarAddressFromPosition(pvApiCtx,3,&piAddr3); + if (sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + intErr = getScalarDouble(pvApiCtx, piAddr3,¢re_y); + if(intErr) + return intErr; + + //for value of radius + sciErr = getVarAddressFromPosition(pvApiCtx,4,&piAddr4); + if (sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + intErr = getScalarDouble(pvApiCtx, piAddr4,&radius); + if(intErr) + return intErr; + + //for value of R value of colour + sciErr = getVarAddressFromPosition(pvApiCtx,5,&piAddr5); + if (sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + intErr = getScalarDouble(pvApiCtx, piAddr5 ,&r_value); + if(intErr) + return intErr; + + //for value of G value of colour + sciErr = getVarAddressFromPosition(pvApiCtx,6,&piAddr6); + if (sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + intErr = getScalarDouble(pvApiCtx, piAddr6 ,&g_value); + if(intErr) + return intErr; + + // for B value of colour + sciErr = getVarAddressFromPosition(pvApiCtx,7,&piAddr7); + if (sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + intErr = getScalarDouble(pvApiCtx, piAddr7,&b_value); + if(intErr) + return intErr; + + if(n==8) + { + // for thickness of circle default: 1 + sciErr = getVarAddressFromPosition(pvApiCtx,8,&piAddr8); + if (sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + intErr = getScalarDouble(pvApiCtx, piAddr8,&thickness); + if(intErr) + return intErr; + } + else if(n==9) + { + sciErr = getVarAddressFromPosition(pvApiCtx,8,&piAddr8); + if (sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + intErr = getScalarDouble(pvApiCtx, piAddr8,&thickness); + if(intErr) + return intErr; + //for line type of circle default: 8 + + sciErr = getVarAddressFromPosition(pvApiCtx,9,&piAddr9); + if (sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + + intErr = getScalarDouble(pvApiCtx, piAddr9,&linetype); + if(intErr) + return intErr; + } + else if(n==10) + { sciErr = getVarAddressFromPosition(pvApiCtx,8,&piAddr8); + if (sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + intErr = getScalarDouble(pvApiCtx, piAddr8,&thickness); + if(intErr) + return intErr; + //for line type of circle default: 8 + + sciErr = getVarAddressFromPosition(pvApiCtx,9,&piAddr9); + if (sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + + intErr = getScalarDouble(pvApiCtx, piAddr9,&linetype); + if(intErr) + return intErr; + + // for shift in circle default : 0 + sciErr = getVarAddressFromPosition(pvApiCtx,10,&piAddr10); + if (sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + intErr = getScalarDouble(pvApiCtx, piAddr10,&shift); + if(intErr) + return intErr; + } + + // for shift in circle defulat : 0 + + + // checking radius parameter + if (radius <0) + { + radius=3; + sciprint("Radius should be positive , 3 value was used instead\n"); + } + // checking the parmeters for correct values + if( r_value <0 || r_value >255) + { + r_value=0; + sciprint(" r value of colour should be between 0 and 255 , using 0 instead\n"); + } + if( g_value <0 || g_value >255) + { + g_value=0; + sciprint(" g value of colour should be between 0 and 255 , using 0 instead\n"); + } + if( b_value <0 || b_value >255) + { + b_value=0; + sciprint(" b value of colour should be between 0 and 255 , using 0 instead\n"); + } + if ((linetype!=0) && (linetype!=4)&& (linetype!=8)) + { + linetype=8; + sciprint("Only 0/4/8 allowed , using 8 instead\n"); + } + //temporary pt variable, to use in function as centre + Point pt(centre_x,centre_y); + /// Draw the circles detected + try + { + circle( src, pt, radius, Scalar(r_value,g_value,b_value), thickness, linetype, shift); + } + catch(cv::Exception& e) + { + Scierror(999,e.what()); + } +//// sending the image + + string tempstring = type2str(src.type()); + char *checker; + checker = (char *)malloc(tempstring.size() + 1); + memcpy(checker, tempstring.c_str(), tempstring.size() + 1); + returnImage(checker,src,1); + free(checker); + + //Assigning the list as the Output Variable + AssignOutputVariable(pvApiCtx, 1) = nbInputArgument(pvApiCtx) + 1; + //Returning the Output Variables as arguments to the Scilab environment + ReturnArguments(pvApiCtx); + return 0; + + + } + +} + diff --git a/sci_gateway/cpp/opencv_correctMatches.cpp b/sci_gateway/cpp/opencv_correctMatches.cpp new file mode 100644 index 0000000..744815d --- /dev/null +++ b/sci_gateway/cpp/opencv_correctMatches.cpp @@ -0,0 +1,187 @@ +//Author:- Nihar Rao + + + + +#include +#include +#include "opencv2/core/core.hpp" +#include "opencv2/highgui/highgui.hpp" +#include "opencv2/opencv.hpp" +#include "opencv2/calib3d/calib3d.hpp" +#include +#include +using namespace cv; +using namespace std; +extern "C" +{ + #include "api_scilab.h" + #include "Scierror.h" + #include "BOOL.h" + #include + #include + #include "../common.h" + + + +int opencv_correctMatches(char *fname, unsigned long fname_len) +{ + + SciErr sciErr; + int intErr = 0; + int iRows=0,iCols=0;//for fundamental matrix + int iRows1=0,iCols1=0;//for points1 array + int iRows2=0,iCols2=0;//for points2 array + int *piAddrNew = NULL; + int *piAddr1 = NULL; + int *piAddr2 = NULL; + int *piAddr3 = NULL; + double *points1,*points2,*fundamental_matrix; + int i,j; + double *new1,*new2; + CheckInputArgument(pvApiCtx, 3,3); + CheckOutputArgument(pvApiCtx, 2, 2); + int n=*getNbInputArgument(pvApiCtx);//get number of input arguments + vector Point1,Point2; + + //for fundamental matrix + sciErr = getVarAddressFromPosition(pvApiCtx,1,&piAddr1); + if (sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + sciErr = getMatrixOfDouble(pvApiCtx, piAddr1, &iRows, &iCols, &fundamental_matrix); + if(sciErr.iErr) + { + printError(&sciErr,0); + return 0; + } + Mat F(3, 3, CV_32FC1, &fundamental_matrix); + + if(iRows!=3 || iCols!=3) + { + + Scierror(999, "%s: The entered Fundamental matrix must have dimensions 3*3.\n", fname, 1); + return 0; + + + } + + + //for points1 + sciErr = getVarAddressFromPosition(pvApiCtx,2,&piAddr2); + if (sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + sciErr = getMatrixOfDouble(pvApiCtx, piAddr2, &iRows1, &iCols1, &points1); + if(sciErr.iErr) + { + printError(&sciErr,0); + return 0; + } + + + + //for points2 + sciErr = getVarAddressFromPosition(pvApiCtx,3,&piAddr3); + if (sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + sciErr = getMatrixOfDouble(pvApiCtx, piAddr3, &iRows2, &iCols2, &points2); + if(sciErr.iErr) + { + printError(&sciErr,0); + return 0; + } + if(iCols1 != iCols2) + { + Scierror(999, "There must be the same number of points in both input arrays(points)\n"); + return 0; + } + + for(i=0;i(i,j); + } + } + + + + new2 = (double*) malloc(sizeof(double) * C.cols *2); //both C and D have same dimensions + for(i = 0 ; i < C.cols ; i++) + { + + for(j = 0 ; j < 2 ; j++) + { + new2[i + C.cols * j] = D.at(i,j); + + } + } + //Creating Output Arguments + sciErr = createMatrixOfDouble(pvApiCtx, nbInputArgument(pvApiCtx) + 1, C.cols, 2, new1); + if(sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + sciErr = createMatrixOfDouble(pvApiCtx, nbInputArgument(pvApiCtx) + 2, C.cols,2, new2); + if(sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + + AssignOutputVariable(pvApiCtx, 1) = nbInputArgument(pvApiCtx) + 1; + AssignOutputVariable(pvApiCtx, 2) = nbInputArgument(pvApiCtx) + 2; + ReturnArguments(pvApiCtx); + return 0; + + + + + + + + + + + + + + + + + +} +} diff --git a/sci_gateway/cpp/opencv_cvtColor.cpp b/sci_gateway/cpp/opencv_cvtColor.cpp new file mode 100644 index 0000000..ba26282 --- /dev/null +++ b/sci_gateway/cpp/opencv_cvtColor.cpp @@ -0,0 +1,204 @@ +/******************************************************** + Author: Shubheksha Jalan , Nihar Rao +********************************************************* + void cvtColor(InputArray src, int code, int dstCn=0 ) +********************************************************/ +// number of channels in the destination image; if the parameter is 0, the number of the channels is derived automatically from src and code + + +#include +#include "opencv2/core/core.hpp" +#include "opencv2/highgui/highgui.hpp" +#include "opencv2/opencv.hpp" +#include +using namespace cv; +using namespace std; +extern "C" +{ + #include "api_scilab.h" + #include "Scierror.h" + #include "sciprint.h" + #include "BOOL.h" + #include + #include "../common.h" + + int opencv_cvtColor(char *fname, unsigned long fname_len) + { + + SciErr sciErr; + int intErr; + int iRows=0,iCols=0; + int *piAddr2 = NULL; + int *piAddr3 = NULL; + int *piAddr4 = NULL; + int *piLen = NULL; + double dstCn=0; + int code; + char **codeString = NULL; + int i, j, k,n; + + + //checking input argument + CheckInputArgument(pvApiCtx, 2, 3); + CheckOutputArgument(pvApiCtx, 1,1) ; + + n = *getNbInputArgument(pvApiCtx); + Mat src; + retrieveImage(src,1); + + + sciErr = getVarAddressFromPosition(pvApiCtx, 2, &piAddr2); + if (sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + + + //Now, we will retrieve the string from the input parameter. For this, we will require 3 calls + //first call to retrieve dimensions + sciErr = getMatrixOfString(pvApiCtx, piAddr2, &iRows, &iCols, NULL, NULL); + if(sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + piLen = (int*)malloc(sizeof(int) * iRows * iCols); + //second call to retrieve length of each string + sciErr = getMatrixOfString(pvApiCtx, piAddr2, &iRows, &iCols, piLen, NULL); + if(sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + + codeString = (char**)malloc(sizeof(char*) * iRows * iCols); + for(i = 0 ; i < iRows * iCols ; i++) + codeString[i] = (char*)malloc(sizeof(char) * (piLen[i] + 1));//+ 1 for null termination + + //third call to retrieve data + sciErr = getMatrixOfString(pvApiCtx, piAddr2, &iRows, &iCols, piLen, codeString); + if(sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + if(n==3) + { + sciErr = getVarAddressFromPosition(pvApiCtx, 3, &piAddr3); + if (sciErr.iErr){ + printError(&sciErr, 0); + return 0; + } + intErr = getScalarDouble(pvApiCtx, piAddr3, &dstCn); + if(intErr){ + return intErr; + } + } + + Mat dst; + if(strcmp(codeString[0], "CV_BGR2GRAY") == 0) + code = CV_BGR2GRAY; + else if(strcmp(codeString[0], "CV_RGB2GRAY") == 0) + code = CV_RGB2GRAY; + else if(strcmp(codeString[0], "CV_GRAY2BGR") == 0) + code = CV_GRAY2BGR; + else if(strcmp(codeString[0], "CV_GRAY2RGB") == 0) + code = CV_GRAY2RGB; + else if(strcmp(codeString[0], "CV_BGR2XYZ") == 0) + code = CV_BGR2XYZ; + else if(strcmp(codeString[0], "CV_RGB2XYZ") == 0) + code = CV_RGB2XYZ; + else if(strcmp(codeString[0], "CV_XYZ2BGR") == 0) + code = CV_XYZ2BGR; + else if(strcmp(codeString[0], "CV_XYZ2RGB") == 0) + code = CV_XYZ2RGB; + else if(strcmp(codeString[0], "CV_BGR2YCrCb") == 0) + code = CV_BGR2YCrCb; + else if(strcmp(codeString[0], "CV_RGB2YCrCb") == 0) + code = CV_RGB2YCrCb; + else if(strcmp(codeString[0], "CV_YCrCb2BGR") == 0) + code = CV_YCrCb2BGR; + else if(strcmp(codeString[0], "CV_YCrCb2RGB") == 0) + code = CV_YCrCb2RGB; + else if(strcmp(codeString[0], "CV_BGR2HSV") == 0) + code = CV_BGR2HSV; + else if(strcmp(codeString[0], "CV_RGB2HSV") == 0) + code = CV_RGB2HSV; + else if(strcmp(codeString[0], "CV_HSV2BGR") == 0) + code = CV_HSV2BGR; + else if(strcmp(codeString[0], "CV_HSV2RGB") == 0) + code = CV_HSV2RGB; + else if(strcmp(codeString[0], "CV_BGR2HLS") == 0) + code = CV_BGR2HLS; + else if(strcmp(codeString[0], "CV_RGB2HLS") == 0) + code = CV_RGB2HLS; + else if(strcmp(codeString[0], "CV_HLS2BGR") == 0) + code = CV_HLS2BGR; + else if(strcmp(codeString[0], "CV_HLS2RGB") == 0) + code = CV_HLS2RGB; + else if(strcmp(codeString[0], "CV_BGR2Lab") == 0) + code = CV_BGR2Lab; + else if(strcmp(codeString[0], "CV_RGB2Lab") == 0) + code = CV_RGB2Lab; + else if(strcmp(codeString[0], "CV_Lab2BGR") == 0) + code = CV_Lab2BGR; + else if(strcmp(codeString[0], "CV_Lab2RGB") == 0) + code = CV_Lab2RGB; + else if(strcmp(codeString[0], "CV_BGR2Luv") == 0) + code = CV_BGR2Luv; + else if(strcmp(codeString[0], "CV_RGB2Luv") == 0) + code = CV_RGB2Luv; + else if(strcmp(codeString[0], "CV_Luv2BGR") == 0) + code = CV_Luv2BGR; + else if(strcmp(codeString[0], "CV_Luv2RGB") == 0) + code = CV_Luv2RGB; + else{ + + sciprint("Invalid code"); + return 0; + } + + try + { + + if(src.channels()==3 || src.channels()==4) + src.convertTo(src,CV_8U); + else + src.convertTo(src,CV_8UC3); + cvtColor(src, dst, code, dstCn); + } + catch(cv::Exception& e) + { + + sciprint("%s",e.what()); + return 0; + + + + } + + // namedWindow ("window", 1); + // imshow("window", dst); + // waitKey(0); + // destroyWindow("window"); + + + string tempstring = type2str(dst.type()); + char *checker; + checker = (char *)malloc(tempstring.size() + 1); + memcpy(checker, tempstring.c_str(), tempstring.size() + 1); + returnImage(checker,dst,1); + free(checker); + + + + + //Assigning the list as the Output Variable + AssignOutputVariable(pvApiCtx, 1) = nbInputArgument(pvApiCtx) + 1; + //Returning the Output Variables as arguments to the Scilab environment + ReturnArguments(pvApiCtx); + return 0; +} +/* ==================================================================== */ +} diff --git a/sci_gateway/cpp/opencv_deconvlucy.cpp b/sci_gateway/cpp/opencv_deconvlucy.cpp new file mode 100644 index 0000000..a8fcd44 --- /dev/null +++ b/sci_gateway/cpp/opencv_deconvlucy.cpp @@ -0,0 +1,134 @@ +/******************************************************** +Author: Vinay Bhat +******************************************************** +Usage: return_image = deconvlucy(input_image, PSF) + return_image = deconvlucy(input_image, PSF, no_of_iterations) +********************************************************/ + +#include +#include "opencv2/core/core.hpp" +#include "opencv2/highgui/highgui.hpp" +#include "opencv2/opencv.hpp" +#include +using namespace cv; +using namespace std; +extern "C" +{ + #include "api_scilab.h" + #include "Scierror.h" + #include "BOOL.h" + #include + #include "sciprint.h" + #include "../common.h" + + int opencv_deconvlucy(char *fname, unsigned long fname_len) + { + + SciErr sciErr; + int intErr = 0; + int *piAddr = NULL; + int i; + double h; + + //checking input argument + CheckInputArgument(pvApiCtx, 2, 3); + CheckOutputArgument(pvApiCtx, 1, 1); + + // Get the input image from the Scilab environment + Mat image, psf; + retrieveImage(image, 1); + retrieveImage(psf, 2); + + + // Check if number of arguments are three, + // if so, then the number of iterations is also + // specified. + // If not, then set number of iterations as + // ten. + if (nbInputArgument(pvApiCtx) == 3) + { + // Get the address of the iterations scalar + sciErr = getVarAddressFromPosition(pvApiCtx, 3, &piAddr); + if (sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + + // Get the no. of iterations scalar + intErr = getScalarDouble(pvApiCtx, piAddr, &h); + if(intErr) + { + return intErr; + } + + if (h < 0) + { + sciprint("Please enter a nonnegative scalar for number of iterations.\n"); + return 0; + } + } + else + h = 10; + + + // Check if the input image is grayscale or not, + + + if (image.channels()!=1) + { + sciprint("\nthe first image must be grayscale!\n"); + return 0; + } + + if (psf.channels()!=1) + { + sciprint("\nthe second image must be grayscale!\n"); + return 0; + + } + + + // Apply the Lucy-Richardson method for deblurring + // an image. + Mat convRes, convRes2, temp; + temp = image.clone(); + + try + { + + for (i = 0; i < h; i++) + { + filter2D(temp, convRes, -1, psf); + max((temp - convRes), 0, convRes2); + min((temp + convRes2), 255, convRes); + temp = convRes.clone(); + } + + } + catch(cv::Exception& e) + { + Scierror(999,e.what()); + return 0; + + } + + image = temp.clone(); + + string tempstring = type2str(image.type()); + char *checker; + checker = (char *)malloc(tempstring.size() + 1); + memcpy(checker, tempstring.c_str(), tempstring.size() + 1); + returnImage(checker, image, 1); + free(checker); + + //Assigning the list as the Output Variable + AssignOutputVariable(pvApiCtx, 1) = nbInputArgument(pvApiCtx) + 1; + //Returning the Output Variables as arguments to the Scilab environment + ReturnArguments(pvApiCtx); + return 0; + + } +/* ==================================================================== */ +} + diff --git a/sci_gateway/cpp/opencv_demosaic.cpp b/sci_gateway/cpp/opencv_demosaic.cpp new file mode 100644 index 0000000..2aa3bb2 --- /dev/null +++ b/sci_gateway/cpp/opencv_demosaic.cpp @@ -0,0 +1,152 @@ +/******************************************************** + Author: V Srinivas +********************************************************* + void cvtColor(InputArray src, int code, int dstCn=0 ) +********************************************************/ +//Demosaicing using cvt color filter + +#include +#include "opencv2/core/core.hpp" +#include "opencv2/highgui/highgui.hpp" +#include "opencv2/opencv.hpp" +#include + +using namespace cv; +using namespace std; +extern "C" +{ + #include "api_scilab.h" + #include "Scierror.h" + #include "sciprint.h" + #include "BOOL.h" + #include + #include "../common.h" + + int opencv_demosaic(char *fname, unsigned long fname_len) + { + + SciErr sciErr; + int intErr; + int iRows=0,iCols=0; + int *piAddr2 = NULL; + int *piAddr3 = NULL; + int *piAddr4 = NULL; + int *piLen = NULL; + double dstCn; + int code; + char **codeString = NULL; + int i, j, k; + + //checking input argument + CheckInputArgument(pvApiCtx, 2,2); + CheckOutputArgument(pvApiCtx, 1,1) ; + + + Mat src; + retrieveImage(src,1); + + sciErr = getVarAddressFromPosition(pvApiCtx, 2, &piAddr2); + if (sciErr.iErr) + { + printError(&sciErr, 0); + return -1; + } + + //Now, we will retrieve the string from the input parameter. For this, we will require 3 calls + //first call to retrieve dimensions + sciErr = getMatrixOfString(pvApiCtx, piAddr2, &iRows, &iCols, NULL, NULL); + if(sciErr.iErr) + { + printError(&sciErr, 0); + return -1; + } + piLen = (int*)malloc(sizeof(int) * iRows * iCols); + //second call to retrieve length of each string + sciErr = getMatrixOfString(pvApiCtx, piAddr2, &iRows, &iCols, piLen, NULL); + if(sciErr.iErr) + { + printError(&sciErr, 0); + return -1; + } + + codeString = (char**)malloc(sizeof(char*) * iRows * iCols); + for(i = 0 ; i < iRows * iCols ; i++) + codeString[i] = (char*)malloc(sizeof(char) * (piLen[i] + 1));//+ 1 for null termination + + //third call to retrieve data + sciErr = getMatrixOfString(pvApiCtx, piAddr2, &iRows, &iCols, piLen, codeString); + if(sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + + + + Mat dst; + + if(strcmp(codeString[0], "gbrg") == 0) + code = CV_BayerGR2RGB; + else if(strcmp(codeString[0], "bggr") == 0) + code = CV_BayerRG2RGB; + else if(strcmp(codeString[0], "rggb") == 0) + code = CV_BayerBG2RGB; + else if(strcmp(codeString[0], "grbg") == 0) + code = CV_BayerGB2RGB; + else{ + + sciprint("Invalid Bayer filter code"); + return 0; + } + + try + { + //convert colored image to grayscale + if(src.channels()>=3) + { + + src.convertTo(src,CV_8U); + cvtColor( src, src, CV_BGR2GRAY ); + + + + } + src.convertTo(src,CV_8U); + cvtColor(src, dst, code, 0); + } + catch(cv::Exception& e) + { + + + Scierror(999,e.what()); + return 0; + + + + + } + + // namedWindow ("window", 1); + // imshow("window", dst); + // waitKey(0); + // destroyWindow("window"); + + + string tempstring = type2str(dst.type()); + char *checker; + checker = (char *)malloc(tempstring.size() + 1); + memcpy(checker, tempstring.c_str(), tempstring.size() + 1); + returnImage(checker,dst,1); + free(checker); + + + + + //Assigning the list as the Output Variable + AssignOutputVariable(pvApiCtx, 1) = nbInputArgument(pvApiCtx) + 1; + //Returning the Output Variables as arguments to the Scilab environment + ReturnArguments(pvApiCtx); + return 0; +} +/* ==================================================================== */ +} \ No newline at end of file diff --git a/sci_gateway/cpp/opencv_demosaic.cpp~ b/sci_gateway/cpp/opencv_demosaic.cpp~ new file mode 100644 index 0000000..4c2ee4b --- /dev/null +++ b/sci_gateway/cpp/opencv_demosaic.cpp~ @@ -0,0 +1,127 @@ +/******************************************************** + Author: V Srinivas +********************************************************* + void cvtColor(InputArray src, int code, int dstCn=0 ) +********************************************************/ +//Demosaicing using cvt color filter + +#include +#include "opencv2/core/core.hpp" +#include "opencv2/highgui/highgui.hpp" +#include "opencv2/opencv.hpp" +#include + +using namespace cv; +using namespace std; +extern "C" +{ + #include "api_scilab.h" + #include "Scierror.h" + #include "sciprint.h" + #include "BOOL.h" + #include + #include "../common.h" + + int opencv_demosaic(char *fname, unsigned long fname_len) + { + + SciErr sciErr; + int intErr; + int iRows=0,iCols=0; + int *piAddr2 = NULL; + int *piAddr3 = NULL; + int *piAddr4 = NULL; + int *piLen = NULL; + double dstCn; + int code; + char **codeString = NULL; + int i, j, k; + + //checking input argument + CheckInputArgument(pvApiCtx, 2,2); + CheckOutputArgument(pvApiCtx, 1,1) ; + + + Mat src; + retrieveImage(src,1); + + sciErr = getVarAddressFromPosition(pvApiCtx, 2, &piAddr2); + if (sciErr.iErr) + { + printError(&sciErr, 0); + return -1; + } + + //Now, we will retrieve the string from the input parameter. For this, we will require 3 calls + //first call to retrieve dimensions + sciErr = getMatrixOfString(pvApiCtx, piAddr2, &iRows, &iCols, NULL, NULL); + if(sciErr.iErr) + { + printError(&sciErr, 0); + return -1; + } + piLen = (int*)malloc(sizeof(int) * iRows * iCols); + //second call to retrieve length of each string + sciErr = getMatrixOfString(pvApiCtx, piAddr2, &iRows, &iCols, piLen, NULL); + if(sciErr.iErr) + { + printError(&sciErr, 0); + return -1; + } + + codeString = (char**)malloc(sizeof(char*) * iRows * iCols); + for(i = 0 ; i < iRows * iCols ; i++) + codeString[i] = (char*)malloc(sizeof(char) * (piLen[i] + 1));//+ 1 for null termination + + //third call to retrieve data + sciErr = getMatrixOfString(pvApiCtx, piAddr2, &iRows, &iCols, piLen, codeString); + if(sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + + + + Mat dst; + + if(strcmp(codeString[0], "gbrg") == 0) + code = CV_BayerGR2RGB; + else if(strcmp(codeString[0], "bggr") == 0) + code = CV_BayerRG2RGB; + else if(strcmp(codeString[0], "rggb") == 0) + code = CV_BayerBG2RGB; + else if(strcmp(codeString[0], "grbg") == 0) + code = CV_BayerGB2RGB; + else{ + + sciprint("Invalid Bayer filter code"); + return 0; + } + + cvtColor(src, dst, code, 0); + + // namedWindow ("window", 1); + // imshow("window", dst); + // waitKey(0); + // destroyWindow("window"); + + + string tempstring = type2str(dst.type()); + char *checker; + checker = (char *)malloc(tempstring.size() + 1); + memcpy(checker, tempstring.c_str(), tempstring.size() + 1); + returnImage(checker,dst,1); + free(checker); + + + + + //Assigning the list as the Output Variable + AssignOutputVariable(pvApiCtx, 1) = nbInputArgument(pvApiCtx) + 1; + //Returning the Output Variables as arguments to the Scilab environment + ReturnArguments(pvApiCtx); + return 0; +} +/* ==================================================================== */ +} \ No newline at end of file diff --git a/sci_gateway/cpp/opencv_denoiseColor.cpp b/sci_gateway/cpp/opencv_denoiseColor.cpp new file mode 100644 index 0000000..2348735 --- /dev/null +++ b/sci_gateway/cpp/opencv_denoiseColor.cpp @@ -0,0 +1,140 @@ +/* +This is the .cpp gateway file for the 'denoiseColor' scilab function. + +It includes the following OpenCV functions, belonging to the Photo module of OpenCV 3.0.0 : + +void cv::fastNlMeansDenoisingColored (InputArray src, OutputArray dst, float h = 3,float hColor = 3, int templateWindowSize = 7,int searchWindowSize = 21 ) + + Removes noise from the input image. Also removes colored noise. + +Author : Shubham Lohakare, NITK Surathkal + Ashish Mantosh Barik, NIT Rourkela +*/ + +#include +#include"opencv2/core/core.hpp" +#include"opencv2/highgui/highgui.hpp" +#include"opencv2/opencv.hpp" +#include"opencv2/shape/shape_transformer.hpp" +#include"opencv2/shape.hpp" +#include"opencv2/imgcodecs.hpp" +#include"opencv2/imgproc/imgproc.hpp" +#include"opencv2/features2d/features2d.hpp" +#include"opencv2/core/utility.hpp" +#include +#include +#include + +using namespace cv; +using namespace std; +extern "C" +{ + #include "api_scilab.h" + #include "Scierror.h" + #include "BOOL.h" + #include + #include "sciprint.h" + #include "../common.h" + + int opencv_denoiseColor(char *fname, unsigned long fname_len) + { SciErr sciErr; + int i; + + CheckInputArgument(pvApiCtx ,5 ,5 );//Checking number of Input Arguments + CheckOutputArgument(pvApiCtx, 1, 1);//Checking number of Output Arguments + + Mat src,dst; + + int *piAddr2 = NULL;//Variables for 2nd Input Argument + int intErr2 = 0; + double filterStrength = 0; + + int *piAddr3 = NULL;//Variables for 3rd Input Argument + int intErr3 = 0; + double filterStrengthColor=0; + + int *piAddr4 = NULL;//Variables for 4th Input Argument + int intErr4 = 0; + double templateWindowSize=0; + + int *piAddr5 = NULL;//Variables for 5th Input Argument + int intErr5 = 0; + double searchWindowSize=0; + + + // to get the argument #2 + sciErr = getVarAddressFromPosition( pvApiCtx, 2, &piAddr2); + if(sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + + intErr2 = getScalarDouble(pvApiCtx, piAddr2, &filterStrength); + if(intErr2) + { + return intErr2; + } + + // to get the argument #3 + sciErr = getVarAddressFromPosition( pvApiCtx, 3, &piAddr3); + if(sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + + intErr3 = getScalarDouble(pvApiCtx, piAddr3, &filterStrengthColor); + if(intErr3) + { + return intErr3; + } + + // to get the argument #4 + sciErr = getVarAddressFromPosition( pvApiCtx, 4, &piAddr4); + if(sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + + intErr4 = getScalarDouble(pvApiCtx, piAddr4, &templateWindowSize); + if(intErr4) + { + return intErr4; + } + + // to get the argument #5 + sciErr = getVarAddressFromPosition( pvApiCtx, 5, &piAddr5); + if(sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + + intErr5 = getScalarDouble(pvApiCtx, piAddr5, &searchWindowSize); + if(intErr5) + { + return intErr5; + } + try{ + + retrieveImage(src,1);//Retrieving the input image + src.convertTo(src,CV_8U);//Converting to 8 bit image + fastNlMeansDenoisingColored(src, dst, filterStrength,filterStrengthColor, templateWindowSize, searchWindowSize);//Calling the denoising OpenCV function + } + catch(Exception& e) + { + const char* err = e.what(); + sciprint("%s", err); + } + + string tempstring = type2str(dst.type());//Returning the output to scilab console + char* checker = (char *)malloc(tempstring.size() + 1); + memcpy(checker, tempstring.c_str(), tempstring.size() + 1); + returnImage(checker,dst,1); + AssignOutputVariable(pvApiCtx, 1) = nbInputArgument(pvApiCtx) + 1; + ReturnArguments(pvApiCtx); + } + +} diff --git a/sci_gateway/cpp/opencv_detectGFTTFeatures.cpp b/sci_gateway/cpp/opencv_detectGFTTFeatures.cpp new file mode 100644 index 0000000..6b8b35f --- /dev/null +++ b/sci_gateway/cpp/opencv_detectGFTTFeatures.cpp @@ -0,0 +1,509 @@ +/*************************************************** +Author : Nihar Rao +***************************************************/ +#include +#include +#include +#include +#include +#include "opencv2/core/core.hpp" +#include "opencv2/features2d.hpp" +#include "opencv2/xfeatures2d.hpp" +#include "opencv2/highgui/highgui.hpp" +#include "opencv2/imgproc/imgproc.hpp" + +using namespace cv; +using namespace std; +using namespace cv::xfeatures2d; + + +extern "C" +{ + #include "api_scilab.h" + #include "Scierror.h" + #include "BOOL.h" + #include + #include "sciprint.h" + #include "../common.h" + + int opencv_detectGFTTFeatures(char *fname, unsigned long fname_len) + { + + SciErr sciErr; + int *piAddr = NULL; + int *piAddrVal = NULL; + int argPresence[7]; + for(int i=0;i<7;i++) + argPresence[i]=0; + int val_position; + int iRows = 0; + int iCols = 0; + int *piLen = NULL; + char ** pstData = NULL; + char *currentArg = NULL; + double *ROImat = NULL; + + double MinContrast = 0.2; + double MinQuality = 0.1; + double numBits = 0; + double numFeatures = 0; + double *featureVector = NULL; + +// DECLARING INPUT ARGUMENTS with their default values + + + + bool useHarris=false; + int maxCorners=1000; + double minDistance=1; + double K = 0.04; + double qualityLevel = 0.01; + int blockSize=3; + + + + + +// DECLARING OUTPUT ARGUMENTS + + vector myPoints; + int *LocationList = NULL; + double *LocationData = NULL; + int feature_rows=0; + int feature_cols=0; + + + int size; + +// ARGUMENT CHECK + + CheckInputArgument(pvApiCtx, 1,15); + CheckOutputArgument(pvApiCtx,1,5); + +// RETRIEVING IMAGE + + Mat image; + retrieveImage(image,1); + +// GRAYSCALE VALIDATION + + if(image.channels()!=1) + { + Scierror(999," Feature is not meant for RGB images\n"); + return 0; + } + +// OBTAINING NUMBER OF ARGUMENTS + + int noOfarguments = *getNbInputArgument(pvApiCtx); + +// ARGUMENT COUNT CHECK + + if(noOfarguments%2==0) + { + Scierror(999," Invalid Number Of Arguments\n"); + return 0; + } + +// MULTIPLE ARGUMENT HANDLING + + for(int i=2;iimage.cols || ROImat[1]>image.rows || ROImat[0]+ROImat[2]>image.cols + || ROImat[1]+ROImat[3]>image.rows) + { + Scierror(999,"Please make sure the arguments are within the image range\n"); + return 0; + } + + argPresence[3]=1; + } + else if(strcmp(currentArg,"maxCorners")==0) + { + val_position=i+1; + + + if(argPresence[4]==1) + { + Scierror(999,"Do not enter the same parameter\n"); + return 0; + } + + sciErr = getVarAddressFromPosition(pvApiCtx,val_position,&piAddrVal); + if (sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + + if(!isDoubleType(pvApiCtx, piAddrVal)) + { + Scierror(999," Invalid type for maxCorners\n"); + return 0; + } + double d=0; + + getScalarDouble(pvApiCtx, piAddrVal, &d); + maxCorners=(int)d; + + + + + argPresence[4]=1; + } + else if(strcmp(currentArg,"useHarris")==0) + { + + + val_position=i+1; + + if(argPresence[5]==1) + { + Scierror(999,"Do not enter the same parameter\n"); + return 0; + } + + sciErr = getVarAddressFromPosition(pvApiCtx,val_position,&piAddrVal); + if (sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + + int *r=NULL; + + sciErr = getMatrixOfBoolean(pvApiCtx, piAddrVal, &iRows, &iCols, &r); + if(sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + + + if(r[0]) + useHarris=true; + else + useHarris=false; + argPresence[5]=1; + + + } + else if(strcmp(currentArg,"blockSize")==0) + { + val_position=i+1; + + + if(argPresence[6]==1) + { + Scierror(999,"Do not enter the same parameter\n"); + return 0; + } + + sciErr = getVarAddressFromPosition(pvApiCtx,val_position,&piAddrVal); + if (sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + + if(!isDoubleType(pvApiCtx, piAddrVal)) + { + Scierror(999," Invalid type for blockSize\n"); + return 0; + } + double d=0; + + getScalarDouble(pvApiCtx, piAddrVal, &d); + blockSize=(int)d; + + + + + argPresence[6]=1; + } + else + { + Scierror(999, "Error: \"%s\" Invalid input argument.\n", currentArg); + return 0; + } + + } + + +// DEFAULT ARGUMENTS + + if(argPresence[3]==0) + { + ROImat=(double *)malloc(sizeof(double)*1*4); + ROImat[0]=0; + ROImat[1]=0; + ROImat[2]=image.cols; + ROImat[3]=image.rows; + } + +// CREATING REGION OF INTEREST + + Rect masker(ROImat[0], ROImat[1], ROImat[2], ROImat[3]); + + Mat mask(image.size(), CV_8UC1, Scalar::all(0)); + mask(masker).setTo(Scalar::all(255)); +//KAZE processing + Mat descriptor; + Ptr myobject = cv::GFTTDetector::create(maxCorners,qualityLevel,minDistance,blockSize,useHarris,K); + try + { + image.convertTo(image, CV_8U); + myobject->detect(image,myPoints,mask); + Ptr obj=FREAK::create( true, true, 22.0f, 4 ,std::vector< int >()); + obj->compute(image, myPoints ,descriptor); + numBits = descriptor.size[1]; + numFeatures = descriptor.size[0]; + + featureVector = (double*)malloc(sizeof(double)*descriptor.size[0]*descriptor.size[1]); + for( int i=0; i(i,j)); + } + feature_rows = descriptor.size[0]; + feature_cols = descriptor.size[1]; + } + catch(cv::Exception &e) + { + const char *err = e.what(); + sciprint("%s", err); + return 0; + } + + + + size = myPoints.size(); + + +// LOCATION ----> + + LocationData = (double *)malloc(sizeof(double) * size * 2); + for(int i = 0; i < size; i++) + { + LocationData[i] = myPoints[i].pt.x; + LocationData[i + size] = myPoints[i].pt.y; + } + + +//Creating Output Arguments + sciErr = createMatrixOfDouble(pvApiCtx, nbInputArgument(pvApiCtx) + 1, feature_rows, feature_cols, featureVector); + if(sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + sciErr = createMatrixOfDouble(pvApiCtx, nbInputArgument(pvApiCtx) + 2, 1, 1, &numBits); + if(sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + + sciErr = createMatrixOfDouble(pvApiCtx, nbInputArgument(pvApiCtx) + 3, 1, 1, &numFeatures); + if(sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + sciErr = createMatrixOfDouble(pvApiCtx, nbInputArgument(pvApiCtx) + 4, size, 2, LocationData); + if(sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + + + createScalarInteger32(pvApiCtx,nbInputArgument(pvApiCtx) + 5, size); + +// ASSIGNING ----> + + for(int i=1;i<=5;i++) + { + AssignOutputVariable(pvApiCtx, i) = nbInputArgument(pvApiCtx) + i; + } + + ReturnArguments(pvApiCtx); + } + + +} \ No newline at end of file diff --git a/sci_gateway/cpp/opencv_detectKAZEFeatures.cpp b/sci_gateway/cpp/opencv_detectKAZEFeatures.cpp new file mode 100644 index 0000000..1ab6100 --- /dev/null +++ b/sci_gateway/cpp/opencv_detectKAZEFeatures.cpp @@ -0,0 +1,510 @@ +/*************************************************** +Author : Nihar Rao +***************************************************/ +#include +#include "opencv2/core/core.hpp" +#include "opencv2/highgui/highgui.hpp" +#include "opencv2/opencv.hpp" +#include +using namespace cv; +using namespace std; +extern "C" +{ + #include "api_scilab.h" + #include "Scierror.h" + #include "BOOL.h" + #include + #include "sciprint.h" + #include "../common.h" + + int opencv_detectKAZEFeatures(char *fname, unsigned long fname_len) + { + + SciErr sciErr; + int *piAddr = NULL; + int *piAddrVal = NULL; + int argPresence[7]; + for(int i=0;i<7;i++) + argPresence[i]=0; + int val_position; + int iRows = 0; + int iCols = 0; + int *piLen = NULL; + char ** pstData = NULL; + char *currentArg = NULL; + double *ROImat = NULL; + + double MinContrast = 0.2; + double MinQuality = 0.1; + double numBits = 0; + double numFeatures = 0; + double *featureVector = NULL; + +// DECLARING INPUT ARGUMENTS with their default values + + + bool extended=false; + bool upright=false; + double Threshold=0.001; + double NumOctaves = 4; + double NumLayers = 4; + double diff=0; + int diffusivity=1; + + + +// DECLARING OUTPUT ARGUMENTS + + vector myPoints; + int *LocationList = NULL; + double *LocationData = NULL; + int feature_rows=0; + int feature_cols=0; + + + int size; + +// ARGUMENT CHECK + + CheckInputArgument(pvApiCtx, 1,15); + CheckOutputArgument(pvApiCtx,1,5); + +// RETRIEVING IMAGE + + Mat image; + retrieveImage(image,1); + +// GRAYSCALE VALIDATION + + if(image.channels()!=1) + { + Scierror(999," Feature is not meant for RGB images\n"); + return 0; + } + +// OBTAINING NUMBER OF ARGUMENTS + + int noOfarguments = *getNbInputArgument(pvApiCtx); + +// ARGUMENT COUNT CHECK + + if(noOfarguments%2==0) + { + Scierror(999," Invalid Number Of Arguments\n"); + return 0; + } + +// MULTIPLE ARGUMENT HANDLING + + for(int i=2;iimage.cols || ROImat[1]>image.rows || ROImat[0]+ROImat[2]>image.cols + || ROImat[1]+ROImat[3]>image.rows) + { + Scierror(999,"Please make sure the arguments are within the image range\n"); + return 0; + } + + argPresence[3]=1; + } + else if(strcmp(currentArg,"upright")==0) + { + + sciprint("hey"); + val_position=i+1; + + if(argPresence[4]==1) + { + Scierror(999,"Do not enter the same parameter\n"); + return 0; + } + + sciErr = getVarAddressFromPosition(pvApiCtx,val_position,&piAddrVal); + if (sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + + int *r=NULL; + + sciErr = getMatrixOfBoolean(pvApiCtx, piAddrVal, &iRows, &iCols, &r); + if(sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + + if(r[0]) + upright=true; + else + upright=false; + argPresence[4]=1; + + + } + else if(strcmp(currentArg,"extended")==0) + { + + + val_position=i+1; + + if(argPresence[5]==1) + { + Scierror(999,"Do not enter the same parameter\n"); + return 0; + } + + sciErr = getVarAddressFromPosition(pvApiCtx,val_position,&piAddrVal); + if (sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + + int *r=NULL; + + sciErr = getMatrixOfBoolean(pvApiCtx, piAddrVal, &iRows, &iCols, &r); + if(sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + + + if(r[0]) + extended=true; + else + extended=false; + argPresence[5]=1; + + + } + else if(strcmp(currentArg,"diffusivity")==0) + { + val_position=i+1; + + + if(argPresence[6]==1) + { + Scierror(999,"Do not enter the same parameter\n"); + return 0; + } + + sciErr = getVarAddressFromPosition(pvApiCtx,val_position,&piAddrVal); + if (sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + + if(!isDoubleType(pvApiCtx, piAddrVal)) + { + Scierror(999," Invalid type for diffusivity\n"); + return 0; + } + + getScalarDouble(pvApiCtx, piAddrVal, &diff); + diffusivity=(int)diff; + + if(diffusivity>3 || diffusivity<0) + { + Scierror(999," diffusivity must be [0,3] \n"); + return 0; + + + } + + + argPresence[6]=1; + } + else + { + Scierror(999, "Error: \"%s\" Invalid input argument.\n", currentArg); + return 0; + } + + } + + +// DEFAULT ARGUMENTS + + if(argPresence[3]==0) + { + ROImat=(double *)malloc(sizeof(double)*1*4); + ROImat[0]=0; + ROImat[1]=0; + ROImat[2]=image.cols; + ROImat[3]=image.rows; + } + +// CREATING REGION OF INTEREST + + Rect masker(ROImat[0], ROImat[1], ROImat[2], ROImat[3]); + + Mat mask(image.size(), CV_8UC1, Scalar::all(0)); + mask(masker).setTo(Scalar::all(255)); +//KAZE processing + Mat descriptor; + Ptr myobject = KAZE::create(extended,upright,Threshold,NumOctaves,NumLayers,diffusivity); + try + { + image.convertTo(image, CV_8U); + myobject->detectAndCompute(image,mask,myPoints,descriptor,false); + + + numBits = descriptor.size[1]; + numFeatures = descriptor.size[0]; + + featureVector = (double*)malloc(sizeof(double)*descriptor.size[0]*descriptor.size[1]); + for( int i=0; i(i,j)); + } + feature_rows = descriptor.size[0]; + feature_cols = descriptor.size[1]; + } + catch(cv::Exception &e) + { + const char *err = e.what(); + sciprint("%s", err); + return 0; + } + + + + size = myPoints.size(); + + +// LOCATION ----> + + LocationData = (double *)malloc(sizeof(double) * size * 2); + for(int i = 0; i < size; i++) + { + LocationData[i] = myPoints[i].pt.x; + LocationData[i + size] = myPoints[i].pt.y; + } + + +//Creating Output Arguments + sciErr = createMatrixOfDouble(pvApiCtx, nbInputArgument(pvApiCtx) + 1, feature_rows, feature_cols, featureVector); + if(sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + sciErr = createMatrixOfDouble(pvApiCtx, nbInputArgument(pvApiCtx) + 2, 1, 1, &numBits); + if(sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + + sciErr = createMatrixOfDouble(pvApiCtx, nbInputArgument(pvApiCtx) + 3, 1, 1, &numFeatures); + if(sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + sciErr = createMatrixOfDouble(pvApiCtx, nbInputArgument(pvApiCtx) + 4, size, 2, LocationData); + if(sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + + + createScalarInteger32(pvApiCtx,nbInputArgument(pvApiCtx) + 5, size); + +// ASSIGNING ----> + + for(int i=1;i<=5;i++) + { + AssignOutputVariable(pvApiCtx, i) = nbInputArgument(pvApiCtx) + i; + } + + ReturnArguments(pvApiCtx); + } + + +} \ No newline at end of file diff --git a/sci_gateway/cpp/opencv_detectMSERFeatures.cpp b/sci_gateway/cpp/opencv_detectMSERFeatures.cpp new file mode 100644 index 0000000..38a240e --- /dev/null +++ b/sci_gateway/cpp/opencv_detectMSERFeatures.cpp @@ -0,0 +1,465 @@ +/******************************************************************************************************************************************************************************************************** +* Author: Umang Agrawal and nihar rao * +* Code: detectMSERFeatures.cpp * +* Function Format: [ list_pixels, ......] = detectMSERFeatures( image, Optional Arguments........) * +* Input Arguments: 1. Image (Grayscale or RGB) * +* 2. ThresholdDelta Value: (0:100] Expressed in Percentage * +* 3. RegionAreaRange Value: [ Min_Area , Max_Area ] * +* 4. MaxAreaVariation Value: Scalar Double typical range from 0.25 - 4 * +* 5. ROI Value: [ x_cord , y_cord , width , height ] * +* * +* Output Argument: 1. List Of Pixels stating the Locus of all features detected * +* 2. Count * +* 3. Location: Centroid of each Locus * +* 4. Axes: Major and Minor axis length of ellipse * +* 5. Orientation: Tilt of the elliptical fit * +* * +********************************************************************************************************************************************************************************************************/ + + +#include +#include +#include +#include +#include "opencv2/core/core.hpp" +#include "opencv2/features2d/features2d.hpp" +#include "opencv2/features2d.hpp" +#include "opencv2/xfeatures2d.hpp" +#include "opencv2/highgui/highgui.hpp" +#include "opencv2/imgproc/imgproc.hpp" + +using namespace cv; +using namespace std; + +extern "C" +{ + #include "api_scilab.h" + #include "Scierror.h" + #include "BOOL.h" + #include + #include "sciprint.h" + #include "../common.h" + + int opencv_detectMSERFeatures(char *fname, unsigned long fname_len) + { + //Various Declarations + //Error Variables + SciErr sciErr; + int sca_read; + + //Mat containers for image + Mat image; + Mat cropped; + + //Address of Various Arguments + int *piAddr = NULL; + int *piAddr2 = NULL; + int *piAddr3 = NULL; + + int inp_params, out_params; //Count of Parameters + double arg_val; //Memory for Scalar Argument Value + int Rows, Cols; //Rows and Columns for Matrix Argument Value + double *roi_arg = NULL; //Memory for Matrix Argument Value + int *pilen = NULL; //For String Matrix Reading: Length of String + char **arg = NULL; //For String Matrix Reading: String + int count_area = 0, count_tres = 0, count_var = 0, count_roi = 0; //Count of all the optional Arguments + double x = 0, y = 0, width = 0, height = 0; //Initials of all Cropped Varaibles + + int i,j; //Iterator + + int delta = 5, min_area = 60, max_area = 14400, max_evolution = 200, edge_blur_size = 5; //Arguments of MSER function with default values + double max_variation = 0.25, min_diversity = 0.2, area_threshold = 1.01, min_margin = 0.003; //Arguments of MSER function with default values + + double *pixellist = NULL; //Output Argument Pixellist + int count[1] ; //Output Argument Count + double *location = NULL; //Output Argument Location + double *axes = NULL; //Output Argument Axes + double *orientation = NULL; //Output Argument Orientation + + vector< vector > mser_points; //3D vector for storing the locus of each detected feature + vector< RotatedRect > regions; + vector bboxes; //RotatedRect vector for storing each region associated with a feature + + CheckInputArgument(pvApiCtx, 1, 9); //Check on Number of Input Arguments + CheckOutputArgument(pvApiCtx, 1, 5); //Check on Number of Output Arguments + + //Read Image + retrieveImage(image, 1); + + + //Getting Number of Input Arguments + inp_params = *getNbInputArgument(pvApiCtx); + + //Based on the number of Input Arguments, alter the arguments of the MSER funtion. + for(i=2; i<=inp_params; i++) + { + if( inp_params == 2 || inp_params == 4 || inp_params == 6 || inp_params == 8) + { + Scierror(999,"Either Argument Name or its Value missing\n"); + return 0; + } + //Reading the Name of the Argument + sciErr = getVarAddressFromPosition(pvApiCtx, i, &piAddr2); + if(sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + //Check for Argument type + if( !isStringType(pvApiCtx, piAddr2)) + { + Scierror(999, "%s: Wrong type of argument #%d. A string is expected.\n", fname, 1); + return 0; + } + //Matrix of Stings + sciErr = getMatrixOfString(pvApiCtx, piAddr2, &Rows, &Cols, NULL, NULL); + if(sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + pilen = (int*)malloc(sizeof(int) * Rows * Cols); + //second call to retrieve the length of the string + sciErr = getMatrixOfString(pvApiCtx, piAddr2, &Rows, &Cols, pilen, NULL); + if(sciErr.iErr) + { + printError(&sciErr, 0); + free(pilen); + return 0; + } + arg = (char**)malloc(sizeof(char*) * Rows * Cols); + for(int j=0;j< Rows * Cols; j++) + { + arg[j] = (char*)malloc(sizeof(char) * (pilen[j] + 1)); + } + + //third call to retrieve data + sciErr = getMatrixOfString(pvApiCtx, piAddr2, &Rows, &Cols, pilen, arg); + if(sciErr.iErr) + { + printError(&sciErr, 0); + free(pilen); + free(arg); + return 0; + } + + if(strcmp(arg[0],"ThresholdDelta") == 0) + { + if(count_tres == 0) + { + sciErr = getVarAddressFromPosition(pvApiCtx, i+1, &piAddr3); + if(sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + //Checking the type of value + if( !isDoubleType(pvApiCtx, piAddr3)) + { + Scierror(999,"Not a valid type of value.\n"); + return 0; + } + //Reading the Value of the argument + sca_read = getScalarDouble(pvApiCtx, piAddr3, &arg_val); + if(sca_read) + { + Scierror(999,"Not a valid value.\n"); + return 0; + } + //Check for valid range + if(arg_val <= 0 && arg_val > 100) + { + Scierror(999,"Not a valid range.Should be between 0 and 100.\n"); + return 0; + } + delta = arg_val; + i++; + count_tres += 1; + } + else + { + Scierror(999,"ThresholdDelta has been specified twice.Check the Arguments\n"); + return 0; + } + } + else if(strcmp(arg[0],"RegionAreaRange") == 0) + { + if(count_area == 0) + { + sciErr = getVarAddressFromPosition(pvApiCtx, i+1, &piAddr3); + if(sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + //Checking the type of argument + if( !(isDoubleType(pvApiCtx, piAddr3) || isIntegerType(pvApiCtx, piAddr3)) ) + { + Scierror(999,"Not a valid type of value.\n"); + return 0; + } + //Reading the Value of the argument + sciErr = getMatrixOfDouble(pvApiCtx, piAddr3, &Rows, &Cols, &roi_arg); + if(sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + if( Rows*Cols != 2 ) + { + Scierror(999,"Only 2 values are expected.Neither less nor more\n"); + return 0; + } + if( roi_arg[0] >= roi_arg[1] ) + { + Scierror(999,"Max Area should be greater than Min Area\n"); + return 0; + } + //Assigning the elements of the list to their proper function + min_area = roi_arg[0]; + max_area = roi_arg[1]; + i++; + count_area += 1; + } + else + { + Scierror(999,"RegionAreaRange has been specified twice.Check the Arguments\n"); + return 0; + } + } + else if(strcmp(arg[0],"MaxAreaVariation") == 0) + { + if(count_var == 0) + { + sciErr = getVarAddressFromPosition(pvApiCtx, i+1, &piAddr3); + if(sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + //Checking the type of value + if( !isDoubleType(pvApiCtx, piAddr3)) + { + Scierror(999,"Not a valid type of value.\n"); + return 0; + } + //Reading the Value of the argument + sca_read = getScalarDouble(pvApiCtx, piAddr3, &arg_val); + if(sca_read) + { + Scierror(999,"Not a valid value.\n"); + return 0; + } + max_variation = arg_val; + i++; + count_var += 1; + } + else + { + Scierror(999,"MaxAreaVariation has been specified twice.Check the Arguments\n"); + return 0; + } + } + else if(strcmp(arg[0],"ROI") == 0) + { + if(count_roi == 0) + { + sciErr = getVarAddressFromPosition(pvApiCtx, i+1, &piAddr3); + if(sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + //Checking the type of argument + if( !(isDoubleType(pvApiCtx, piAddr3) || isIntegerType(pvApiCtx, piAddr3)) ) + { + Scierror(999,"Not a valid type of value.\n"); + return 0; + } + //Reading the Value of the argument + sciErr = getMatrixOfDouble(pvApiCtx, piAddr3, &Rows, &Cols, &roi_arg); + if(sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + if( Rows*Cols != 4 ) + { + Scierror(999,"Expected 4 arguments in format [x,y,width,height]\n"); + return 0; + } + //Assigning the elements of the list to their proper function + x = roi_arg[0]; + y = roi_arg[1]; + width = roi_arg[2]; + height = roi_arg[3]; + if(x>=image.cols || y>=image.rows || x<0 || y<0) + { + sciprint("Invalid x or y value\n"); + return 0; + } + if(width<=0 || height<=0 || x+width > image.cols || y+height > image.rows) + { + sciprint("Invalid width or height value\n"); + return 0; + } + Rect myROI(x, y, width, height); + Mat croppedRef(image, myROI); + croppedRef.copyTo(cropped); + i++; //Incrementing iterator to count for the value argument read + count_roi += 1; //Indicating ROI has been called once + } + else + { + Scierror(999,"ROI has been specified twice.Check the Arguments\n"); + return 0; + } + } + else + { + Scierror(999,"Invalid Argument\n"); + return 0; + } + } + try + { + image.convertTo(image,CV_8UC3); + //Creating an MSER class Object with specified conditions + + Ptr img_ms = cv:: + MSER::create(delta, min_area, max_area, max_variation, min_diversity, max_evolution, area_threshold, min_margin, edge_blur_size); + + //Checking if have to operate on original image or cropped one + // 1st Argument: Image on which MSER features has to be detected + // 2nd Argument: Locus of all the points detected + // 3rd Argument: Mask of empty Mat container + if(count_roi == 0) + img_ms->detectRegions( image, mser_points,bboxes); + else + img_ms->detectRegions( cropped, mser_points,bboxes); + + // Extracting Regions from the mser_points locus and approximating them to an elliptic fit + for(i=0; i= regions[i].size.height ) + { + axes[i] = regions[i].size.width; //Axis: Major Axis of Ellipse + axes[mser_points.size() + i] = regions[i].size.height; //Axis: Minor Axis of Ellipse + } + else + { + axes[i] = regions[i].size.height; //Axis: Major Axis of Ellipse + axes[mser_points.size() + i] = regions[i].size.width; //Axis: Minor Axis of Ellipse + } + orientation[i] = regions[i].angle; //Orientation + } + + //Reading the number of output Arguments user demands + + //Assigning Pixel_List + + out_params = *getNbOutputArgument(pvApiCtx); + if( out_params >= 1 ) + { + sciErr = createList(pvApiCtx, nbInputArgument(pvApiCtx) + 1, mser_points.size(), &piAddr); + if(sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + for(i = 0; i= 2 ) + { + sciErr = createMatrixOfInteger32(pvApiCtx, nbInputArgument(pvApiCtx) + 2, 1, 1, count); + if(sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + AssignOutputVariable(pvApiCtx, 2) = nbInputArgument(pvApiCtx) + 2; + } + + //Assigning Location + if( out_params >= 3 ) + { + sciErr = createMatrixOfDouble(pvApiCtx, nbInputArgument(pvApiCtx) + 3, mser_points.size(), 2, location); + if(sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + AssignOutputVariable(pvApiCtx, 3) = nbInputArgument(pvApiCtx) + 3; + } + + //Assigning Axes + if( out_params >= 4 ) + { + sciErr = createMatrixOfDouble(pvApiCtx, nbInputArgument(pvApiCtx) + 4, mser_points.size(), 2, axes); + if(sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + AssignOutputVariable(pvApiCtx, 4) = nbInputArgument(pvApiCtx) + 4; + } + + //Assigning Orientation + if( out_params == 5 ) + { + sciErr = createMatrixOfDouble(pvApiCtx, nbInputArgument(pvApiCtx) + 5, mser_points.size(), 1, orientation); + if(sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + AssignOutputVariable(pvApiCtx, 5) = nbInputArgument(pvApiCtx) + 5; + } + + //Releasing all the memory Captured + free(location); + free(axes); + free(orientation); + + //Returning the Output Arguments + ReturnArguments(pvApiCtx); + return 0; + } +} \ No newline at end of file diff --git a/sci_gateway/cpp/opencv_detectMinEigenFeatures.cpp b/sci_gateway/cpp/opencv_detectMinEigenFeatures.cpp new file mode 100644 index 0000000..a1de682 --- /dev/null +++ b/sci_gateway/cpp/opencv_detectMinEigenFeatures.cpp @@ -0,0 +1,367 @@ +/*************************************************** +Author : Rohit Suri +***************************************************/ +#include +#include +#include "opencv2/core/core.hpp" +#include "opencv2/highgui/highgui.hpp" +#include "opencv2/opencv.hpp" +#include "opencv2/imgproc/imgproc.hpp" +#include +#include +using namespace cv; +using namespace std; +extern "C" +{ + #include "api_scilab.h" + #include "Scierror.h" + #include "BOOL.h" + #include + #include "sciprint.h" + #include "../common.h" + + + int opencv_detectMinEigenFeatures(char *fname, unsigned long fname_len) + { + // Error management variables + SciErr sciErr; + int intErr; + + //------Local variables------// + int *location = NULL; + double *metric = NULL; + int *piAddr = NULL; + int *piLen = NULL; + int nbInputArguments; + char **pstData = NULL; + char *currentArg = NULL; + bool *providedArgs = NULL; + double *matrixOfRoi; // ROI[xStart, yStart, width, height] + int iRows, iCols; + Mat sourceImage, dst, dstThresholded, ucharDstThresholded, extended; + vector > contours; + double filterSize = 5, minQuality = 0.01, blockSize = 2, maxDst, localMax; + bool *included = NULL; + int pointCount = 0, localMaxPos; + double tempForSwapping; + int coordinateMin, coordinatePos; + + //------Check number of parameters------// + CheckInputArgument(pvApiCtx, 1, 7); + CheckOutputArgument(pvApiCtx, 1, 3); + + //------Get input arguments------// + retrieveImage(sourceImage, 1); + sourceImage.convertTo(sourceImage,CV_8U); + if(sourceImage.channels() != 1) + { + Scierror(999, "The input image is not a grayscale image."); + return 0; + } + matrixOfRoi = (double*) malloc(sizeof(double) * 4); + providedArgs = (bool*) malloc(sizeof(bool) * 3); + memset(providedArgs, 0, 3); + matrixOfRoi[0] = 0; + matrixOfRoi[1] = 0; + matrixOfRoi[2] = sourceImage.cols; + matrixOfRoi[3] = sourceImage.rows; + nbInputArguments = *getNbInputArgument(pvApiCtx); + + // The following loop is for checking if optional arguments have been provided + for(int iter=2; iter <= nbInputArguments; iter++) + { + // Getting address of next argument + sciErr = getVarAddressFromPosition(pvApiCtx, iter, &piAddr); + if (sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + + // Extracting name of next argument takes three calls to getMatrixOfString + sciErr = getMatrixOfString(pvApiCtx, piAddr, &iRows, &iCols, NULL, NULL); + if (sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + + piLen = (int*) malloc(sizeof(int) * iRows * iCols); + + sciErr = getMatrixOfString(pvApiCtx, piAddr, &iRows, &iCols, piLen, NULL); + if (sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + + pstData = (char**) malloc(sizeof(char*) * iRows * iCols); + for(int iterPstData = 0; iterPstData < iRows * iCols; iterPstData++) + { + pstData[iterPstData] = (char*) malloc(sizeof(char) * piLen[iterPstData] + 1); + } + + sciErr = getMatrixOfString(pvApiCtx, piAddr, &iRows, &iCols, piLen, pstData); + if (sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + + currentArg = pstData[0]; + // providedArgs[] makes sure that no optional argument is provided more than once + if(strcmp(currentArg, "MinQuality")==0) + { + if(iter+1<=nbInputArguments && !providedArgs[0]) + { + sciErr = getVarAddressFromPosition(pvApiCtx, ++iter, &piAddr); + if (sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + intErr = getScalarDouble(pvApiCtx, piAddr, &minQuality); + if(intErr) + { + return intErr; + } + // Checking if values are in proper range. Same for all optional arguments + if(minQuality < 0 || minQuality > 1) + { + Scierror(999, "Error: Please provide proper value for \"%s\". Permissible range is [0, 1].\n", currentArg); + return 0; + } + providedArgs[0] = 1; + } + else if(providedArgs[0]) // Send an error message if an argument is provided more than once. Same for all optional arguments. + { + Scierror(999, "Please provide optional arguments only once.\n"); + return 0; + } + else // Send an error message if name of argument is given but type is incorrect. Same for all optional arguments. + { + Scierror(999, "Incorrect number of arguments provided. Please check the documentation for more information.\n"); + return 0; + } + } + else if(strcmp(currentArg, "FilterSize")==0) + { + if(iter+1 <= nbInputArguments && !providedArgs[1]) + { + sciErr = getVarAddressFromPosition(pvApiCtx, ++iter, &piAddr); + if (sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + intErr = getScalarDouble(pvApiCtx, piAddr, &filterSize); + if(intErr) + { + return intErr; + } + providedArgs[1] = 1; + if(filterSize!=1 && filterSize!=3 && filterSize!=5 && filterSize!=7) + { + Scierror(999, "Error: Please provide proper value for \"%s\". Permissible values are {1, 3, 5, 7}.\n", currentArg); + return 0; + } + } + else if(providedArgs[1]) + { + Scierror(999, "Please provide optional arguments only once.\n"); + return 0; + } + else + { + Scierror(999, "Incorrect number of arguments provided. Please check the documentation for more information.\n"); + return 0; + } + } + else if(strcmp(currentArg, "ROI")==0) + { + if(iter+1 <= nbInputArguments && !providedArgs[2]) + { + sciErr = getVarAddressFromPosition(pvApiCtx, ++iter, &piAddr); + if (sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + if(!isDoubleType(pvApiCtx, piAddr) || isVarComplex(pvApiCtx, piAddr)) + { + Scierror(999, "%s: Wrong type for input argument #%d: A real matrix expected.\n", fname, iter); + return 0; + } + sciErr = getMatrixOfDouble(pvApiCtx, piAddr, &iRows, &iCols, &matrixOfRoi); + if(sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + if(iRows!=1 || iCols!=4) + { + Scierror(999, "Incorrect dimension of matrix for argument ROI.\n"); + return 0; + } + providedArgs[2] = 1; + if(matrixOfRoi[0] < 0 || matrixOfRoi[0] > sourceImage.cols || matrixOfRoi[1] < 0 || + matrixOfRoi[1] > sourceImage.cols || matrixOfRoi[2] < 0 || matrixOfRoi[0] + matrixOfRoi[2] > sourceImage.cols + || matrixOfRoi[3] < 0 || matrixOfRoi[1] + matrixOfRoi[3] > sourceImage.rows) + { + Scierror(999, "Error: Please provide proper values for \"%s\".\n", currentArg); + return 0; + } + } + else if(providedArgs[2]) + { + Scierror(999, "Please provide optional arguments only once.\n"); + return 0; + } + else + { + Scierror(999, "Incorrect number of arguments provided. Please check the documentation for more information.\n"); + return 0; + } + } + else + { + Scierror(999, "Error: \"%s\" name for input argument is not valid.\n", currentArg); + return 0; + } + } + try + { + //------Actual processing------// + cornerMinEigenVal(sourceImage(Rect(matrixOfRoi[0], matrixOfRoi[1], matrixOfRoi[2], matrixOfRoi[3])), dst, blockSize, filterSize, BORDER_DEFAULT); + + // Finding the maximum value at a pixel in dst + maxDst = 0; + for(int rowIter=0; rowIter < dst.rows; rowIter++) + { + for(int colIter=0; colIter < dst.cols; colIter++) + { + if(dst.at(rowIter, colIter) > maxDst) + { + maxDst = dst.at(rowIter, colIter); + } + } + } + + /* First, we threshold dst according to the minQuality expected by the user. + We then find contours in the thresholded image and check each pixel's value + to compute the local maxima. A extended mat is created because contours + having edges on the boundaries of the images are not considered by + findContours */ + threshold(dst, dstThresholded, maxDst*minQuality, 255, THRESH_BINARY); + dstThresholded.convertTo(ucharDstThresholded, CV_8UC1); + extended = Mat(dst.rows+2, dst.cols+2, CV_8UC1); + for(int rowIter = 0; rowIter < extended.rows; rowIter++) + { + for(int colIter = 0; colIter < extended.cols; colIter++) + { + if(rowIter == 0 || rowIter == extended.rows - 1 + || colIter == 0 || colIter == extended.cols - 1) + { + extended.at(rowIter, colIter) = 0; + } + else + { + extended.at(rowIter, colIter) = ucharDstThresholded.at(rowIter-1, colIter-1); + } + } + } + + findContours(extended, contours, CV_RETR_TREE, CV_CHAIN_APPROX_NONE); + pointCount = contours.size(); + location = (int*) malloc(sizeof(int) * pointCount * 2); + metric = (double*) malloc(sizeof(double)*pointCount); + for(int rowIter = 0; rowIter < contours.size(); rowIter++) + { + localMax = 0; + localMaxPos = 0; + for(int colIter=0; colIter(contours[rowIter][colIter].y-1, contours[rowIter][colIter].x-1)>localMax) + { + localMax = dst.at(contours[rowIter][colIter].y-1, contours[rowIter][colIter].x-1); + localMaxPos = colIter; + } + } + if(localMax > maxDst*minQuality) + { + location[rowIter] = contours[rowIter][localMaxPos].x-1 + matrixOfRoi[0]; + location[pointCount + rowIter] = contours[rowIter][localMaxPos].y-1 + matrixOfRoi[1]; + metric[rowIter] = dst.at(location[pointCount + rowIter], location[rowIter]); + } + } + } + catch(cv::Exception& e) + { + const char* err=e.what(); + sciprint("\n%s\n",err); + + + } + // To return coordinates in order + for(int iter1 = 0; iter1 < pointCount - 1; iter1++) + { + coordinateMin = location[iter1]; + coordinatePos = iter1; + for(int iter2 = iter1 + 1; iter2 < pointCount; iter2++) + { + if(location[iter2] < coordinateMin) + { + coordinateMin = location[iter2]; + coordinatePos = iter2; + } + else if(location[iter2] == coordinateMin) + { + if(location[pointCount + iter2] < location[pointCount + coordinatePos]) + { + coordinateMin = location[iter2]; + coordinatePos = iter2; + } + } + } + // Swapping x coordinate + tempForSwapping = location[coordinatePos]; + location[coordinatePos] = location[iter1]; + location[iter1] = tempForSwapping; + // Swapping y coordinate + tempForSwapping = location[pointCount + coordinatePos]; + location[pointCount + coordinatePos] = location[pointCount + iter1]; + location[pointCount + iter1] = tempForSwapping; + // Swapping metric + tempForSwapping = metric[coordinatePos]; + metric[coordinatePos] = metric[iter1]; + metric[iter1] = tempForSwapping; + } + //------Create output arguments------// + sciErr = createMatrixOfInteger32(pvApiCtx, nbInputArgument(pvApiCtx)+1, pointCount, 2, location); + if(sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + sciErr = createMatrixOfDouble(pvApiCtx, nbInputArgument(pvApiCtx)+2, pointCount, 1, metric); + if(sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + sciErr = createMatrixOfInteger32(pvApiCtx, nbInputArgument(pvApiCtx)+3, 1, 1, &pointCount); + if(sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + + //------Return Arguments------// + AssignOutputVariable(pvApiCtx, 1) = nbInputArgument(pvApiCtx)+1; + AssignOutputVariable(pvApiCtx, 2) = nbInputArgument(pvApiCtx)+2; + AssignOutputVariable(pvApiCtx, 3) = nbInputArgument(pvApiCtx)+3; + ReturnArguments(pvApiCtx); + return 0; + } +/* ==================================================================== */ +} \ No newline at end of file diff --git a/sci_gateway/cpp/opencv_ellipse.cpp b/sci_gateway/cpp/opencv_ellipse.cpp new file mode 100644 index 0000000..db9a284 --- /dev/null +++ b/sci_gateway/cpp/opencv_ellipse.cpp @@ -0,0 +1,324 @@ +/******************************************************** + Author: Sukul Bagai +********************************************************* + return_image = ellipse(input_image , x_coordinate_of_centre , y_coordinate_centre , first_axis, second_axis, angle, startAngle, endAngle, r_value,g_value,b_value,thickness,linetype,shift); +********************************************************/ + +#include +#include "opencv2/core/core.hpp" +#include "opencv2/highgui/highgui.hpp" +#include "opencv2/opencv.hpp" +#include +using namespace cv; +using namespace std; +extern "C" +{ + #include "api_scilab.h" + #include "Scierror.h" + #include "BOOL.h" + #include + #include + #include "../common.h" + + int opencv_ellipse(char *fname, unsigned long fname_len) + { + + SciErr sciErr; + int intErr=0; + int iRows=0,iCols=0; + int *piAddrNew = NULL; + int *piAddr2 = NULL; + int *piAddr3 = NULL; + int *piAddr4 = NULL; + int *piAddr5 = NULL; + int *piAddr6 = NULL; + int *piAddr7 = NULL; + int *piAddr8 = NULL; + int *piAddr9 = NULL; + int *piAddr10 = NULL; + int *piAddr11 = NULL; + int *piAddr12 = NULL; + int *piAddr13 = NULL; + int *piAddr14 = NULL; + int i,j,k; + double thickness=1 , linetype=8, shift=0 ,centre_x ,centre_y,first_axis,second_axis,angle,startAngle,endAngle,r_value,g_value,b_value; + + //checking input argument + CheckInputArgument(pvApiCtx, 11, 14); + CheckOutputArgument(pvApiCtx, 1, 1) ; + //get number of input arguments + int n=*getNbInputArgument(pvApiCtx); + Mat src; + retrieveImage(src,1); + + //for value of x coordinate of centre + sciErr = getVarAddressFromPosition(pvApiCtx,2,&piAddr2); + if (sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + intErr = getScalarDouble(pvApiCtx, piAddr2,¢re_x); + if(intErr) + return intErr; + + + //for value of y coordinate of centre + sciErr = getVarAddressFromPosition(pvApiCtx,3,&piAddr3); + if (sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + intErr = getScalarDouble(pvApiCtx, piAddr3,¢re_y); + if(intErr) + return intErr; + + //for value of first_axis + sciErr = getVarAddressFromPosition(pvApiCtx,4,&piAddr4); + if (sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + intErr = getScalarDouble(pvApiCtx, piAddr4,&first_axis); + if(intErr) + return intErr; + + //for value of second_axis + sciErr = getVarAddressFromPosition(pvApiCtx,5,&piAddr5); + if (sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + intErr = getScalarDouble(pvApiCtx, piAddr5,&first_axis); + if(intErr) + return intErr; + + //for value of angle + sciErr = getVarAddressFromPosition(pvApiCtx,6,&piAddr6); + if (sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + intErr = getScalarDouble(pvApiCtx, piAddr6,&angle); + if(intErr) + return intErr; + + //for value of startAngle + sciErr = getVarAddressFromPosition(pvApiCtx,7,&piAddr7); + if (sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + intErr = getScalarDouble(pvApiCtx, piAddr7,&startAngle); + if(intErr) + return intErr; + + //for value of endAngle + sciErr = getVarAddressFromPosition(pvApiCtx,8,&piAddr8); + if (sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + intErr = getScalarDouble(pvApiCtx, piAddr8,&endAngle); + if(intErr) + return intErr; + + //for value of R value of colour + sciErr = getVarAddressFromPosition(pvApiCtx,9,&piAddr9); + if (sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + intErr = getScalarDouble(pvApiCtx, piAddr9 ,&r_value); + if(intErr) + return intErr; + + //for value of G value of colour + sciErr = getVarAddressFromPosition(pvApiCtx,10,&piAddr10); + if (sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + intErr = getScalarDouble(pvApiCtx, piAddr10 ,&g_value); + if(intErr) + return intErr; + + // for B value of colour + sciErr = getVarAddressFromPosition(pvApiCtx,11,&piAddr11); + if (sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + intErr = getScalarDouble(pvApiCtx, piAddr11,&b_value); + if(intErr) + return intErr; + if(n==12) + { + // for thickness of circle default: 1 + sciErr = getVarAddressFromPosition(pvApiCtx,12,&piAddr12); + if (sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + intErr = getScalarDouble(pvApiCtx, piAddr12,&thickness); + if(intErr) + return intErr; + } + else if(n==13) + { + sciErr = getVarAddressFromPosition(pvApiCtx,12,&piAddr12); + if (sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + intErr = getScalarDouble(pvApiCtx, piAddr12,&thickness); + if(intErr) + return intErr; + //for line type of circle default: 8 + + sciErr = getVarAddressFromPosition(pvApiCtx,13,&piAddr13); + if (sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + + intErr = getScalarDouble(pvApiCtx, piAddr13,&linetype); + if(intErr) + return intErr; + } + else if(n==14) + { sciErr = getVarAddressFromPosition(pvApiCtx,12,&piAddr12); + if (sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + intErr = getScalarDouble(pvApiCtx, piAddr12,&thickness); + if(intErr) + return intErr; + //for line type of circle default: 8 + + sciErr = getVarAddressFromPosition(pvApiCtx,13,&piAddr13); + if (sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + + intErr = getScalarDouble(pvApiCtx, piAddr13,&linetype); + if(intErr) + return intErr; + + // for shift in circle default : 0 + sciErr = getVarAddressFromPosition(pvApiCtx,14,&piAddr14); + if (sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + intErr = getScalarDouble(pvApiCtx, piAddr14,&shift); + if(intErr) + return intErr; + } + // checking radius parameter + if (first_axis < 0) + { + first_axis=3; + sciprint("first_axis should be positive , 3 value was used instead\n"); + } + if (second_axis < 0) + { + second_axis=3; + sciprint("second_axis should be positive , 3 value was used instead\n"); + } + if (first_axis < second_axis) + { + double temp; + temp=first_axis; + first_axis=second_axis; + second_axis=temp; + sciprint("first_axis should be greater than second_axis. Values swapped.\n"); + } + if(angle < 0 || angle > 360) + { + angle=45; + sciprint("Imvalid angle value used. Using 45 instead"); + } + if(startAngle < 0 || startAngle > 360) + { + startAngle=45; + sciprint("Imvalid startAngle value used. Using 120 instead"); + } + if(endAngle < 0 || endAngle > 360) + { + endAngle=45; + sciprint("Imvalid endAngle value used. Using 120 instead"); + } + // checking the parmeters for correct values + if( r_value <0 || r_value >255) + { + r_value=0; + sciprint(" r value of colour should be between 0 and 255 , using 0 instead\n"); + } + if( g_value <0 || g_value >255) + { + g_value=0; + sciprint(" g value of colour should be between 0 and 255 , using 0 instead\n"); + } + if( b_value <0 || b_value >255) + { + b_value=0; + sciprint(" b value of colour should be between 0 and 255 , using 0 instead\n"); + } + if ((linetype!=0) && (linetype!=4)&& (linetype!=8)) + { + linetype=8; + sciprint("Only 0/4/8 allowed , using 8 instead\n"); + } + //temporary pt variable, to use in function as centre + Point pt(centre_x,centre_y); + Size sz(first_axis,second_axis); + /// Draw the circles detected + try + { + ellipse( src, pt, sz, angle, startAngle, endAngle, Scalar(r_value,g_value,b_value), thickness, linetype, shift); + } + catch(cv::Exception& e) + { + + Scierror(999,e.what()); + + + + } +//// sending the image + string tempstring = type2str(src.type()); + char *checker; + checker = (char *)malloc(tempstring.size() + 1); + memcpy(checker, tempstring.c_str(), tempstring.size() + 1); + returnImage(checker,src,1); + free(checker); + + //Assigning the list as the Output Variable + AssignOutputVariable(pvApiCtx, 1) = nbInputArgument(pvApiCtx) + 1; + //Returning the Output Variables as arguments to the Scilab environment + ReturnArguments(pvApiCtx); + return 0; + + + } + +} + diff --git a/sci_gateway/cpp/opencv_erode.cpp b/sci_gateway/cpp/opencv_erode.cpp new file mode 100644 index 0000000..2876c3b --- /dev/null +++ b/sci_gateway/cpp/opencv_erode.cpp @@ -0,0 +1,124 @@ +#include +#include "opencv2/core/core.hpp" +#include "opencv2/highgui/highgui.hpp" +#include "opencv2/opencv.hpp" +#include +#include +using namespace cv; +using namespace std; +extern "C" +{ + #include "api_scilab.h" + #include "Scierror.h" + #include "BOOL.h" + #include + #include + #include "../common.h" + + int opencv_erode(char *fname, unsigned long fname_len) + { + + SciErr sciErr; + int intErr = 0; + int iRows=0,iCols=0; + int *piLen = NULL; + int *piAddr = NULL; + int *piAddrNew = NULL; + int *piAddr2 = NULL; + int *piAddr3 = NULL; + int *piAddr4 = NULL; + int *piAddr5 = NULL; + char **type = NULL; + int i,j,k; + double anchorX,anchorY,iterations; + double *kernel; + + //checking input argument + CheckInputArgument(pvApiCtx, 5, 5); + CheckOutputArgument(pvApiCtx, 1, 1) ; + + Mat image; + retrieveImage(image,1); + + //for kernel + sciErr = getVarAddressFromPosition(pvApiCtx,2,&piAddr2); + if (sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + sciErr = getMatrixOfDouble(pvApiCtx, piAddr2, &iRows, &iCols, &kernel); + if(sciErr.iErr) + { + printError(&sciErr,0); + return 0; + } + + double actualkernel[iRows][iCols]; + for(i=0;i +#include "opencv2/core/core.hpp" +#include "opencv2/highgui/highgui.hpp" +#include "opencv2/opencv.hpp" +#include "opencv2/imgproc/imgproc.hpp" +#include "opencv2/calib3d/calib3d.hpp" +#include +using namespace cv; +using namespace std; +extern "C" +{ + #include "api_scilab.h" + #include "Scierror.h" + #include "BOOL.h" + #include + #include + #include "../common.h" + + int opencv_estimateFundamentalMat(char *fname, unsigned long fname_len) + { + + SciErr sciErr; + int intErr=0; + int iComplex = 0; + int iType = 0; + int *piAddr = NULL; + int *piLen = NULL; + int iRows,iCols; + int iA1Rows=0,iA1Cols=0,iA2Rows=0,iA2Cols=0; + int method=FM_RANSAC; + int nbInputArguments,iter,i,j; + char **pstData = NULL; + char *currentArg = NULL; + bool *providedArgs = NULL; + double* pdblReal = NULL; + double *iArray1=NULL,*iArray2=NULL; + double param1=3,param2=0.99; + + vector point1,point2; + + CheckInputArgument(pvApiCtx, 2, 8); + CheckOutputArgument(pvApiCtx, 1, 1) ; + + nbInputArguments = *getNbInputArgument(pvApiCtx); + providedArgs = (bool*) malloc(sizeof(bool) * 3); + + + sciErr = getVarAddressFromPosition(pvApiCtx, 1, &piAddr); + if(sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + sciErr = getVarType(pvApiCtx, piAddr, &iType); + if(sciErr.iErr || iType != sci_matrix) + { + printError(&sciErr, 0); + return 0; + } + //Get complexity + iComplex = isVarComplex(pvApiCtx, piAddr); + //Check complexity + if(iComplex) + { + Scierror(999, "%s: Wrong type for input argument: A complex number is not expected.\n"); + return 0; + } + + sciErr = getMatrixOfDouble(pvApiCtx, piAddr, &iA1Rows, &iA1Cols, &iArray1); + if(sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + + + sciErr = getVarAddressFromPosition(pvApiCtx, 2, &piAddr); + if(sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + sciErr = getVarType(pvApiCtx, piAddr, &iType); + if(sciErr.iErr || iType != sci_matrix) + { + printError(&sciErr, 0); + return 0; + } + //Get complexity + iComplex = isVarComplex(pvApiCtx, piAddr); + //Check complexity + if(iComplex) + { + Scierror(999, "%s: Wrong type for input argument: A complex number is not expected.\n"); + return 0; + } + + sciErr = getMatrixOfDouble(pvApiCtx, piAddr, &iA2Rows, &iA2Cols, &iArray2); + if(sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + if(iA1Rows != iA2Rows) + { + Scierror(999, "There must be the same number of points in both input arrays\n"); + return 0; + } + + for(i=0;i(i,j); + } + } + sciErr = createMatrixOfDouble(pvApiCtx, nbInputArgument(pvApiCtx) + 1, fm.rows , 3, pdblReal); + if(sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + AssignOutputVariable(pvApiCtx, 1) = nbInputArgument(pvApiCtx) + 1; + ReturnArguments(pvApiCtx); + return 0; + } +} diff --git a/sci_gateway/cpp/opencv_extractFeatures.cpp b/sci_gateway/cpp/opencv_extractFeatures.cpp new file mode 100644 index 0000000..d47cf88 --- /dev/null +++ b/sci_gateway/cpp/opencv_extractFeatures.cpp @@ -0,0 +1,1775 @@ +#include +#include +#include +#include +#include +#include "opencv2/core/core.hpp" +#include "opencv2/features2d.hpp" +#include "opencv2/xfeatures2d.hpp" +#include "opencv2/highgui/highgui.hpp" +#include "opencv2/imgproc/imgproc.hpp" + +using namespace cv; +using namespace std; +using namespace cv::xfeatures2d; + +extern "C" +{ + #include "api_scilab.h" + #include "Scierror.h" + #include "BOOL.h" + #include + #include "sciprint.h" + #include "../common.h" + + /*string type2str(int type) + { + string r; + uchar depth = type & CV_MAT_DEPTH_MASK; + uchar chans = 1 + (type >> CV_CN_SHIFT); + switch ( depth ) + { + case CV_8U: r = "8U"; break; + case CV_8S: r = "8S"; break; + case CV_16U: r = "16U"; break; + case CV_16S: r = "16S"; break; + case CV_32S: r = "32S"; break; + case CV_32F: r = "32F"; break; + case CV_64F: r = "64F"; break; + default: r = "User"; break; + } + r += "C"; + r += (chans+'0'); + return r; + }*/ + + int opencv_extractFeatures(char *fname, unsigned long fname_len) + { + //...................................................................................................................................................................................... + //Declarations + // Error Handling + SciErr sciErr; + + // Address of Various Scilab API + int *piAddr1 = NULL; + int *piAddr2 = NULL; + int *piAddr3 = NULL; + int *piAddr4 = NULL; + + // Number of input and output Arguments + int inputArguments = 0; + int out_params; + + // Matrix Reading Argument + int iPrec = 0; + int noItemInList = 0; + int iRows,iCols; + int Rows, Cols; + int *pilen = NULL; + char **arg = NULL; + char **method = NULL; + char **clas = NULL; + int length_M = 0; + + // Necessary Output Arguments + double *valid_points = NULL; + double numBits = 0; + double numFeatures = 0; + double *featureVector = NULL; + + // Count of various Arguments + int count_method=0, count_block=0, count_surf=0, count_upright=0 ,count_metric=0; + int count_orient=0, count_scale=0, count_axes=0, count_sign=0, count_class=0; + + // Iterator + int i; + + //Input Arguments Parameters + double *metric = NULL; + double *orient = NULL; + double *axes = NULL; + double *scale = NULL; + double *sign = NULL; + double block_size = 0; + double upright = 0; + double surf_size = 64; + + // Keypoint Vector + vector keypoints; + vector copy_k; + + //Image Container + Mat image; + + //Output Argument + int feature_rows, feature_cols; + int valid_rows; + double count; + double *metric_o = NULL; + double *scale_o = NULL; + double *orientation_o = NULL; + double *axes_o = NULL; + double *sign_o = NULL; + + + // Checks on Number of Input and Output Arguments + CheckInputArgument(pvApiCtx, 4, 22); + CheckOutputArgument(pvApiCtx, 2, 9); + + + inputArguments = *getNbInputArgument(pvApiCtx); + + //....................................................................................................................................................................................... + //Checking for the Presence of Valid Number of Arguments + if( inputArguments%2 == 0) + { + + //Argument 1 - Image + sciErr = getVarAddressFromPosition(pvApiCtx, 1, &piAddr1); + if(sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + if(isListType(pvApiCtx, piAddr1)) + { + sciErr = getListItemNumber(pvApiCtx, piAddr1, &noItemInList); + if( noItemInList != 1) + { + Scierror(999,"Expecting a grayscale image as first Argument\n"); + return 0; + } + retrieveImage(image, 1); + } + else + { + if( !isDoubleType(pvApiCtx, piAddr1)) + { + Scierror(999,"Expecting a grayscale Image as first Argument\n"); + return 0; + } + retrieveImage(image, 1); + } + + + //.............................................................................................................................................................................. + //Argument 2 - Location Co-ordinates + sciErr = getVarAddressFromPosition(pvApiCtx, 2, &piAddr2); + if(sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + if( !isVarMatrixType(pvApiCtx, piAddr2)) + { + Scierror(999,"Expecting a Matrix of Mx2 order depicting the Location Coordinates as 2nd Argument.\n"); + return 0; + } + //Checking the type of location coordinates + if(isDoubleType(pvApiCtx, piAddr2)) + { + //for double location co-ordinates + double *points = NULL; + sciErr = getMatrixOfDouble(pvApiCtx, piAddr2, &iRows, &iCols, &points); + if(sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + length_M = iRows; + KeyPoint *X = new KeyPoint; + for(int i=0; ipt = Point2f(points[i],points[iRows+i]); + X->size = 7; + keypoints.push_back(*X); + copy_k.push_back(*X); + } + } + else if(isIntegerType(pvApiCtx, piAddr2)) + { + sciErr = getMatrixOfIntegerPrecision(pvApiCtx, piAddr2, &iPrec); + if(sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + switch(iPrec) + { + case SCI_UINT8: //for unsigned integer 8 location co-ordinates + { + unsigned char *points = NULL; + sciErr = getMatrixOfUnsignedInteger8(pvApiCtx, piAddr2, &iRows, &iCols, &points); + if(sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + length_M = iRows; + KeyPoint *X = new KeyPoint; + for(int i=0; ipt = Point2f(points[i],points[iRows+i]); + X->size = 7; + keypoints.push_back(*X); + copy_k.push_back(*X); + } + break; + } + case SCI_UINT16: //for unsigned integer 16 location co-ordinates + { + unsigned short *points = NULL; + sciErr = getMatrixOfUnsignedInteger16(pvApiCtx, piAddr2, &iRows, &iCols, &points); + if(sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + length_M = iRows; + KeyPoint *X = new KeyPoint; + for(int i=0; ipt = Point2f(points[i],points[iRows+i]); + X->size = 7; + keypoints.push_back(*X); + copy_k.push_back(*X); + } + break; + } + case SCI_INT32: + { + int *points = NULL; + sciErr = getMatrixOfInteger32(pvApiCtx, piAddr2, &iRows, &iCols, &points); + if(sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + length_M = iRows; + KeyPoint *X = new KeyPoint; + for(int i=0; ipt = Point2f(points[i],points[iRows+i]); + X->size = 7; + keypoints.push_back(*X); + copy_k.push_back(*X); + } + break; + } + } + } + else + { + Scierror(999,"Expecting a Double or an Integer Matrix as Location Coordinates in 2nd Argument.\n"); + return 0; + } + + + //............................................................................................................................................................................. + //Argument 3 - Class + sciErr = getVarAddressFromPosition(pvApiCtx, 3, &piAddr3); + if(sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + //Check for Argument type + if( !isStringType(pvApiCtx, piAddr3)) + { + Scierror(999,"Expecting String Argument \"Class\" as Argument 3.\n"); + return 0; + } + //Matrix of Stings + sciErr = getMatrixOfString(pvApiCtx, piAddr3, &Rows, &Cols, NULL, NULL); + if(sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + pilen = (int*)malloc(sizeof(int) * Rows * Cols); + //second call to retrieve the length of the string + sciErr = getMatrixOfString(pvApiCtx, piAddr3, &Rows, &Cols, pilen, NULL); + if(sciErr.iErr) + { + printError(&sciErr, 0); + free(pilen); + return 0; + } + arg = (char**)malloc(sizeof(char*) * Rows * Cols); + for(int j=0;j< Rows * Cols; j++) + { + arg[j] = (char*)malloc(sizeof(char) * (pilen[j] + 1)); + } + //third call to retrieve data + sciErr = getMatrixOfString(pvApiCtx, piAddr3, &Rows, &Cols, pilen, arg); + if(sciErr.iErr) + { + printError(&sciErr, 0); + free(pilen); + free(arg); + return 0; + } + + //Checking Whether Argument 3 is Method or not + if(strcmp(arg[0],"Class") == 0) + { + //If method extracting the Value of the Argument + if(count_class != 0) + { + Scierror(999,"Class Argument has been called twice\n"); + return 0; + } + free(arg); + free(pilen); + sciErr = getVarAddressFromPosition(pvApiCtx, 4, &piAddr4); + if(sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + //Check for Argument type + if( !isStringType(pvApiCtx, piAddr4)) + { + Scierror(999, "%s: Wrong type of 2nd argument #%d. A string is expected.\n", fname, 1); + return 0; + } + //Matrix of Stings + sciErr = getMatrixOfString(pvApiCtx, piAddr4, &Rows, &Cols, NULL, NULL); + if(sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + pilen = (int*)malloc(sizeof(int) * Rows * Cols); + //second call to retrieve the length of the string + sciErr = getMatrixOfString(pvApiCtx, piAddr4, &Rows, &Cols, pilen, NULL); + if(sciErr.iErr) + { + printError(&sciErr, 0); + free(pilen); + return 0; + } + clas = (char**)malloc(sizeof(char*) * Rows * Cols); + for(int j=0;j< Rows*Cols; j++) + { + clas[j] = (char*)malloc(sizeof(char) * (pilen[j] + 1)); + } + //third call to retrieve data + sciErr = getMatrixOfString(pvApiCtx, piAddr4, &Rows, &Cols, pilen, clas); + if(sciErr.iErr) + { + printError(&sciErr, 0); + free(pilen); + free(clas); + return 0; + } + count_class += 1; + } + else + { + Scierror(999,"Expecting \"Class\" as the 3rd Argument\n"); + return 0; + } + } + else + { + Scierror(999,"Required Arguments are Missing\n"); + return 0; + } + + //.......................................................................................................................................................................................... + //Getting Optional Input Arguments + for( i=5; i<= inputArguments; i++) + { + + + + + + sciErr = getVarAddressFromPosition(pvApiCtx, i, &piAddr3); + if(sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + //Check for Argument type + if( !isStringType(pvApiCtx, piAddr3)) + { + Scierror(999, "%s: Wrong type of argument #%d. A string is expected.\n", fname, 1); + return 0; + } + //Matrix of Stings + sciErr = getMatrixOfString(pvApiCtx, piAddr3, &Rows, &Cols, NULL, NULL); + if(sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + pilen = (int*)malloc(sizeof(int) * Rows * Cols); + //second call to retrieve the length of the string + sciErr = getMatrixOfString(pvApiCtx, piAddr3, &Rows, &Cols, pilen, NULL); + if(sciErr.iErr) + { + printError(&sciErr, 0); + free(pilen); + return 0; + } + arg = (char**)malloc(sizeof(char*) * Rows * Cols); + for(int j=0;j< Rows * Cols; j++) + { + arg[j] = (char*)malloc(sizeof(char) * (pilen[j] + 1)); + } + //third call to retrieve data + sciErr = getMatrixOfString(pvApiCtx, piAddr3, &Rows, &Cols, pilen, arg); + if(sciErr.iErr) + { + printError(&sciErr, 0); + free(pilen); + free(arg); + return 0; + } + + + + //................................................................................................................................................................................. + //Reading the Value of Optional Arguments + //If Optional Argument is Method + if(strcmp(arg[0],"Method") == 0) + { + if(count_method!= 0) + { + Scierror(999,"Method Argument has been called twice\n"); + return 0; + } + free(arg); + free(pilen); + sciErr = getVarAddressFromPosition(pvApiCtx, i+1, &piAddr4); + if(sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + //Check for Argument type + if( !isStringType(pvApiCtx, piAddr4)) + { + Scierror(999, "%s: Wrong type of 2nd argument #%d. A string is expected.\n", fname, 1); + return 0; + } + //Matrix of Stings + sciErr = getMatrixOfString(pvApiCtx, piAddr4, &Rows, &Cols, NULL, NULL); + if(sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + pilen = (int*)malloc(sizeof(int) * Rows * Cols); + //second call to retrieve the length of the string + sciErr = getMatrixOfString(pvApiCtx, piAddr4, &Rows, &Cols, pilen, NULL); + if(sciErr.iErr) + { + printError(&sciErr, 0); + free(pilen); + return 0; + } + method = (char**)malloc(sizeof(char*) * Rows * Cols); + for(int j=0;j< Rows*Cols; j++) + { + method[j] = (char*)malloc(sizeof(char) * (pilen[j] + 1)); + } + //third call to retrieve data + sciErr = getMatrixOfString(pvApiCtx, piAddr4, &Rows, &Cols, pilen, method); + if(sciErr.iErr) + { + printError(&sciErr, 0); + free(pilen); + free(method); + return 0; + } + + i++; + + count_method += 1; + } + //................................................................................................................................................................................. + //If Optional Argument is Metric + else if(strcmp(arg[0],"Metric") == 0) + { + if(count_metric != 0) + { + Scierror(999,"Metric Argument has been called twice\n"); + return 0; + } + free(arg); + free(pilen); + sciErr = getVarAddressFromPosition(pvApiCtx, i+1, &piAddr4); + if(sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + //Check for Argument type + if( !isVarMatrixType(pvApiCtx, piAddr4)) + { + Scierror(999,"Expecting a Matrix of Mx1 order depicting the Metric Values as Value of Metric Argument.\n"); + return 0; + } + sciErr = getMatrixOfDouble(pvApiCtx, piAddr4, &iRows, &iCols, &metric); + if(sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + if( iCols != 1) + { + Scierror(999,"Expecting a single Column Metric Matrix\n"); + return 0; + } + if( iRows != length_M) + { + Scierror(999,"Expecting a M Row matrix having M number of elements corresponding to M rows of location coordinates\n"); + return 0; + } + i++; + count_metric += 1; + } + //................................................................................................................................................................................. + //If Optional Argument is BlockSize + else if(strcmp(arg[0],"blockSize") == 0) + { + if(count_block != 0) + { + Scierror(999,"BlockSize has been called twice\n"); + return 0; + } + free(arg); + free(pilen); + sciErr = getVarAddressFromPosition(pvApiCtx, i+1, &piAddr4); + if(sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + //Check for Argument type + if( !(isDoubleType(pvApiCtx, piAddr4)) ) + { + Scierror(999,"BlockSize Value should be an odd Integer\n"); + return 0; + } + if(getScalarDouble(pvApiCtx, piAddr4, &block_size)) + { + Scierror(999,"Cannot Read Block Size Value"); + return 0; + } + if(int(block_size)%2 == 0) + { + Scierror(999,"Expecting a odd value for Block Size"); + return 0; + } + + i++; + count_block += 1; + } + //................................................................................................................................................................................. + //If Optional Argument is Upright + else if(strcmp(arg[0],"upright") == 0) + { + if(count_upright != 0) + { + Scierror(999,"Upright Argument has been called twice\n"); + return 0; + } + free(arg); + free(pilen); + sciErr = getVarAddressFromPosition(pvApiCtx, i+1, &piAddr4); + if(sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + //Check for Argument type + if( !(isDoubleType(pvApiCtx, piAddr4)) ) + { + Scierror(999,"Upright Value must be a logic scalar\n"); + return 0; + } + if(getScalarDouble(pvApiCtx, piAddr4, &upright)) + { + Scierror(999,"Cannot Read Upright Value\n"); + return 0; + } + i++; + count_upright += 1; + } + //................................................................................................................................................................................. + //If Optional Argument is SURFSize + else if(strcmp(arg[0],"surfSize") == 0) + { + + if(count_surf != 0) + { + Scierror(999,"SURFSize Argument has been called twice\n"); + return 0; + } + free(arg); + free(pilen); + sciErr = getVarAddressFromPosition(pvApiCtx, i+1, &piAddr4); + if(sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + //Check for Argument type + if( !(isDoubleType(pvApiCtx, piAddr4)) ) + { + Scierror(999,"Surf Size Value should be an Integer\n"); + return 0; + } + if(getScalarDouble(pvApiCtx, piAddr4, &surf_size)) + { + Scierror(999,"Cannot Read Surf Size Value"); + return 0; + } + if( int(surf_size) != 64 && int(surf_size) !=128 ) + { + Scierror(999,"Expecting value 64 or 128 for Surf Size\n"); + return 0; + } + + i++; + count_surf += 1; + } + //................................................................................................................................................................................. + //If Optional Argument is Orientation + else if(strcmp(arg[0],"Orientation") == 0) + { + if(count_orient != 0) + { + Scierror(999,"Orientation Argument has been called twice\n"); + return 0; + } + free(arg); + free(pilen); + sciErr = getVarAddressFromPosition(pvApiCtx, i+1, &piAddr4); + if(sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + //Check for Argument type + if( !isVarMatrixType(pvApiCtx, piAddr4)) + { + Scierror(999,"Expecting a Matrix of Mx1 order depicting the Orientation Values as Value of Orientation Argument.\n"); + return 0; + } + sciErr = getMatrixOfDouble(pvApiCtx, piAddr4, &iRows, &iCols, &orient); + if(sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + if( iCols != 1) + { + Scierror(999,"Expecting a single Column Orientation Matrix\n"); + return 0; + } + if( iRows != length_M) + { + Scierror(999,"Expecting a M Row matrix having M number of elements corresponding to M rows of location coordinates\n"); + return 0; + } + i++; + count_orient += 1; + } + //................................................................................................................................................................................. + //If Optional Argument is Axes + else if(strcmp(arg[0],"Axes") == 0) + { + if(count_axes != 0) + { + Scierror(999,"Axes Argument has been called twice\n"); + return 0; + } + free(arg); + free(pilen); + sciErr = getVarAddressFromPosition(pvApiCtx, i+1, &piAddr4); + if(sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + //Check for Argument type + if( !isVarMatrixType(pvApiCtx, piAddr4)) + { + Scierror(999,"Expecting a Matrix of Mx2 order depicting the Axes as Value of Axes Argument.\n"); + return 0; + } + sciErr = getMatrixOfDouble(pvApiCtx, piAddr4, &iRows, &iCols, &axes); + if(sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + if( iCols != 2) + { + Scierror(999,"Expecting a 2 Column Axes Matrix\n"); + return 0; + } + if( iRows != length_M) + { + Scierror(999,"Expecting a M Row matrix having M number of elements corresponding to M rows of location coordinates\n"); + return 0; + } + i++; + count_axes += 1; + } + //................................................................................................................................................................................ + //If Optional Argument is Scale + else if(strcmp(arg[0],"Scale") == 0) + { + if(count_scale != 0) + { + Scierror(999,"Scale Argument has been called twice\n"); + return 0; + } + free(arg); + free(pilen); + sciErr = getVarAddressFromPosition(pvApiCtx, i+1, &piAddr4); + if(sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + //Check for Argument type + if( !isVarMatrixType(pvApiCtx, piAddr4)) + { + Scierror(999,"Expecting a Matrix of Mx1 order depicting the Scale as Value of Scale Argument.\n"); + return 0; + } + sciErr = getMatrixOfDouble(pvApiCtx, piAddr4, &iRows, &iCols, &scale); + if(sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + if( iCols != 1) + { + Scierror(999,"Expecting a single Column Scale Matrix\n"); + return 0; + } + if( iRows != length_M) + { + Scierror(999,"Expecting a M Row matrix having M number of elements corresponding to M rows of location coordinates\n"); + return 0; + } + i++; + count_scale += 1; + } + //................................................................................................................................................................................ + //If Optional Argument is SignOfLaplacian + else if(strcmp(arg[0],"SignOfLaplacian") == 0) + { + + if(count_sign != 0) + { + Scierror(999,"SignOfLaplacian Argument has been called twice\n"); + return 0; + } + free(arg); + free(pilen); + + sciErr = getVarAddressFromPosition(pvApiCtx, i+1, &piAddr4); + if(sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + //Check for Argument type + + if( !isVarMatrixType(pvApiCtx, piAddr4)) + { + Scierror(999,"Expecting a Matrix of Mx1 order depicting the Sign Of Laplacian as Value of SignOfLaplacian Argument.\n"); + return 0; + } + + sciErr = getMatrixOfDouble(pvApiCtx, piAddr4, &iRows, &iCols, &sign); + + if(sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + + if( iCols != 1) + { + Scierror(999,"Expecting a single Column Axes Matrix\n"); + return 0; + } + + if( iRows != length_M) + { + Scierror(999,"Expecting a M Row matrix having M number of elements corresponding to M rows of location coordinates\n"); + return 0; + } + i++; + count_sign += 1; + + //Check for Validity of Laplacian Matrix + for(int i=0; i obj=FREAK::create( true, true, 22.0f, 4 ,std::vector< int >()); + image.convertTo(image,CV_8U); + obj->compute(image, keypoints, descriptor); + numBits = descriptor.size[1]; + numFeatures = descriptor.size[0]; + + valid_points = (double *)malloc(sizeof(double) * keypoints.size() * 2); + + for( int i=0; i(i,j)); + } + feature_rows = descriptor.size[0]; + feature_cols = descriptor.size[1]; + valid_rows = descriptor.size[0]; + count = descriptor.size[0]; + } + catch(cv::Exception& e) + { + const char* err=e.what(); + sciprint("\n%s\n",err); + } + if( strcmp(clas[0],"cornerPoints") == 0) + { + try + { + metric_o = (double*)malloc(sizeof(double) * valid_rows); + int iterator = 0; + for(int i=0; i obj; + if( int(upright) == 1) + { + if( int(surf_size) == 64) + obj = SURF::create(100, 4, 3, 0, 1); + else if ( int(surf_size) == 128) + obj = SURF::create(100, 4, 3, 1, 1); + } + else if( int(upright) == 0) + { + if( int(surf_size) == 64) + obj = SURF::create(100, 4, 3, 0, 0); + else if ( int(surf_size) == 128) + obj = SURF::create(100, 4, 3, 1, 0); + } + + image.convertTo(image,CV_8U); + obj->compute(image, keypoints, descriptor); + + numBits = descriptor.size[1]; + numFeatures = descriptor.size[0]; + + valid_points = (double *)malloc(sizeof(double) * keypoints.size() * 2); + + for( int i=0; i(i,j)); + } + feature_rows = descriptor.size[0]; + feature_cols = descriptor.size[1]; + valid_rows = descriptor.size[0]; + count = descriptor.size[0]; + } + catch(cv::Exception& e) + { + const char* err=e.what(); + sciprint("\n%s\n",err); + + + } + if( strcmp(clas[0],"cornerPoints") == 0) + { + metric_o = (double*)malloc(sizeof(double) * valid_rows); + int iterator = 0; + for(int i=0; i(i,j)); + } + feature_rows = descriptor.size[0]; + feature_cols = descriptor.size[1]; + valid_rows = descriptor.size[0]; + count = descriptor.size[0]; + + if( strcmp(clas[0],"cornerPoints") == 0) + { + metric_o = (double*)malloc(sizeof(double) * valid_rows); + int iterator = 0; + for(int i=0; i valid; + for( i=0; i image.cols || keypoints[i].pt.y + (block_size-1)/2 > image.rows) + continue; + valid.push_back(keypoints[i]); + } + valid_points = (double *)malloc(sizeof(double)*valid.size()*2); + featureVector = (double *)malloc(sizeof(double)*valid.size()*int(block_size)*int(block_size)); + for( int i=0; i(j,k); + iterator = iterator+1; + } + } + feature_rows = valid.size(); + feature_cols = int(block_size)*int(block_size); + valid_rows = valid.size(); + numFeatures = valid.size(); + numBits = int(block_size)*int(block_size); + count = valid.size(); + + if( strcmp(clas[0],"cornerPoints") == 0) + { + metric_o = (double*)malloc(sizeof(double) * valid_rows); + int iterator = 0; + for(int i=0; i &h, int templateWindowSize=7, int searchWindowSize=21, int normType=NORM_L1) +void cv::fastNlMeansDenoising (InputArray src, OutputArray dst, const std::vector &h, int templateWindowSize=7, int searchWindowSize=21, int normType=NORM_L2) + + Removes noise from the input image. The noise is expected to be gaussian white noise. + +Author : Shubham Lohakare, NITK Surathkal + Ashish Manatosh Barik, NIT Rourkela +*/ + + +#include +#include"opencv2/core/core.hpp" +#include"opencv2/highgui/highgui.hpp" +#include"opencv2/opencv.hpp" +#include"opencv2/shape/shape_transformer.hpp" +#include"opencv2/shape.hpp" +#include"opencv2/imgcodecs.hpp" +#include"opencv2/imgproc/imgproc.hpp" +#include"opencv2/features2d/features2d.hpp" +#include"opencv2/core/utility.hpp" +#include +#include +#include +#include"opencv2/core/cuda.hpp" +using namespace cv; +using namespace std; +using namespace cv::cuda; +extern "C" +{ + #include "api_scilab.h" + #include "Scierror.h" + #include "BOOL.h" + #include + #include "sciprint.h" + #include "../common.h" + + int opencv_fastNlMeansDenoising(char *fname, unsigned long fname_len) + { + SciErr sciErr; + int i; + + CheckInputArgument(pvApiCtx ,5 ,5 );//Checking number of Input Arguments + CheckOutputArgument(pvApiCtx, 1, 1);//Checking number of Output Arguments + + int *piAddr2 = NULL;//Variables for 2nd Input Argument + int intErr2 = 0; + double filterStrength = 0; + + int *piAddr3 = NULL;//Variables for 3rd Input Argument + int intErr3 = 0; + double templateWindowSize=0; + + int *piAddr4 = NULL;//Variables for 4th Input Argument + int intErr4 = 0; + double searchWindowSize=0; + + int *piAddr5 = NULL;//Variables for 5th Input Argument + int intErr5 = 0; + double choice=0; + + + Mat src,dst; + retrieveImage(src,1);//Retrieving the image + src.convertTo(src,CV_8U);//Converting the image to 8bit image + + // to get the argument #2 + sciErr = getVarAddressFromPosition( pvApiCtx, 2, &piAddr2); + if(sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + + intErr2 = getScalarDouble(pvApiCtx, piAddr2, &filterStrength); + if(intErr2) + { + return intErr2; + } + + // to get the argument #3 + sciErr = getVarAddressFromPosition( pvApiCtx, 3, &piAddr3); + if(sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + + intErr3 = getScalarDouble(pvApiCtx, piAddr3, &templateWindowSize); + if(intErr3) + { + return intErr3; + } + + // to get the argument #4 + sciErr = getVarAddressFromPosition( pvApiCtx, 4, &piAddr4); + if(sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + + intErr4 = getScalarDouble(pvApiCtx, piAddr4, &searchWindowSize); + if(intErr4) + { + return intErr4; + } + // to get the argument #5 + sciErr = getVarAddressFromPosition( pvApiCtx, 5, &piAddr5); + if(sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + + intErr5 = getScalarDouble(pvApiCtx, piAddr5, &choice); + if(intErr5) + { + return intErr5; + } + + //Stream stream = Null(); + + try{ + + /*if(choice==1) + fastNlMeansDenoising(src, dst, filterStrength, searchWindowSize, templateWindowSize, stream );//Calling the denoising OpenCV function*/ + + if(choice==1) + fastNlMeansDenoising(src, dst, filterStrength, templateWindowSize, searchWindowSize );//Calling the fastNlDenoising OpenCV function + + else if(choice==2) + { + vector h; + h.push_back(filterStrength); + fastNlMeansDenoising(src, dst, h, templateWindowSize, searchWindowSize, NORM_L1 );//Calling the fastNlDenoising OpenCV function with NORM_L1 + } + + else if(choice==3) + { + vector h; + h.push_back(filterStrength); + fastNlMeansDenoising(src, dst, h, templateWindowSize, searchWindowSize, NORM_L2 );//Calling the fastNlDenoising OpenCV function with NORM_l2 + } + + else + sciprint("INVALID INPUT for choice. Enter 1\n2\n3\nor 4\n");//If wrong input is given + } + catch(Exception& e) + { + const char* err=e.what(); + sciprint("%s",err); + } + + + string tempstring = type2str(dst.type());//Returning the image to Scilab console + char* checker = (char *)malloc(tempstring.size() + 1); + memcpy(checker, tempstring.c_str(), tempstring.size() + 1); + returnImage(checker,dst,1); + AssignOutputVariable(pvApiCtx, 1) = nbInputArgument(pvApiCtx) + 1; + ReturnArguments(pvApiCtx); + } + +} diff --git a/sci_gateway/cpp/opencv_findContours.cpp b/sci_gateway/cpp/opencv_findContours.cpp new file mode 100644 index 0000000..785a587 --- /dev/null +++ b/sci_gateway/cpp/opencv_findContours.cpp @@ -0,0 +1,166 @@ +/******************************************************** + Author: Abhilasha Sancheti, Sukul Bagai, Shubham Lohakare +********************************************************* + contours = findcontours(input_image(after canny is applied on it), mode, method, point_x, point_y) +********************************************************/ + +#include +#include "opencv2/core/core.hpp" +#include "opencv2/highgui/highgui.hpp" +#include "opencv2/opencv.hpp" +#include +using namespace cv; +using namespace std; +extern "C" +{ + #include "api_scilab.h" + #include "Scierror.h" + #include "BOOL.h" + #include + #include + #include "../common.h" + + int opencv_findContours(char *fname, unsigned long fname_len) + { + //Declaring variables + SciErr sciErr; + int intErr=0; + int iRows=0,iCols=0; + int *piLen2=NULL; + int *piLen3 = NULL; + int *piAddrNew = NULL; + int *piAddr2 = NULL; + int *piAddr3 = NULL; + int *piAddr4 = NULL; + int *piAddr5 = NULL; + int i,j,k, findmode , findmethod; + double find_method , mode; + double x,y; + + + CheckInputArgument(pvApiCtx, 5, 5);//checking input argument + CheckOutputArgument(pvApiCtx, 1, 1) ;//checking output argument + + + Mat src; + retrieveImage(src,1);//Retrieving the input image + src.convertTo(src,CV_8U);//Converting the input image to 8-bit image + cvtColor(src,src,CV_BGR2GRAY);//Converting to grayscale + //threshold(src,src,0,255,THRESH_BINARY); + sciErr = getVarAddressFromPosition(pvApiCtx,2,&piAddr2); + if (sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + intErr = getScalarDouble(pvApiCtx, piAddr2,&mode);//Getting the second input argument + if(intErr) + return intErr; + + sciErr = getVarAddressFromPosition(pvApiCtx,3,&piAddr3); + if (sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + intErr = getScalarDouble(pvApiCtx, piAddr3,&find_method);//Getting the third input argument + if(intErr) + return intErr; + //toget the x coordinate of point parameter of findcontours + sciErr = getVarAddressFromPosition(pvApiCtx,4,&piAddr4); + if (sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + intErr = getScalarDouble(pvApiCtx, piAddr4,&x);//Getting the fourth input argument + if(intErr) + return intErr; + + //toget the y coordinate of point parameter of findcontours + sciErr = getVarAddressFromPosition(pvApiCtx,5,&piAddr5); + if (sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + intErr = getScalarDouble(pvApiCtx, piAddr5 ,&y);//Getting the fifth input argument + if(intErr) + return intErr; + + //to set hte mode for findcontour + if(mode==1) + findmode = CV_RETR_EXTERNAL; + else if (mode==2) + findmode = CV_RETR_LIST; + else if (mode==3) + findmode = CV_RETR_CCOMP; + else if (mode==4) + findmode = CV_RETR_TREE; + else + { + findmode = CV_RETR_LIST; + sciprint("wrong mode given , using CV_RETR_TREE instead"); + } + // to set the method for findContours + if (find_method==1) + findmethod = CV_CHAIN_APPROX_NONE; + else if (find_method==2) + findmethod = CV_CHAIN_APPROX_SIMPLE; + else if (find_method==3) + findmethod = CV_CHAIN_APPROX_TC89_L1; + else if (find_method==4) + findmethod = CV_CHAIN_APPROX_TC89_KCOS; + else + { + findmethod = CV_CHAIN_APPROX_NONE; + sciprint("wrong method given , using CV_CHAIN_APPROX_SIMPLE instead"); + } + Point pt(x,y); + /// Find contours + vector > contours; + vector hierarchy; + try{ + findContours( src, contours, findmode, findmethod); + } + catch(Exception& e) + { + const char* err=e.what(); + printf("%s",err); + } + //Assigning the list as the Output Variable + sciErr = createList(pvApiCtx, nbInputArgument(pvApiCtx) + 1, contours.size(), &piAddrNew); + if(sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + + for(i=0;i +#include "opencv2/core/core.hpp" +#include "opencv2/highgui/highgui.hpp" +#include "opencv2/opencv.hpp" +#include +#include +#include +using namespace cv; +using namespace std; + extern "C" + { + #include "api_scilab.h" + #include "Scierror.h" + #include "BOOL.h" + #include + #include "../common.h" + int opencv_fitellipse(char *fname, unsigned long fname_len) + { + // Error management variable + SciErr sciErr; + //variable info + int iRows = 0; + int iCols = 0; + int piRows = 0; + int piCols = 0; + int* piAddr = NULL; + int* piAddr2 = NULL; + int* piAddr3 = NULL; + int* piAddr4 = NULL; + int* piAddr5 = NULL; + int* piAddr6 = NULL; + int* piAddrNew = NULL; + int* piLen = NULL; + double* pstData = NULL; + int* pstData2 = NULL; + double *rrows; + double *rcols; + double sigmaSpace; + int error; + vector contours; + ////checking input argument + CheckInputArgument(pvApiCtx,1,1); + //checking output argument + CheckOutputArgument(pvApiCtx,5,5); + //for first argument + // get Address of first input + sciErr = getVarAddressFromPosition(pvApiCtx,1,&piAddr); + //check for any error + if(sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + //retrieve input array + //SciErr getMatrixOfDouble(void* _pvCtx, int* _piAddress, int* _piRows, int* _piCols, double** _pdblReal) + sciErr = getMatrixOfDouble(pvApiCtx, piAddr, &iRows, &iCols,&pstData); + if(sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + int k=0; + + //The input array can be N*2 or 2*N + int temp=max(iCols,iRows); + contours.resize(temp); + for(int i=0;i +#include +#include "opencv2/core/core.hpp" +#include "opencv2/highgui/highgui.hpp" +#include "opencv2/imgproc/imgproc.hpp" +#include "opencv2/features2d.hpp" +#include "opencv2/xfeatures2d.hpp" +#include "opencv2/ml.hpp" +#include "opencv2/opencv.hpp" + + +using namespace cv; +using namespace cv::xfeatures2d; +using namespace std; +using namespace cv::ml; + +extern "C" +{ + #include "api_scilab.h" + #include "Scierror.h" + #include "BOOL.h" + #include + #include "sciprint.h" + #include "../common.h" + int opencv_getParamsSVM(char *fname, unsigned long fname_len) + { + // Error management variables + SciErr sciErr; + + //------Local variables------// + int upright = 1; + Ptr matcher = DescriptorMatcher::create("FlannBased"); + Ptr detector = SURF::create(400, 4, 2, 1, int(upright)); + Ptr extractor=detector; + Ptr bowDE=makePtr(extractor,matcher); + //SurfFeatureDetector detector(1, 4, 2, 1, int(upright)); + // char *classifierLocation = NULL; + Mat dictionary,features; + double response; + vector keyPoints; + int dictionarySize; + int *piAddr = NULL; + int *piChild = NULL; + int iRows, iCols; + char **pstData = NULL; + int *piLen = NULL; + char **classifierDescription = NULL; + int classifierDescriptionCount; + char *bagOfFeaturesLocation = NULL; + int descriptionCount; + double C=0,gamma=1,coef=0,degree=0,P=0,Nu=0,kernelType=2,setType=100; + //------Check number of parameters------// + CheckInputArgument(pvApiCtx, 1, 1); + CheckOutputArgument(pvApiCtx, 1, 1); + + //------Get input arguments------// + sciErr = getVarAddressFromPosition(pvApiCtx, 1, &piAddr); + if (sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + if(!isListType(pvApiCtx, piAddr)) + { + Scierror(999, "Error: The input argument #1 is not of type classifier.\n"); + return 0; + } + + // Extracting object type and checking if type is classifier + sciErr = getMatrixOfStringInList(pvApiCtx, piAddr, 1, &iRows, &iCols, NULL, NULL); + if(sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + + piLen = (int*)malloc(sizeof(int) * iRows * iCols); + + sciErr = getMatrixOfStringInList(pvApiCtx, piAddr, 1, &iRows, &iCols, piLen, NULL); + if(sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + + pstData = (char**)malloc(sizeof(char*) * iRows * iCols); + + for(int iter = 0 ; iter < iRows * iCols ; iter++) + { + pstData[iter] = (char*)malloc(sizeof(char) * (piLen[iter] + 1));//+ 1 for null termination + } + + sciErr = getMatrixOfStringInList(pvApiCtx, piAddr, 1, &iRows, &iCols, piLen, pstData); + if(sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + + if(!(strcmp(pstData[0],"classifier")==0)) + { + Scierror(999, "Error: The input argument #1 is not of type classifier.\n"); + return 0; + } + sciErr = getMatrixOfStringInList(pvApiCtx, piAddr, 2, &iRows, &iCols, NULL, NULL); + if (sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + + piLen = (int*) malloc(sizeof(int) * iRows * iCols); + + sciErr = getMatrixOfStringInList(pvApiCtx, piAddr, 2, &iRows, &iCols, piLen, NULL); + if (sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + + pstData = (char**) malloc(sizeof(char*) * iRows * iCols); + for(int iterPstData = 0; iterPstData < iRows * iCols; iterPstData++) + { + pstData[iterPstData] = (char*) malloc(sizeof(char) * piLen[iterPstData] + 1); + } + + sciErr = getMatrixOfStringInList(pvApiCtx, piAddr, 2, &iRows, &iCols, piLen, pstData); + if (sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + + if(iRows!=1 || iCols!=1) + { + Scierror(999, "1x1 Matrix expected for classifier argument."); + return 0; + } + string classifierLocation = string(pstData[0]); + sciErr = getMatrixOfStringInList(pvApiCtx, piAddr, 3, &iRows, &iCols, NULL, NULL); + if (sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + + piLen = (int*) malloc(sizeof(int) * iRows * iCols); + + sciErr = getMatrixOfStringInList(pvApiCtx, piAddr, 3, &iRows, &iCols, piLen, NULL); + if (sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + + pstData = (char**) malloc(sizeof(char*) * iRows * iCols); + for(int iterPstData = 0; iterPstData < iRows * iCols; iterPstData++) + { + pstData[iterPstData] = (char*) malloc(sizeof(char) * piLen[iterPstData] + 1); + } + + sciErr = getMatrixOfStringInList(pvApiCtx, piAddr, 3, &iRows, &iCols, piLen, pstData); + if (sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + + if(iRows!=1 || iCols!=1) + { + Scierror(999, "1x1 Matrix expected for bagOfFeatures argument."); + return 0; + } + bagOfFeaturesLocation = pstData[0]; + sciErr = getMatrixOfStringInList(pvApiCtx, piAddr, 4, &iRows, &iCols, NULL, NULL); + if (sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + + piLen = (int*) malloc(sizeof(int) * iRows * iCols); + + sciErr = getMatrixOfStringInList(pvApiCtx, piAddr, 4, &iRows, &iCols, piLen, NULL); + if (sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + + classifierDescription = (char**) malloc(sizeof(char*) * iRows * iCols); + for(int iterPstData = 0; iterPstData < iRows * iCols; iterPstData++) + { + classifierDescription[iterPstData] = (char*) malloc(sizeof(char) * piLen[iterPstData] + 1); + } + + sciErr = getMatrixOfStringInList(pvApiCtx, piAddr, 4, &iRows, &iCols, piLen, classifierDescription); + if (sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + sciprint("getting the parameters of trained SVM Model...\n"); +//------Actual processing------// + try{ + Ptr svm = Algorithm::load(classifierLocation); + if(!svm->isTrained()) + { + Scierror(999,"\nthe given model is not trained!,please try again!\n"); + return 0; + + } + C=svm->getC(); + degree=svm->getDegree(); + gamma=svm->getGamma(); + kernelType=svm->getKernelType(); + Nu=svm->getNu(); + P=svm->getP(); + setType=svm->getType(); + + sciprint("\ndone"); + } + catch(cv::Exception& e) + { + const char* err=e.what(); + sciprint("%s",err); + + } + //------Create output arguments------// + sciErr = createList(pvApiCtx, nbInputArgument(pvApiCtx) + 1, 8, &piAddr); + if(sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + sciErr = createMatrixOfDoubleInList(pvApiCtx, nbInputArgument(pvApiCtx)+1, piAddr, 1, 1, 1, &C); + if(sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + sciErr = createMatrixOfDoubleInList(pvApiCtx, nbInputArgument(pvApiCtx)+1, piAddr, 2, 1, 1, &coef); + if(sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + sciErr = createMatrixOfDoubleInList(pvApiCtx, nbInputArgument(pvApiCtx)+1, piAddr, 3, 1, 1, °ree); + if(sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + sciErr = createMatrixOfDoubleInList(pvApiCtx, nbInputArgument(pvApiCtx)+1, piAddr, 4, 1, 1, &gamma); + if(sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + sciErr = createMatrixOfDoubleInList(pvApiCtx, nbInputArgument(pvApiCtx)+1, piAddr, 5, 1, 1, &kernelType); + if(sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + sciErr = createMatrixOfDoubleInList(pvApiCtx, nbInputArgument(pvApiCtx)+1, piAddr, 6, 1, 1, &Nu); + if(sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + sciErr = createMatrixOfDoubleInList(pvApiCtx, nbInputArgument(pvApiCtx)+1, piAddr, 7, 1, 1, &P); + if(sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + sciErr = createMatrixOfDoubleInList(pvApiCtx, nbInputArgument(pvApiCtx)+1, piAddr, 8, 1, 1, &setType); + if(sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + //------Return Arguments------// + AssignOutputVariable(pvApiCtx, 1) = nbInputArgument(pvApiCtx)+1; + ReturnArguments(pvApiCtx); + return 0; + } + /* ==================================================================== */ +} + diff --git a/sci_gateway/cpp/opencv_getParamsSVMSGD.cpp b/sci_gateway/cpp/opencv_getParamsSVMSGD.cpp new file mode 100644 index 0000000..34cf794 --- /dev/null +++ b/sci_gateway/cpp/opencv_getParamsSVMSGD.cpp @@ -0,0 +1,275 @@ +/*************************************************** +Author : Nihar Rao +***************************************************/ +#include +#include +#include "opencv2/core/core.hpp" +#include "opencv2/highgui/highgui.hpp" +#include "opencv2/imgproc/imgproc.hpp" +#include "opencv2/features2d.hpp" +#include "opencv2/xfeatures2d.hpp" +#include "opencv2/ml.hpp" +#include "opencv2/opencv.hpp" + + +using namespace cv; +using namespace cv::xfeatures2d; +using namespace std; +using namespace cv::ml; + +extern "C" +{ + #include "api_scilab.h" + #include "Scierror.h" + #include "BOOL.h" + #include + #include "sciprint.h" + #include "../common.h" + int opencv_getParamsSVMSGD(char *fname, unsigned long fname_len) + { + // Error management variables + SciErr sciErr; + + //------Local variables------// + int upright = 1; + Ptr matcher = DescriptorMatcher::create("FlannBased"); + Ptr detector = SURF::create(400, 4, 2, 1, int(upright)); + Ptr extractor=detector; + Ptr bowDE=makePtr(extractor,matcher); + //SurfFeatureDetector detector(1, 4, 2, 1, int(upright)); + // char *classifierLocation = NULL; + Mat dictionary,features; + double response; + vector keyPoints; + int dictionarySize; + int *piAddr = NULL; + int *piChild = NULL; + int iRows, iCols; + char **pstData = NULL; + int *piLen = NULL; + char **classifierDescription = NULL; + int classifierDescriptionCount; + char *bagOfFeaturesLocation = NULL; + int descriptionCount; + double initStepSize=0.1,marginreg=0,optimalParam=0,stepDecreasingPower=0.1;//all model paramenter set to their default values + double marginType=0,svmsgdsgdType=0; + //------Check number of parameters------// + CheckInputArgument(pvApiCtx, 1, 1); + CheckOutputArgument(pvApiCtx, 1, 1); + + //------Get input arguments------// + sciErr = getVarAddressFromPosition(pvApiCtx, 1, &piAddr); + if (sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + if(!isListType(pvApiCtx, piAddr)) + { + Scierror(999, "Error: The input argument #1 is not of type classifier.\n"); + return 0; + } + + // Extracting object type and checking if type is classifier + sciErr = getMatrixOfStringInList(pvApiCtx, piAddr, 1, &iRows, &iCols, NULL, NULL); + if(sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + + piLen = (int*)malloc(sizeof(int) * iRows * iCols); + + sciErr = getMatrixOfStringInList(pvApiCtx, piAddr, 1, &iRows, &iCols, piLen, NULL); + if(sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + + pstData = (char**)malloc(sizeof(char*) * iRows * iCols); + + for(int iter = 0 ; iter < iRows * iCols ; iter++) + { + pstData[iter] = (char*)malloc(sizeof(char) * (piLen[iter] + 1));//+ 1 for null termination + } + + sciErr = getMatrixOfStringInList(pvApiCtx, piAddr, 1, &iRows, &iCols, piLen, pstData); + if(sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + + if(!(strcmp(pstData[0],"classifier")==0)) + { + Scierror(999, "Error: The input argument #1 is not of type classifier.\n"); + return 0; + } + sciErr = getMatrixOfStringInList(pvApiCtx, piAddr, 2, &iRows, &iCols, NULL, NULL); + if (sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + + piLen = (int*) malloc(sizeof(int) * iRows * iCols); + + sciErr = getMatrixOfStringInList(pvApiCtx, piAddr, 2, &iRows, &iCols, piLen, NULL); + if (sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + + pstData = (char**) malloc(sizeof(char*) * iRows * iCols); + for(int iterPstData = 0; iterPstData < iRows * iCols; iterPstData++) + { + pstData[iterPstData] = (char*) malloc(sizeof(char) * piLen[iterPstData] + 1); + } + + sciErr = getMatrixOfStringInList(pvApiCtx, piAddr, 2, &iRows, &iCols, piLen, pstData); + if (sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + + if(iRows!=1 || iCols!=1) + { + Scierror(999, "1x1 Matrix expected for classifier argument."); + return 0; + } + string classifierLocation = string(pstData[0]); + sciErr = getMatrixOfStringInList(pvApiCtx, piAddr, 3, &iRows, &iCols, NULL, NULL); + if (sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + + piLen = (int*) malloc(sizeof(int) * iRows * iCols); + + sciErr = getMatrixOfStringInList(pvApiCtx, piAddr, 3, &iRows, &iCols, piLen, NULL); + if (sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + + pstData = (char**) malloc(sizeof(char*) * iRows * iCols); + for(int iterPstData = 0; iterPstData < iRows * iCols; iterPstData++) + { + pstData[iterPstData] = (char*) malloc(sizeof(char) * piLen[iterPstData] + 1); + } + + sciErr = getMatrixOfStringInList(pvApiCtx, piAddr, 3, &iRows, &iCols, piLen, pstData); + if (sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + + if(iRows!=1 || iCols!=1) + { + Scierror(999, "1x1 Matrix expected for bagOfFeatures argument."); + return 0; + } + bagOfFeaturesLocation = pstData[0]; + sciErr = getMatrixOfStringInList(pvApiCtx, piAddr, 4, &iRows, &iCols, NULL, NULL); + if (sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + + piLen = (int*) malloc(sizeof(int) * iRows * iCols); + + sciErr = getMatrixOfStringInList(pvApiCtx, piAddr, 4, &iRows, &iCols, piLen, NULL); + if (sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + + classifierDescription = (char**) malloc(sizeof(char*) * iRows * iCols); + for(int iterPstData = 0; iterPstData < iRows * iCols; iterPstData++) + { + classifierDescription[iterPstData] = (char*) malloc(sizeof(char) * piLen[iterPstData] + 1); + } + + sciErr = getMatrixOfStringInList(pvApiCtx, piAddr, 4, &iRows, &iCols, piLen, classifierDescription); + if (sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + sciprint("getting the parameters of trained SVMSGD Model...\n"); +//------Actual processing------// + try{ + Ptr svmsgd = Algorithm::load(classifierLocation); + if(!svmsgd->isTrained()) + { + Scierror(999,"\nthe given model is not trained!,please try again!\n"); + return 0; + + } + initStepSize=svmsgd->getInitialStepSize(); + marginreg=svmsgd->getMarginRegularization(); + stepDecreasingPower=svmsgd->getStepDecreasingPower(); + svmsgdsgdType=svmsgd->getSvmsgdType(); + marginType=svmsgd->getMarginType(); + + sciprint("\ndone\n"); + } + catch(cv::Exception& e) + { + const char* err=e.what(); + sciprint("%s",err); + + } + //------Create output arguments------// + sciErr = createList(pvApiCtx, nbInputArgument(pvApiCtx) + 1, 6, &piAddr); + if(sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + sciErr = createMatrixOfDoubleInList(pvApiCtx, nbInputArgument(pvApiCtx)+1, piAddr, 1, 1, 1, &initStepSize); + if(sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + sciErr = createMatrixOfDoubleInList(pvApiCtx, nbInputArgument(pvApiCtx)+1, piAddr, 2, 1, 1, &marginreg); + if(sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + sciErr = createMatrixOfDoubleInList(pvApiCtx, nbInputArgument(pvApiCtx)+1, piAddr, 3, 1, 1, &stepDecreasingPower); + if(sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + sciErr = createMatrixOfDoubleInList(pvApiCtx, nbInputArgument(pvApiCtx)+1, piAddr, 4, 1, 1, &svmsgdsgdType); + if(sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + sciErr = createMatrixOfDoubleInList(pvApiCtx, nbInputArgument(pvApiCtx)+1, piAddr, 5, 1, 1, &marginType); + if(sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + //------Return Arguments------// + AssignOutputVariable(pvApiCtx, 1) = nbInputArgument(pvApiCtx)+1; + ReturnArguments(pvApiCtx); + return 0; + } + /* ==================================================================== */ +} + diff --git a/sci_gateway/cpp/opencv_graycoprops.cpp b/sci_gateway/cpp/opencv_graycoprops.cpp new file mode 100644 index 0000000..cf6daa4 --- /dev/null +++ b/sci_gateway/cpp/opencv_graycoprops.cpp @@ -0,0 +1,674 @@ +/* Author: Nihar rao & Samiran Roy + +/* Usage of the function is exactly similar to matlab function */ +/* + * graycoprops + * + * graycoprops in scilab + * Please refer to : + * http://www.cse.unsw.edu.au/~icml2002/workshops/MLCV02/MLCV02-Bevk.pdf, p.3. + */ + +#include +#include +#include +#include "opencv2/core/core.hpp" +#include "opencv2/highgui/highgui.hpp" +#include "opencv2/opencv.hpp" +#include +using namespace cv; +using namespace std; +extern "C" { +#include "api_scilab.h" +#include "Scierror.h" +#include "BOOL.h" +#include +#include "sciprint.h" +#include "../common.h" + +double return_contrast(Mat image) + +{ + double contrast = 0; + + for (int i = 0; i < image.rows; i++) { + for (int j = 0; j < image.cols; j++) { + contrast = contrast + (pow((i - j), 2) * image.at(i, j)); + } + } + return contrast; +} + +double return_correlation(Mat image) + +{ + double correlation = 0; + + std::vector mg_rows; + std::vector mg_cols; + + // Meshgrid of row and column indices + for (int i = 0; i < image.rows; i++) { + for (int j = 0; j < image.cols; j++) { + mg_rows.push_back(j); + mg_cols.push_back(i); + } + } + + // for (int i=0; i(i); + + for (int i = 0; i < mg_cols.size(); i++) + mean_col = mean_col + mg_cols[i] * flat_image.at(i); + + for (int i = 0; i < mg_rows.size(); i++) + std_row = + std_row + (pow(mg_rows[i] - mean_row, 2) * flat_image.at(i)); + + std_row = sqrt(std_row); + + for (int i = 0; i < mg_cols.size(); i++) + std_col = + std_col + (pow(mg_cols[i] - mean_col, 2) * flat_image.at(i)); + + std_col = sqrt(std_col); + + for (int i = 0; i < mg_rows.size(); i++) + correlation = + correlation + ((mg_rows[i] - mean_row) * (mg_cols[i] - mean_col) * + flat_image.at(i)); + + double denom = std_col * std_row; + if (denom != 0) { + correlation = correlation / denom; + } + + // sciprint("\n"); + + // sciprint("MR: %f",mean_row); + // sciprint("MC: %f",mean_col); + + // sciprint("SR: %f",std_row); + // sciprint("SC: %f",std_col); + return correlation; +} + +double return_energy(Mat image) + +{ + double energy = 0; + + for (int i = 0; i < image.rows; i++) { + for (int j = 0; j < image.cols; j++) { + energy = energy + pow(image.at(i, j), 2); + } + } + return energy; +} + +double return_homogeneity(Mat image) + +{ + double homogeneity = 0; + + for (int i = 0; i < image.rows; i++) { + for (int j = 0; j < image.cols; j++) { + homogeneity = homogeneity + (image.at(i, j) / (1 + abs(i - j))); + } + } + return homogeneity; +} + +int opencv_graycoprops(char *fname, unsigned long fname_len) { + SciErr sciErr; + int intErr = 0; + + int *piAddr1 = NULL; + int *piLen = NULL; + int i,j; + int argPresence[4]={0}; + + int error; + int iRows,iCols; + // String holding the second argument + int iRet = 0; + char **pstData = NULL; + vector rgb; + double s; + + // Checking input argument + CheckInputArgument(pvApiCtx, 1, 2); + CheckOutputArgument(pvApiCtx, 1, 4); + + //get number of input arguments + int n=*getNbInputArgument(pvApiCtx); + // Get input image + Mat image; + retrieveImage(image, 1); + + // converting image to float + + image.convertTo(image, CV_64FC1, 1, 0); + //if only one input argument + if(n==1) + { + if (image.channels() == 1) { + // Normalizing image + + double s = cv::sum(image)[0]; + image = image / s; + + + double contrast = return_contrast(image); + intErr = + createScalarDouble(pvApiCtx, nbInputArgument(pvApiCtx) + 1, contrast); + if (intErr) return intErr; + + // Assigning the list as the Output Variable + AssignOutputVariable(pvApiCtx, 1) = nbInputArgument(pvApiCtx) + 1; + // Returning the Output Variables as arguments to the Scilab environment + + + + + + double correlation = return_correlation(image); + + intErr = createScalarDouble(pvApiCtx, nbInputArgument(pvApiCtx) + 2, + correlation); + if (intErr) return intErr; + + // Assigning the list as the Output Variable + AssignOutputVariable(pvApiCtx, 2) = nbInputArgument(pvApiCtx) + 2; + // Returning the Output Variables as arguments to the Scilab environment + + + double energy = return_energy(image); + + intErr = + createScalarDouble(pvApiCtx, nbInputArgument(pvApiCtx) + 3, energy); + if (intErr) return intErr; + + // Assigning the list as the Output Variable + AssignOutputVariable(pvApiCtx, 3) = nbInputArgument(pvApiCtx) + 3; + + + double homogeneity = return_homogeneity(image); + + intErr = createScalarDouble(pvApiCtx, nbInputArgument(pvApiCtx) + 4, + homogeneity); + if (intErr) return intErr; + + // Assigning the list as the Output Variable + AssignOutputVariable(pvApiCtx, 4) = nbInputArgument(pvApiCtx) + 4; + // Returning the Output Variables as arguments to the Scilab environment + ReturnArguments(pvApiCtx); + return 0; + } + + else if (image.channels() == 3) { + + + split(image, rgb); + + double *contrast = (double *)malloc(sizeof(double) * 3); + + + for (int i = 0; i < 3; i++) { + s = cv::sum(rgb[i])[0]; + rgb[i] = rgb[i] / s; + contrast[2-i] = return_contrast(rgb[i]); + } + + sciErr = createMatrixOfDouble(pvApiCtx, nbInputArgument(pvApiCtx)+1, 1, 3, + contrast); + + free(contrast); + + if (sciErr.iErr) { + printError(&sciErr, 0); + return 0; + } + + // Assigning the list as the Output Variable + AssignOutputVariable(pvApiCtx, 1) = nbInputArgument(pvApiCtx)+1; + // Returning the Output Variables as arguments to the Scilab environment + + + + split(image, rgb); + + double *correlation = (double *)malloc(sizeof(double) * 3); + + + for (int i = 0; i < 3; i++) { + s = cv::sum(rgb[i])[0]; + rgb[i] = rgb[i] / s; + correlation[2-i] = return_correlation(rgb[i]); + } + + sciErr = createMatrixOfDouble(pvApiCtx, nbInputArgument(pvApiCtx)+2, 1, 3, + correlation); + + free(correlation); + + if (sciErr.iErr) { + printError(&sciErr, 0); + return 0; + } + + // Assigning the list as the Output Variable + AssignOutputVariable(pvApiCtx, 2) = nbInputArgument(pvApiCtx)+2; + // Returning the Output Variables as arguments to the Scilab environment + + + + + split(image, rgb); + + double *energy = (double *)malloc(sizeof(double) * 3); + + + for (int i = 0; i < 3; i++) { + s = cv::sum(rgb[i])[0]; + rgb[i] = rgb[i] / s; + energy[2-i] = return_energy(rgb[i]); + } + + sciErr = createMatrixOfDouble(pvApiCtx, nbInputArgument(pvApiCtx)+3, 1, 3, + energy); + + free(energy); + + if (sciErr.iErr) { + printError(&sciErr, 0); + return 0; + } + + // Assigning the list as the Output Variable + AssignOutputVariable(pvApiCtx, 3) = nbInputArgument(pvApiCtx)+3; + + + + split(image, rgb); + + double *homogeneity = (double *)malloc(sizeof(double) * 3); + + for (int i = 0; i < 3; i++) { + s = cv::sum(rgb[i])[0]; + rgb[i] = rgb[i] / s; + homogeneity[2-i] = return_homogeneity(rgb[i]); + } + + sciErr = createMatrixOfDouble(pvApiCtx, nbInputArgument(pvApiCtx)+4, 1, 3, + homogeneity); + + free(homogeneity); + + if (sciErr.iErr) { + printError(&sciErr, 0); + return 0; + } + + // Assigning the list as the Output Variable + AssignOutputVariable(pvApiCtx, 4) = nbInputArgument(pvApiCtx)+4; + // Returning the Output Variables as arguments to the Scilab environment + ReturnArguments(pvApiCtx); + return 0; + + + } else { + sciprint("Invalid number of channels in the image(must be 1 or 3)\n"); + return 0; + } + + + + } + + //2 input arguments + + else + { + + if (image.channels() == 1) { + // Normalizing image + + s = cv::sum(image)[0]; + image = image / s; + + sciErr = getVarAddressFromPosition(pvApiCtx, 2, &piAddr1); + + if (sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + + sciErr = getMatrixOfString(pvApiCtx, piAddr1, &iRows, &iCols, NULL, NULL); + if(sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + piLen = (int*)malloc(sizeof(int) * iRows * iCols); + //second call to retrieve length of each string + sciErr = getMatrixOfString(pvApiCtx, piAddr1, &iRows, &iCols, piLen, NULL); + if(sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + pstData= (char**)malloc(sizeof(char*) * iRows * iCols); + for(i = 0 ; i < iRows * iCols ; i++) + { + pstData[i] = (char*)malloc(sizeof(char) * (piLen[i] + 1));//+ 1 for null termination + } + //third call to retrieve data + sciErr = getMatrixOfString(pvApiCtx, piAddr1, &iRows, &iCols, piLen,pstData); + if(sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + //iterate througt the matrix + + for(j=0;j +#include "opencv2/core/core.hpp" +#include "opencv2/highgui/highgui.hpp" +#include "opencv2/imgproc/imgproc.hpp" +#include "opencv2/opencv.hpp" +#include +using namespace cv; +using namespace std; +extern "C" +{ + #include "api_scilab.h" + #include "Scierror.h" + #include "BOOL.h" + #include + #include + #include "../common.h" + int opencv_histeq(char *fname, unsigned long fname_len) + { + + // Error management variable + SciErr sciErr; + + //checking input argument + CheckInputArgument(pvApiCtx,1,1); + //checking output argument + CheckOutputArgument(pvApiCtx,1,1) ; + //for first argument + Mat img,p,dst; + + retrieveImage(img,1);//Retrieving the input image + try{ + img.convertTo(img,CV_8U);//Converting the image to 8-bit image + cvtColor(img,img,CV_BGR2GRAY);//Converting to grayscale + + //open cv function to equalize the histogram + equalizeHist(img,dst); + } + catch(Exception& e) + { + const char* err=e.what(); + printf("%s",err); + } + + string tempstring = type2str(dst.type()); + char* checker = (char *)malloc(tempstring.size() + 1); + memcpy(checker, tempstring.c_str(), tempstring.size() + 1); + returnImage(checker,dst,1); + AssignOutputVariable(pvApiCtx, 1) = nbInputArgument(pvApiCtx) + 1; + ReturnArguments(pvApiCtx); + + } +} +/* ==================================================================== */ + diff --git a/sci_gateway/cpp/opencv_imadd.cpp b/sci_gateway/cpp/opencv_imadd.cpp new file mode 100644 index 0000000..1e14b59 --- /dev/null +++ b/sci_gateway/cpp/opencv_imadd.cpp @@ -0,0 +1,74 @@ +/******************************************************** +Function :imadd +Syntax :C=imadd(A,B) +Author : Tess Zacharias, Shubham Lohakare +********************************************************/ + +#include +#include "opencv2/core/core.hpp" +#include "opencv2/highgui/highgui.hpp" +#include "opencv2/opencv.hpp" +#include +#include "string.h" +using namespace cv; +using namespace std; +extern "C" +{ + #include "api_scilab.h" + #include "Scierror.h" + #include "BOOL.h" + #include + #include "sciprint.h" + #include "../common.h" + int opencv_imadd(char *fname, unsigned long fname_len) + { + SciErr sciErr; + Mat A,B,C; + int* piAddr2=NULL; + int iType = 0; + int iRet = 0; + double value= 0; + + CheckInputArgument(pvApiCtx, 2, 2);//checking Input arguments + CheckOutputArgument(pvApiCtx, 1, 1);//Checking Output arguments + + retrieveImage(A,1);//Retrieving the first argument + + sciErr =getVarAddressFromPosition(pvApiCtx,2,&piAddr2); + sciErr = getVarType(pvApiCtx, piAddr2, &iType); + if(iType==sci_list)//Checking the type of 2nd argument + { + retrieveImage(B,2); + Size s1=A.size(); + Size s2=B.size(); + if(s1!=s2) + { + sciprint("\nBoth input should be same size"); + return 0; + } + add(A,B,C); + } + else + { + if(isDoubleType(pvApiCtx, piAddr2)) + { + if(isScalar(pvApiCtx, piAddr2)) + { + iRet = getScalarDouble(pvApiCtx, piAddr2, &value); + } + } + add(A,value,C); + } + + int temp = nbInputArgument(pvApiCtx) + 1; + string tempstring = type2str(C.type()); + char *checker; + checker = (char *)malloc(tempstring.size() + 1); + memcpy(checker, tempstring.c_str(), tempstring.size() + 1); + returnImage(checker,C,1); + free(checker); + AssignOutputVariable(pvApiCtx, 1) = nbInputArgument(pvApiCtx) + 1; + ReturnArguments(pvApiCtx); + return 0; + } +} diff --git a/sci_gateway/cpp/opencv_imcomplement.cpp b/sci_gateway/cpp/opencv_imcomplement.cpp new file mode 100644 index 0000000..7d88e13 --- /dev/null +++ b/sci_gateway/cpp/opencv_imcomplement.cpp @@ -0,0 +1,56 @@ +/******************************************************** +Function :imcomplement +Syntax :B=imcomplement(A) +Author : Shubham Lohakare, Tess Zacharias +********************************************************/ + +#include +#include "opencv2/core/core.hpp" +#include "opencv2/highgui/highgui.hpp" +#include "opencv2/opencv.hpp" +#include +#include "string.h" +using namespace cv; +using namespace std; +extern "C" +{ + #include "api_scilab.h" + #include "Scierror.h" + #include "BOOL.h" + #include + #include "sciprint.h" + #include "../common.h" + int opencv_imcomplement(char *fname, unsigned long fname_len) + { + //DEclaring variables + SciErr sciErr; + Mat A,B,C; + int* piAddr2=NULL; + int iType = 0; + int iRet = 0; + double value= 0; + + CheckInputArgument(pvApiCtx, 1,1);//Check input arguments + CheckOutputArgument(pvApiCtx, 1, 1);//Check output arguments + + retrieveImage(A,1);//Retrieving the first input + try{ + cv::subtract(cv::Scalar::all(255),A,A);//Calculates the complement + } + catch(Exception& e) + { + const char* err=e.what(); + sciprint("%s",err); + } + int temp = nbInputArgument(pvApiCtx) + 1; + string tempstring = type2str(A.type()); + char *checker; + checker = (char *)malloc(tempstring.size() + 1); + memcpy(checker, tempstring.c_str(), tempstring.size() + 1); + returnImage(checker,A,1); + free(checker); + AssignOutputVariable(pvApiCtx, 1) = nbInputArgument(pvApiCtx) + 1; + ReturnArguments(pvApiCtx); + return 0; + } +} diff --git a/sci_gateway/cpp/opencv_imcontour.cpp b/sci_gateway/cpp/opencv_imcontour.cpp new file mode 100644 index 0000000..69014ae --- /dev/null +++ b/sci_gateway/cpp/opencv_imcontour.cpp @@ -0,0 +1,63 @@ +/******************************************************** +Function :imcontour +Syntax :B=imcontour(A) +Authors: Tess Zacharias, Shubham Lohakare + +********************************************************/ + +#include +#include "opencv2/core/core.hpp" +#include "opencv2/highgui/highgui.hpp" +#include "opencv2/opencv.hpp" +#include +using namespace cv; +using namespace std; +extern "C" +{ + #include "api_scilab.h" + #include "Scierror.h" + #include "BOOL.h" + #include + #include "sciprint.h" + #include "../common.h" + + int opencv_imcontour(char *fname, unsigned long fname_len) + { + + SciErr sciErr; + int intErr = 0; + Mat gray,image; + //checking input argument + CheckInputArgument(pvApiCtx, 1, 1); + CheckOutputArgument(pvApiCtx, 1, 1) ; + retrieveImage(image, 1); + image.convertTo(image,CV_8U); + cvtColor(image, gray, CV_BGR2GRAY); + Canny(gray, gray, 100, 200, 3); + /// Find contours + vector > contours; + vector hierarchy; + RNG rng(12345); + findContours( gray, contours, hierarchy, CV_RETR_TREE, CV_CHAIN_APPROX_SIMPLE, Point(0, 0) ); + /// Draw contours + Mat drawing = Mat::zeros( gray.size(), CV_8UC3 ); + for( int i = 0; i< contours.size(); i++ ) + { + Scalar color = Scalar(rng.uniform(0,255),rng.uniform(0,255),rng.uniform(0,255)); + drawContours( drawing, contours, i, color, 1, 8, hierarchy, 0, Point()); + } + bitwise_not(drawing,drawing); + string tempstring = type2str(drawing.type()); + char *checker; + checker = (char *)malloc(tempstring.size() + 1); + memcpy(checker, tempstring.c_str(), tempstring.size() + 1); + returnImage(checker,drawing,1); + free(checker); + //Assigning the list as the Output Variable + AssignOutputVariable(pvApiCtx, 1) = nbInputArgument(pvApiCtx) + 1; + //Returning the Output Variables as arguments to the Scilab environment + ReturnArguments(pvApiCtx); + return 0; + + } +} diff --git a/sci_gateway/cpp/opencv_imdecolor.cpp b/sci_gateway/cpp/opencv_imdecolor.cpp new file mode 100644 index 0000000..c8acc3c --- /dev/null +++ b/sci_gateway/cpp/opencv_imdecolor.cpp @@ -0,0 +1,70 @@ +/* +This is a .cpp gateway file for the 'imdecolor' scilab function. +It uses the OpenCV function : cv::decolor (InputArray src, OutputArray grayscale, OutputArray color_boost) +It takes an image as input and gives 2 output images. One is a grayscale image and the other a color boosted image. + +Author : Shubham Lohakare, NITK Surathkal + Ashish Manatosh Barik, NIT Rourkela +*/ +#include +#include "opencv2/core/core.hpp" +#include "opencv2/highgui/highgui.hpp" +#include "opencv2/opencv.hpp" +#include +using namespace cv; +using namespace std; +extern "C" +{ + #include "api_scilab.h" + #include "Scierror.h" + #include "BOOL.h" + #include + #include "sciprint.h" + #include "../common.h" + + int opencv_imdecolor(char *fname, unsigned long fname_len) + { SciErr sciErr; + int i; + + + + CheckInputArgument(pvApiCtx, 1, 1);//Check The number of input arguments + CheckOutputArgument(pvApiCtx, 2, 2) ;//Check The number of output arguments + + Mat src, dst,colout;//Declaring variables + + try{ + retrieveImage(src,1);//Getting the input image + src.convertTo(src,CV_8U);//Converting the image to 8bit + + decolor(src,dst,colout);//OpenCV function. Gives 2 outputs. In dst a decolored image is stored and in colout a color boosted image is stored. + } + catch(Exception &e) + { + const char* err=e.what(); + sciprint("%s",err); + } + + string tempstring1 = type2str(dst.type());//For returning the first image as output + char* checker1; + checker1 = (char *)malloc(tempstring1.size() + 1); + memcpy(checker1, tempstring1.c_str(), tempstring1.size() + 1); + returnImage(checker1,dst,1); + free(checker1); + AssignOutputVariable(pvApiCtx, 1) = nbInputArgument(pvApiCtx) + 1; + + string tempstring2 = type2str(colout.type());//For returning the second image as output + char* checker2; + checker2 = (char *)malloc(tempstring2.size() + 1); + memcpy(checker2, tempstring2.c_str(), tempstring2.size() + 1); + returnImage(checker2,colout,2); + free(checker2); + AssignOutputVariable(pvApiCtx, 2) = nbInputArgument(pvApiCtx) + 2; + + ReturnArguments(pvApiCtx); + + return 0; + + } + +} diff --git a/sci_gateway/cpp/opencv_imdivide.cpp b/sci_gateway/cpp/opencv_imdivide.cpp new file mode 100644 index 0000000..6755322 --- /dev/null +++ b/sci_gateway/cpp/opencv_imdivide.cpp @@ -0,0 +1,78 @@ +/******************************************************** +Function :imdivide +Syntax :C=imdivide(A,B) +Authors : Tess Zacharias, Shubham Lohakare +********************************************************/ + +#include +#include "opencv2/core/core.hpp" +#include "opencv2/highgui/highgui.hpp" +#include "opencv2/opencv.hpp" +#include +#include "string.h" +using namespace cv; +using namespace std; +extern "C" +{ + #include "api_scilab.h" + #include "Scierror.h" + #include "BOOL.h" + #include + #include "sciprint.h" + #include "../common.h" + int opencv_imdivide(char *fname, unsigned long fname_len) + { + //DEclaring the variables + SciErr sciErr; + Mat A,B,C; + int* piAddr2=NULL; + int iType = 0; + int iRet = 0; + double value= 0; + + CheckInputArgument(pvApiCtx, 2, 2);//Checking the input arguments + CheckOutputArgument(pvApiCtx, 1, 1);//Checking the output arguments + + retrieveImage(A,1);//Getting the first argument + + sciErr =getVarAddressFromPosition(pvApiCtx,2,&piAddr2); + sciErr = getVarType(pvApiCtx, piAddr2, &iType); + if(iType==sci_list)//Checking the type of 2nd argument + { + retrieveImage(B,2); + Size s1=A.size(); + Size s2=B.size(); + + try{ + divide(A,B,C); + } + catch(Exception& e) + { + const char* err=e.what(); + sciprint("%s",err); + } + } + else + { + if(isDoubleType(pvApiCtx, piAddr2)) + { + if(isScalar(pvApiCtx, piAddr2)) + { + iRet = getScalarDouble(pvApiCtx, piAddr2, &value); + } + } + C=A/value; + } + + int temp = nbInputArgument(pvApiCtx) + 1; + string tempstring = type2str(C.type()); + char *checker; + checker = (char *)malloc(tempstring.size() + 1); + memcpy(checker, tempstring.c_str(), tempstring.size() + 1); + returnImage(checker,C,1); + free(checker); + AssignOutputVariable(pvApiCtx, 1) = nbInputArgument(pvApiCtx) + 1; + ReturnArguments(pvApiCtx); + return 0; + } +} diff --git a/sci_gateway/cpp/opencv_imfill.cpp b/sci_gateway/cpp/opencv_imfill.cpp new file mode 100644 index 0000000..6f94e05 --- /dev/null +++ b/sci_gateway/cpp/opencv_imfill.cpp @@ -0,0 +1,193 @@ +/******************************************************** +Author: Vinay Bhat +******************************************************** +Usage: return_image = imfill(image) + return_image = imfill(image, 'holes') + return_image = imfill(image, points) +Example: + im = imfill(image, [1 1; 10 10; 11 12]) +********************************************************/ + +#include +#include "opencv2/core/core.hpp" +#include "opencv2/highgui/highgui.hpp" +#include "opencv2/opencv.hpp" +#include +using namespace cv; +using namespace std; +extern "C" +{ + #include "api_scilab.h" + #include "Scierror.h" + #include "BOOL.h" + #include + #include "sciprint.h" + #include "../common.h" + + void imfill_imreconstruct(Mat, Mat, Mat&); + + int opencv_imfill(char *fname, unsigned long fname_len) + { + + SciErr sciErr; + int intErr = 0; + int *piAddr = NULL; + int i, j; + double maxVal; + int iRet; + int iRows, iCols; + double *pstData = NULL; + + //checking input argument + CheckInputArgument(pvApiCtx, 1, 2); + CheckOutputArgument(pvApiCtx, 1, 1); + + // Get the input image from the Scilab environment + Mat image, dst; + retrieveImage(image, 1); + image.convertTo(image,CV_8U); + if (nbInputArgument(pvApiCtx) == 2) + { + sciErr = getVarAddressFromPosition(pvApiCtx, 2, &piAddr); + if (sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + + if (image.type() != CV_8UC1) + { + Mat temp; + temp = image.clone(); + cvtColor(temp, image, CV_BGR2GRAY); + } + + if(isStringType(pvApiCtx, piAddr)) + { + char* pstData = NULL; + + iRet = getAllocatedSingleString(pvApiCtx, piAddr, &pstData); + + if(iRet) + { + freeAllocatedSingleString(pstData); + return iRet; + } + + if (strcmp(pstData, "holes") == 0) + { + freeAllocatedSingleString(pstData); + // Floodfill from point (0, 0) + Mat im_floodfill = image.clone(); + floodFill(im_floodfill, Point(0,0), Scalar(255)); + + // Invert floodfilled image + Mat im_floodfill_inv; + bitwise_not(im_floodfill, im_floodfill_inv); + + // Combine the two images to get the foreground. + Mat dst2 = (image | im_floodfill_inv); + erode(dst2, dst, Mat()); + + } + else + { + sciprint("Option not identified. Maybe you meant 'holes'."); + return 0; + } + } + else + { + + // Get the points list in the form of a matrix + // No. of columns = 2 + // No. of rows = No. of points + sciErr = getMatrixOfDouble(pvApiCtx, piAddr, &iRows, &iCols, &pstData); + if(sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + + if (iCols != 2) + { + sciprint("Please enter a valid column and row index."); + return 0; + } + + for (i = 0; i < iRows*iCols; i += iCols) + { + if (pstData[i] < 0 || pstData[i+1] < 0) + { + sciprint("Coordinates cannot be negative.\n"); + return 0; + } + else + floodFill(image, Point(pstData[i], pstData[i+1]), Scalar(255)); + } + + dst = image.clone(); + } + + } + else + { + Mat gray_image; + + cvtColor(image, gray_image, CV_BGR2GRAY); + + minMaxLoc(gray_image, NULL, &maxVal, NULL, NULL); + + Mat marker = Mat(gray_image.size(), gray_image.type()); + + marker = Scalar::all(maxVal); + + for (i = 0; (i == 0 || i == marker.cols-1); i += (marker.cols - 1)) + { + for (j = 0; j < marker.rows; j++) + { + marker.at(i,j) = gray_image.at(i,j); + } + } + + for (i = 1; i < marker.cols-1; i++) + { + for (j = 0; (j == 0 || j == marker.rows-1); j += (marker.rows - 1)) + { + marker.at(i,j) = gray_image.at(i,j); + } + } + + imfill_imreconstruct(gray_image, marker, dst); + } + + + + string tempstring = type2str(dst.type()); + char *checker; + checker = (char *)malloc(tempstring.size() + 1); + memcpy(checker, tempstring.c_str(), tempstring.size() + 1); + returnImage(checker, dst, 1); + free(checker); + + //Assigning the list as the Output Variable + AssignOutputVariable(pvApiCtx, 1) = nbInputArgument(pvApiCtx) + 1; + //Returning the Output Variables as arguments to the Scilab environment + ReturnArguments(pvApiCtx); + return 0; + + } + void imfill_imreconstruct(Mat g, Mat f, Mat& dest) + { + Mat m0, m1, m; + m1 = f; + do { + m0 = m1.clone(); + erode(m0, m, Mat()); + max(g, m, m1); + } while(countNonZero(m1 != m0) != 0); + dest = m1.clone(); + } + +/* ==================================================================== */ +} diff --git a/sci_gateway/cpp/opencv_imfindcircles.cpp~ b/sci_gateway/cpp/opencv_imfindcircles.cpp~ new file mode 100644 index 0000000..7201e7d --- /dev/null +++ b/sci_gateway/cpp/opencv_imfindcircles.cpp~ @@ -0,0 +1,148 @@ +/******************************************************** +Function :imfindcircles +Syntax :B=imfindcircles(A) +Author: Tess Zacharias + +********************************************************/ + +#include +#include "opencv2/core/core.hpp" +#include "opencv2/highgui/highgui.hpp" +#include "opencv2/opencv.hpp" +#include +using namespace cv; +using namespace std; +extern "C" +{ + #include "api_scilab.h" + #include "Scierror.h" + #include "BOOL.h" + #include + #include "sciprint.h" + #include "../common.h" + + int opencv_imfindcircles(char *fname, unsigned long fname_len) + { + + SciErr sciErr; + int intErr = 0; + int *piAddrNew = NULL; + int *piAddr2 = NULL; + int *piAddr3 = NULL; + Mat src_gray,image; + double Rmin,Rmax; + //checking input argument + CheckInputArgument(pvApiCtx, 1, 1); + CheckOutputArgument(pvApiCtx, 1, 2) ; + sciprint("here1"); + retrieveImage(image, 1); +// sciErr = getVarAddressFromPosition(pvApiCtx,2,&piAddr2); +// if (sciErr.iErr) +// { +// printError(&sciErr, 0); +// return 0; +// } +// intErr = getScalarDouble(pvApiCtx, piAddr2, &Rmin); +// if(intErr) +// { +// return intErr; +// } +// if(Rmin!= round(Rmin) || Rmin<=0) +// { +// sciprint("The value of minium Radius must be an integer\n"); +// return 0; +// } +// if(Rmin<5) +// { +// sciprint("The value of minium Radius too small\n"); +// return 0; +// } +// sciErr = getVarAddressFromPosition(pvApiCtx,3,&piAddr3); +// if (sciErr.iErr) +// { +// printError(&sciErr, 0); +// return 0; +// } +// intErr = getScalarDouble(pvApiCtx, piAddr3, &Rmax); +// if(intErr) +// { +// return intErr; +// } +// if(Rmax!= round(Rmax) || Rmax<=0) +// { +// sciprint("The value of maximum Radius must be an integer\n"); +// return 0; +// } + sciprint("here2"); + cvtColor(image,src_gray,CV_BGR2GRAY); + GaussianBlur( src_gray, src_gray, Size(9, 9), 2, 2 ); + vector circles; + HoughCircles( src_gray, circles, CV_HOUGH_GRADIENT, 1, src_gray.rows/8, 200, 100,0,0); + sciprint("here3"); + int k=circles.size(); + if (k==0) + {sciprint("zero");} + else if (k==1) + {sciprint("one");} + else if (k==2) + {sciprint("two");} + else if (k==3) + {sciprint("three");} + else + {sciprint(">3");} + double *radius=NULL; + radius=( double *)malloc(sizeof(double)*k); + double *c1=NULL; + c1=( double *)malloc(sizeof(double)*k); + double *c2=NULL; + c2=( double *)malloc(sizeof(double)*k); + sciprint("here4"); + for( size_t i= 0; i < circles.size(); i++ ) + { + c1[i]=cvRound(circles[i][0]); + cout< +#include"opencv2/core/core.hpp" +#include"opencv2/highgui/highgui.hpp" +#include"opencv2/opencv.hpp" +#include"opencv2/shape/shape_transformer.hpp" +#include"opencv2/shape.hpp" +#include"opencv2/imgcodecs.hpp" +#include"opencv2/imgproc/imgproc.hpp" +#include"opencv2/features2d/features2d.hpp" +#include"opencv2/core/utility.hpp" +#include +#include +#include + +using namespace cv; +using namespace std; +extern "C" +{ + #include "api_scilab.h" + #include "Scierror.h" + #include "BOOL.h" + #include + #include "sciprint.h" + #include "../common.h" + + int opencv_iminpaint(char *fname, unsigned long fname_len) + { + //Declaring Variables + SciErr sciErr; + + Mat img1,img2,outputImage; + + int *piAddr3 = NULL; + int intErr3 = 0; + double radius = 5; + + int *piAddr4 = NULL; + int intErr4 = 0; + double methodNum=0; + int *addvartwo=NULL; + + CheckInputArgument(pvApiCtx, 4, 4);//Checking the input arguments + CheckOutputArgument(pvApiCtx, 1, 1);//Checking the output arguments + + + //Getting argument #3 + sciErr = getVarAddressFromPosition(pvApiCtx, 3, &piAddr3); + if(sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + intErr3 = getScalarDouble(pvApiCtx, piAddr3, &radius); + if(intErr3) + { + return intErr3; + } + //Getting argument #4 + sciErr = getVarAddressFromPosition(pvApiCtx, 4, &piAddr4); + if(sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + intErr4 = getScalarDouble(pvApiCtx,piAddr4, &methodNum); + if(intErr4) + { + return intErr4; + } + try + { + retrieveImage(img1,1);//Retrieving the source image + img1.convertTo(img1,CV_8U);//Converting the image to 8-bit image + + + + retrieveImage(img2,2);//Retrieving the mask + img2.convertTo(img2,CV_8U);//Converting the mask + + if(methodNum==1) + inpaint(img1,img2,outputImage,radius,INPAINT_NS);//Calling the opencv inpaint function with method inpaint_ns + else if(methodNum==2) + inpaint(img1,img2,outputImage,radius,INPAINT_TELEA);//Calling the opencv inpaint function with method inpaint_telea + + } + catch(Exception &e) + { + const char* err=e.what(); + sciprint("%s",err); + } + //Assigning the output to be displayed on scilab console + string tempstring = type2str(outputImage.type()); + char* checker = (char *)malloc(tempstring.size() + 1); + memcpy(checker, tempstring.c_str(), tempstring.size() + 1); + returnImage(checker,outputImage,1); + AssignOutputVariable(pvApiCtx, 1) = nbInputArgument(pvApiCtx) + 1; + ReturnArguments(pvApiCtx); + } +} diff --git a/sci_gateway/cpp/opencv_immultiply.cpp b/sci_gateway/cpp/opencv_immultiply.cpp new file mode 100644 index 0000000..863a1b7 --- /dev/null +++ b/sci_gateway/cpp/opencv_immultiply.cpp @@ -0,0 +1,71 @@ +/******************************************************** +Function :immultiply +Syntax :C=immultiply(A,B) +Author : Tess Zacharias, Shubham Lohakare +********************************************************/ + +#include +#include "opencv2/core/core.hpp" +#include "opencv2/highgui/highgui.hpp" +#include "opencv2/opencv.hpp" +#include +#include "string.h" +using namespace cv; +using namespace std; +extern "C" +{ + #include "api_scilab.h" + #include "Scierror.h" + #include "BOOL.h" + #include + #include "sciprint.h" + #include "../common.h" + int opencv_immultiply(char *fname, unsigned long fname_len) + { + //Declaring variables + SciErr sciErr; + Mat A,B,C; + int* piAddr2=NULL; + int iType = 0; + int iRet = 0; + double value= 0; + + CheckInputArgument(pvApiCtx, 2, 2);//Checking Input arguments + CheckOutputArgument(pvApiCtx, 1, 1);//Checking Output arguments + + retrieveImage(A,1);//Retrieving the first input + + sciErr =getVarAddressFromPosition(pvApiCtx,2,&piAddr2); + sciErr = getVarType(pvApiCtx, piAddr2, &iType); + if(iType==sci_list)//Checking the type of 2nd argument + { + retrieveImage(B,2); + Size s1=A.size(); + Size s2=B.size(); + + multiply(A,B,C);//Calling the opencv function + } + else + { + if(isDoubleType(pvApiCtx, piAddr2)) + { + if(isScalar(pvApiCtx, piAddr2)) + { + iRet = getScalarDouble(pvApiCtx, piAddr2, &value); + } + } + C=A*value; + } + //Assigning the output to be returned to scilab console + int temp = nbInputArgument(pvApiCtx) + 1; + string tempstring = type2str(C.type()); + char *checker; + checker = (char *)malloc(tempstring.size() + 1); + memcpy(checker, tempstring.c_str(), tempstring.size() + 1); + returnImage(checker,C,1); + free(checker); + AssignOutputVariable(pvApiCtx, 1) = nbInputArgument(pvApiCtx) + 1; + ReturnArguments(pvApiCtx); + return 0; + } +} diff --git a/sci_gateway/cpp/opencv_imread.cpp b/sci_gateway/cpp/opencv_imread.cpp new file mode 100644 index 0000000..5e28bd1 --- /dev/null +++ b/sci_gateway/cpp/opencv_imread.cpp @@ -0,0 +1,215 @@ +/*************************************************** +Authors : Sukul Bagai and Nihar Rao +***************************************************/ + +#include +#include "opencv2/core/core.hpp" +#include "opencv2/highgui/highgui.hpp" +#include "opencv2/opencv.hpp" +#include +#include +using namespace cv; +using namespace std; +extern "C" +{ + #include "api_scilab.h" + #include "Scierror.h" + #include "BOOL.h" + #include + #include "sciprint.h" + #include "../common.h" + #include "../common.cpp" + + bool file_exists_check( char *name) { + struct stat buffer; + return (stat (name, &buffer) == 0); + } + +int opencv_imread(char *fname, unsigned long fname_len) +{ + + SciErr sciErr; + int iLen = 0; + //variable info + int iRows = 0; + int iCols = 0; + int piRows = 0; + int piCols = 0; + int *piAddr = NULL; + int *piLen = NULL; + char **pstData = NULL; + int **pstData1 = NULL; + int i,j,k=0; + int intErr; + double val; + Mat img; + + + //Checking number of input and output arguments (enviromnet variable, min arguments, max arguments) + CheckInputArgument(pvApiCtx, 1, 2); + CheckOutputArgument(pvApiCtx, 1, 1) ; + + //get number of input arguments + int n=*getNbInputArgument(pvApiCtx); + + // get Address of inputs + sciErr = getVarAddressFromPosition(pvApiCtx, 1, &piAddr); + + if (sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + + + //Now, we will retrieve the string from the input parameter. For this, we will require 3 calls + //first call to retrieve dimensions + sciErr = getMatrixOfString(pvApiCtx, piAddr, &iRows, &iCols, NULL, NULL); + if(sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + piLen = (int*)malloc(sizeof(int) * iRows * iCols); + //second call to retrieve length of each string + sciErr = getMatrixOfString(pvApiCtx, piAddr, &iRows, &iCols, piLen, NULL); + if(sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + + pstData = (char**)malloc(sizeof(char*) * iRows * iCols); + for(i = 0 ; i < iRows * iCols ; i++) + { + pstData[i] = (char*)malloc(sizeof(char) * (piLen[i] + 1));//+ 1 for null termination + } + //third call to retrieve data + sciErr = getMatrixOfString(pvApiCtx, piAddr, &iRows, &iCols, piLen, pstData); + if(sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + //read 2nd argument if user has passed 2 arguments + if(n==2) + { + sciErr = getVarAddressFromPosition(pvApiCtx,2,&piAddr); + if (sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + intErr = getScalarDouble(pvApiCtx, piAddr ,&val); + if(intErr) + { + Scierror(999,"Error: there was an error while reading the second argument \n"); + return 0; + + } + } + int d=(int)val; + + if(!file_exists_check(pstData[0])) + { + + Scierror(999, "Error: the input image not found!.Please enter correct path!\n"); + return 0; + } + + + + try{ + + + + if(n==2) + { + switch(d) + { + + case -1: + img = imread(pstData[0],CV_LOAD_IMAGE_UNCHANGED); + break; + case 0: + img = imread(pstData[0],CV_LOAD_IMAGE_GRAYSCALE); + break; + case 1: + img = imread(pstData[0],CV_LOAD_IMAGE_COLOR); + break; + case 2: + img = imread(pstData[0],2); + break; + case 4: + img = imread(pstData[0],4); + break; + case 8: + img = imread(pstData[0],8); + break; + case 16: + img = imread(pstData[0],16); + break; + case 17: + img = imread(pstData[0],16); + break; + case 32: + img = imread(pstData[0],32); + break; + case 33: + img = imread(pstData[0],33); + break; + case 64: + img = imread(pstData[0],64); + break; + case 65: + img = imread(pstData[0],65); + break; + case 128: + img = imread(pstData[0],128); + break; + + } + + } + //one argument + else + { + + img = imread(pstData[0],CV_LOAD_IMAGE_UNCHANGED); + } + } + catch(cv::Exception& e) + { + + const char* err=e.what(); + Scierror(999,err); + + } + + + //wrong argument check + if(n==2 && img.empty()) + { + Scierror(999,"Error: the second argument is invalid or the image path is wrong!! \n"); + return 0; + + + } + + + + string tempstring = type2str(img.type()); + char *checker; + checker = (char *)malloc(tempstring.size() + 1); + memcpy(checker, tempstring.c_str(), tempstring.size() + 1); + returnImage(checker,img,1); + free(checker); + + //Assigning the list as the Output Variable + AssignOutputVariable(pvApiCtx, 1) = nbInputArgument(pvApiCtx) + 1; + //Returning the Output Variables as arguments to the Scilab environment + ReturnArguments(pvApiCtx); + return 0; +} +/* ==================================================================== */ +} diff --git a/sci_gateway/cpp/opencv_imresize.cpp b/sci_gateway/cpp/opencv_imresize.cpp new file mode 100644 index 0000000..190ab5e --- /dev/null +++ b/sci_gateway/cpp/opencv_imresize.cpp @@ -0,0 +1,94 @@ +/******************************************************** +Author: Sukul Bagai +********************************************************/ + +#include +#include "opencv2/core/core.hpp" +#include "opencv2/highgui/highgui.hpp" +#include "opencv2/opencv.hpp" +#include +using namespace cv; +using namespace std; +extern "C" +{ + #include "api_scilab.h" + #include "Scierror.h" + #include "BOOL.h" + #include + #include "sciprint.h" + #include "../common.h" + + int opencv_imresize(char *fname, unsigned long fname_len) + { + SciErr sciErr; + int intErr = 0; + int iRows=0,iCols=0; + int *piAddr = NULL; + int *piAddrNew = NULL; + int *piAddr2 = NULL; + int *piAddr3 = NULL; + int i,j,k; + double alpha, beta; + + //checking input argument + CheckInputArgument(pvApiCtx, 3, 3); + CheckOutputArgument(pvApiCtx, 1, 1) ; + + Mat image; + retrieveImage(image, 1); + + //for new no. of rows + sciErr = getVarAddressFromPosition(pvApiCtx,2,&piAddr2); + if (sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + intErr = getScalarDouble(pvApiCtx, piAddr2, &alpha); + if(sciErr.iErr) + { + return intErr; + } + + //for new no. of columns + sciErr = getVarAddressFromPosition(pvApiCtx,3,&piAddr3); + if (sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + intErr = getScalarDouble(pvApiCtx, piAddr3, &beta); + if(sciErr.iErr) + { + return intErr; + } + + + Mat new_image; + Size size(alpha, beta); + + if(alpha<=0 || beta<=0) + { + sciprint("Invalid new size\n"); + return 0; + } + //resizes the image to new_image to the size given by the user + resize(image,new_image,size); + + int temp = nbInputArgument(pvApiCtx) + 1; + string tempstring = type2str(new_image.type()); + char *checker; + checker = (char *)malloc(tempstring.size() + 1); + memcpy(checker, tempstring.c_str(), tempstring.size() + 1); + returnImage(checker,new_image,1); + free(checker); + + //Assigning the list as the Output Variable + AssignOutputVariable(pvApiCtx, 1) = nbInputArgument(pvApiCtx) + 1; + //Returning the Output Variables as arguments to the Scilab environment + ReturnArguments(pvApiCtx); + return 0; + + } +/* ==================================================================== */ +} diff --git a/sci_gateway/cpp/opencv_imrotate.cpp b/sci_gateway/cpp/opencv_imrotate.cpp new file mode 100644 index 0000000..d8b0ab2 --- /dev/null +++ b/sci_gateway/cpp/opencv_imrotate.cpp @@ -0,0 +1,133 @@ +/* ==================================================================== */ +/* Authors :Priyanka Hiranandani NIT Surat, Shubham Lohakare NITK Surathkal */ +/* ==================================================================== */ +/* Syntax : rotated_image=imrotate(sourcrimage,angle); + rotated_image=imrotate(sourceimage,angle,'crop'); + rotated_image=imrotate(sourceimage,angle,'loose'); */ +/* ==================================================================== */ +#include +#include "opencv2/core/core.hpp" +#include "opencv2/highgui/highgui.hpp" +#include "opencv2/opencv.hpp" +#include +#include +using namespace cv; +using namespace std; + extern "C" + { + #include "api_scilab.h" + #include "Scierror.h" + #include "BOOL.h" + #include + #include "../common.h" + int opencv_imrotate(char *fname, unsigned long fname_len) + { + // Error management variable + SciErr sciErr; + //variable info + int iRows = 0; + int iCols = 0; + int piRows = 0; + int piCols = 0; + int* piAddr = NULL; + int* piAddr2 = NULL; + int* piAddr3 = NULL; + int* piAddrNew = NULL; + int* piLen = NULL; + double angle; + char **pstData2 = NULL; + double *rrows; + double *rcols; + int error; + //function to check number of input variable + CheckInputArgument(pvApiCtx, 2, 3); + //function to check number of output variable + CheckOutputArgument(pvApiCtx, 1, 1); + + int n = *getNbInputArgument(pvApiCtx);//Getting the total number of input variables + + // get Address of first input + Mat src,dst; + retrieveImage(src,1); //Retrieving the first image + + sciErr = getVarAddressFromPosition(pvApiCtx,2,&piAddr2); + //checking for error if any + if (sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + //this function will fetch second argument i.e angle + error=getScalarDouble(pvApiCtx,piAddr2,&angle); + if(error!=0) + { + sciprint("error in retrieving second argument"); + } + if(n==2)//If number of input arguments are 2 + { + cv::Point2f pc(src.cols/2., src.rows/2.); + cv::Mat r = cv::getRotationMatrix2D(pc, angle, 1.0); + + cv::warpAffine(src, dst, r, src.size()); + } + if(n==3)//If number of arguments are 3 + { + //Getting the third variable which is the type of bounding box required + sciErr = getVarAddressFromPosition(pvApiCtx,3,&piAddr3); + sciErr = getMatrixOfString(pvApiCtx, piAddr3, &iRows, &iCols, NULL, NULL); + if(sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + piLen = (int*)malloc(sizeof(int) * iRows * iCols); + //second call to retrieve length of each string of first argument + sciErr = getMatrixOfString(pvApiCtx, piAddr3, &iRows, &iCols, piLen, NULL); + if(sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + pstData2 = (char**)malloc(sizeof(char*) * iRows * iCols); + for(int i = 0 ; i < iRows * iCols ; i++) + { + pstData2[i] = (char*)malloc(sizeof(char) * (piLen[i] + 1));//+ 1 for null termination + } + //third call to retrieve data of each string of first argument + sciErr = getMatrixOfString(pvApiCtx, piAddr3, &iRows, &iCols, piLen, pstData2); + if(sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + + if(!strcmp("crop",pstData2[0]))//If type of bounding box is crop + { + cv::Point2f pc(src.cols/2., src.rows/2.); + cv::Mat r = cv::getRotationMatrix2D(pc, angle, 1.0); + + cv::warpAffine(src, dst, r, src.size()); + } + else if(!strcmp("loose",pstData2[0]))//If type of bounding box is loose + { + cv::Point2f center(src.cols/2.0, src.rows/2.0); + cv::Mat rot = cv::getRotationMatrix2D(center, angle, 1.0); + // determine bounding rectangle + cv::Rect bbox = cv::RotatedRect(center,src.size(), angle).boundingRect(); + // adjust transformation matrix + rot.at(0,2) += bbox.width/2.0 - center.x; + rot.at(1,2) += bbox.height/2.0 - center.y; + + + cv::warpAffine(src, dst, rot, bbox.size()); + } + } + //The image which will be shown as output + string tempstring = type2str(dst.type()); + char* checker = (char *)malloc(tempstring.size() + 1); + memcpy(checker, tempstring.c_str(), tempstring.size() + 1); + returnImage(checker,dst,1); + AssignOutputVariable(pvApiCtx, 1) = nbInputArgument(pvApiCtx) + 1; + ReturnArguments(pvApiCtx); + } +} diff --git a/sci_gateway/cpp/opencv_imrotate.cpp~ b/sci_gateway/cpp/opencv_imrotate.cpp~ new file mode 100644 index 0000000..a2b0e54 --- /dev/null +++ b/sci_gateway/cpp/opencv_imrotate.cpp~ @@ -0,0 +1,81 @@ +/* ==================================================================== */ +/* Author :Priyanka Hiranandani NIT Surat */ +/* ==================================================================== */ +/* Syntax : rotated_image=imrotate(sourcrimage,angle); */ +/* ==================================================================== */ +#include +#include "opencv2/core/core.hpp" +#include "opencv2/highgui/highgui.hpp" +#include "opencv2/opencv.hpp" +#include +#include +using namespace cv; +using namespace std; + extern "C" + { + #include "api_scilab.h" + #include "Scierror.h" + #include "BOOL.h" + #include + #include "../common.h" + int imrotate(char *fname, unsigned long fname_len) + { + // Error management variable + SciErr sciErr; + //variable info + int iRows = 0; + int iCols = 0; + int piRows = 0; + int piCols = 0; + int* piAddr = NULL; + int* piAddr2 = NULL; + int* piAddr3 = NULL; + int* piAddrNew = NULL; + int* piLen = NULL; + double pstData; + int* pstData2 = NULL; + double *rrows; + double *rcols; + int error; + //function to check number of input variable + CheckInputArgument(pvApiCtx, 2, 2); + //function to check number of output variable + CheckOutputArgument(pvApiCtx, 1, 1); + // get Address of first input + Mat img; + retrieveImage(img,1); + //second argument + //fetching address of second argument + sciErr = getVarAddressFromPosition(pvApiCtx,2,&piAddr2); + //checking for error if any + if (sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + //this function will fetch second argument i.e angle + error=getScalarDouble(pvApiCtx,piAddr2,&pstData); + if(error!=0) + { + sciprint("error in retrieving second argument"); + } + //creating distination matrix + Mat dst; + //following set of functions for image rotation + Point2f pt((img.cols)/2., (img.rows)/2.); + Mat r1 = getRotationMatrix2D(pt, pstData, 1.0); + warpAffine(img, dst, r1, Size(dst.cols, dst.rows)); + //Since we need to pass a single pointer as an arguement, for a 2-D matrix, we define it in this manner + string tempstring = type2str(dst.type()); + char* checker = (char *)malloc(tempstring.size() + 1); + memcpy(checker, tempstring.c_str(), tempstring.size() + 1); + returnImage(checker,dst,1); + //returning output arguments + AssignOutputVariable(pvApiCtx, 1) = nbInputArgument(pvApiCtx) + 1; + ReturnArguments(pvApiCtx); + return 0; + + + + } +} diff --git a/sci_gateway/cpp/opencv_ind2gray.cpp b/sci_gateway/cpp/opencv_ind2gray.cpp new file mode 100644 index 0000000..77a8d35 --- /dev/null +++ b/sci_gateway/cpp/opencv_ind2gray.cpp @@ -0,0 +1,151 @@ +/******************************************************** +Author: Vinay, + Shubham Lohakare, NITK Surathkal + +Function: ind2gray(image, choice) +image: input image +choice: choice of the colormap which the user wants to apply +********************************************************/ + +#include +#include "opencv2/core/core.hpp" +#include "opencv2/highgui/highgui.hpp" +#include "opencv2/opencv.hpp" +#include +using namespace cv; +using namespace std; +extern "C" +{ + #include "api_scilab.h" + #include "Scierror.h" + #include "BOOL.h" + #include + #include "sciprint.h" + #include "../common.h" + + int opencv_ind2gray(char *fname, unsigned long fname_len) + { + + SciErr sciErr; + int intErr = 0; + int iRows=0,iCols=0; + int cRows=0,cCols=0; + int *piAddr = NULL; + int *piAddrNew = NULL; + +int *piAddr2 = NULL;//Variables for 2nd Input Argument + int intErr2 = 0; + double choice = 0; + //checking input argument + CheckInputArgument(pvApiCtx, 2, 2); + CheckOutputArgument(pvApiCtx, 1, 1) ; + + Mat image, imgcpy; + retrieveImage(image, 1); + image.convertTo(image,CV_8U); + + iRows = image.rows; + iCols = image.cols; + image.convertTo(imgcpy, CV_64F); + //cvtColor(image,image,CV_BGR2GRAY); + Mat cmap, cmapcpy; + // to get the argument #2 + sciErr = getVarAddressFromPosition( pvApiCtx, 2, &piAddr2); + if(sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + + intErr2 = getScalarDouble(pvApiCtx, piAddr2, &choice); + if(intErr2) + { + return intErr2; + } + + if(choice==0) + applyColorMap(image, cmap, COLORMAP_AUTUMN); + + else if(choice==1) + applyColorMap(image, cmap, COLORMAP_BONE); + + else if(choice==2) + applyColorMap(image, cmap, COLORMAP_JET); + + else if(choice==3) + applyColorMap(image, cmap, COLORMAP_WINTER); + + else if(choice==4) + applyColorMap(image, cmap, COLORMAP_RAINBOW); + + else if(choice==5) + applyColorMap(image, cmap, COLORMAP_OCEAN); + + else if(choice==6) + applyColorMap(image, cmap, COLORMAP_SUMMER); + + else if(choice==7) + applyColorMap(image, cmap, COLORMAP_SPRING); + + else if(choice==8) + applyColorMap(image, cmap, COLORMAP_COOL); + + else if(choice==9) + applyColorMap(image, cmap, COLORMAP_HSV); + + else if(choice==10) + applyColorMap(image, cmap, COLORMAP_PINK); + + else if(choice==11) + applyColorMap(image, cmap, COLORMAP_HOT); + + else if(choice==12) + applyColorMap(image, cmap, COLORMAP_PARULA); + + else + printf("Wrong input of choice"); + + + cRows = cmap.rows; + cCols = cmap.cols; + cmap.convertTo(cmapcpy, CV_64F); + + /*for (int i=0; i(i,j)<0 || cmapcpy.at(i,j)>1) { + sciprint("Invalid colormap"); + return 0; + } + } + }*/ + + Mat gray = Mat::zeros(image.size(), CV_64F); + + + for (int i=0; i(i, j); + if (temp >= cRows) { + temp = cRows - 1; + } + if (!true) { + if (temp!=0) {temp-=1;} + } + gray.at(i,j) = (0.2989 * cmapcpy.at(temp, 0) + 0.5870 * cmapcpy.at(temp, 1) + 0.1140 * cmapcpy.at(temp, 2)) ; + + } + } + + Mat grayimage; + gray.convertTo(grayimage, CV_64F); + string tempstring = type2str(grayimage.type());//Returning the image to Scilab console + char* checker = (char *)malloc(tempstring.size() + 1); + memcpy(checker, tempstring.c_str(), tempstring.size() + 1); + returnImage(checker,grayimage,1); + AssignOutputVariable(pvApiCtx, 1) = nbInputArgument(pvApiCtx) + 1; + ReturnArguments(pvApiCtx); + return 0; + + } +/* ==================================================================== */ +} diff --git a/sci_gateway/cpp/opencv_ind2rgb.cpp b/sci_gateway/cpp/opencv_ind2rgb.cpp new file mode 100644 index 0000000..c7ff043 --- /dev/null +++ b/sci_gateway/cpp/opencv_ind2rgb.cpp @@ -0,0 +1,182 @@ +/******************************************************** +Author: Vinay + +Function: ind2rgb(image, colormap) +********************************************************/ + +#include +#include "opencv2/core/core.hpp" +#include "opencv2/highgui/highgui.hpp" +#include "opencv2/opencv.hpp" +#include +using namespace cv; +using namespace std; +extern "C" +{ + #include "api_scilab.h" + #include "Scierror.h" + #include "BOOL.h" + #include + #include "sciprint.h" + #include "../common.h" + + int opencv_ind2rgb(char *fname, unsigned long fname_len) + { + + SciErr sciErr; + int intErr = 0; + int iRows=0,iCols=0; + int cRows=0,cCols=0; + int *piAddr = NULL; + int *piAddrNew = NULL; + + + int *piAddr2 = NULL;//Variables for 2nd Input Argument + int intErr2 = 0; + double choice = 0; + //unsigned short int *image = NULL; + double *map = NULL; + int i,j,k; + double x, y, width, height; + + //checking input argument + CheckInputArgument(pvApiCtx, 2, 2); + CheckOutputArgument(pvApiCtx, 1, 1) ; + + Mat image, imgcpy; + retrieveImage(image, 1); + + iRows = image.rows; + iCols = image.cols; + image.convertTo(imgcpy, CV_64F); + + Mat cmap, cmapcpy; + sciErr = getVarAddressFromPosition( pvApiCtx, 2, &piAddr2); + if(sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + + intErr2 = getScalarDouble(pvApiCtx, piAddr2, &choice); + if(intErr2) + { + return intErr2; + } + + if(choice==0) + applyColorMap(image, cmap, COLORMAP_AUTUMN); + + else if(choice==1) + applyColorMap(image, cmap, COLORMAP_BONE); + + else if(choice==2) + applyColorMap(image, cmap, COLORMAP_JET); + + else if(choice==3) + applyColorMap(image, cmap, COLORMAP_WINTER); + + else if(choice==4) + applyColorMap(image, cmap, COLORMAP_RAINBOW); + + else if(choice==5) + applyColorMap(image, cmap, COLORMAP_OCEAN); + + else if(choice==6) + applyColorMap(image, cmap, COLORMAP_SUMMER); + + else if(choice==7) + applyColorMap(image, cmap, COLORMAP_SPRING); + + else if(choice==8) + applyColorMap(image, cmap, COLORMAP_COOL); + + else if(choice==9) + applyColorMap(image, cmap, COLORMAP_HSV); + + else if(choice==10) + applyColorMap(image, cmap, COLORMAP_PINK); + + else if(choice==11) + applyColorMap(image, cmap, COLORMAP_HOT); + + else if(choice==12) + applyColorMap(image, cmap, COLORMAP_PARULA); + + else + printf("Wrong input of choice"); + + cRows = cmap.rows; + cCols = cmap.cols; + cmap.convertTo(cmapcpy, CV_64F); + + + + + double *r,*g,*b; + r=(double *)malloc(sizeof(double)*iRows*iCols); + g=(double *)malloc(sizeof(double)*iRows*iCols); + b=(double *)malloc(sizeof(double)*iRows*iCols); + int m = 0; + + + for (int i=0; i(i, j); + if (temp >= cRows) { + temp = cRows - 1; + } + if (!true) { + if (temp!=0) {temp-=1;} + } + r[i + iRows*j] = cmapcpy.at(temp, 0); + g[i + iRows*j] = cmapcpy.at(temp, 1); + b[i + iRows*j] = cmapcpy.at(temp, 2); + } + } + + sciErr = createList(pvApiCtx, nbInputArgument(pvApiCtx) + 1, 3, &piAddrNew); + if(sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + + + //Adding the R value matrix to the list + //Syntax : createMatrixOfInteger32InList(void* _pvCtx, int _iVar, int* _piParent, int _iItemPos, int _iRows, int _iCols, const int* _piData) + sciErr = createMatrixOfDoubleInList(pvApiCtx, nbInputArgument(pvApiCtx)+1 , piAddrNew, 1,iRows, iCols, r); + free(r); + if(sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + + //Adding the G value matrix to the list + sciErr = createMatrixOfDoubleInList(pvApiCtx, nbInputArgument(pvApiCtx)+1 , piAddrNew, 2,iCols, iRows, g); + free(g); + if(sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + + //Adding the B value matrix to the list + sciErr = createMatrixOfDoubleInList(pvApiCtx, nbInputArgument(pvApiCtx)+1 , piAddrNew, 3, iCols, iRows, b); + free(b); + if(sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + + + AssignOutputVariable(pvApiCtx, 1) = nbInputArgument(pvApiCtx) + 1; + //Returning the Output Variables as arguments to the Scilab environment + ReturnArguments(pvApiCtx); + return 0; + + } +/* ==================================================================== */ +} diff --git a/sci_gateway/cpp/opencv_indexImages.cpp b/sci_gateway/cpp/opencv_indexImages.cpp new file mode 100644 index 0000000..28ce9b7 --- /dev/null +++ b/sci_gateway/cpp/opencv_indexImages.cpp @@ -0,0 +1,669 @@ +/**************************************************************************************** +* Author: Umang Agrawal * +* Code: indexImages.cpp * +* Function Call: indexImage = indexImages( Image_Set, Bag, Optional Arguments) * +* Optional Argument: Name Value * +* Verbose Bool(1 or 0) * +* SaveFeatureLocations Bool(1 or 0) * +****************************************************************************************/ +#include +#include +#include +#include +#include "opencv2/core/core.hpp" +#include "opencv2/highgui/highgui.hpp" +#include "opencv2/imgproc/imgproc.hpp" +#include "opencv2/features2d.hpp" +#include "opencv2/xfeatures2d.hpp" + + +using namespace cv; +using namespace cv::xfeatures2d; +using namespace std; + +extern "C" +{ + #include "api_scilab.h" + #include "Scierror.h" + #include "BOOL.h" + #include + #include "sciprint.h" + #include "../common.h" + + bool response(const KeyPoint& p1, const KeyPoint& p2) { + return p1.response > p2.response; + } + + int opencv_indexImages(char *fname, unsigned long fname_len) + { + SciErr sciErr; + + int *piAddr = NULL; + int *piAddr1 = NULL; + int *piAddr2 = NULL; + int *piAddr3 = NULL; + int *piAddr4 = NULL; + int *piChild = NULL; + int *piGrandChild = NULL; + int iRows, iCols; + int *piLen = NULL; + char **pstData = NULL; + char *objectType = "invertedImageIndex"; + char **description = NULL; + char ***location = NULL; + int *count = NULL; + int descriptionCount; + char **arg = NULL; + char **filePath = NULL; + + int inp_params = 0; + char *bagOfFeaturesLocation = NULL; + double *upright_bag = NULL; + double *strength_bag = NULL; + double *vocab_size_bag = NULL; + int count_ver = 0, count_save = 0; + double save = 1; + double verbose = 1; + int upright = 1; + int vocab_size = 500; + double strength = 0.8; + + vector key_size_vector; + double *wordFrequency = NULL; + double ***ImageWords = NULL; + int indx; + + Mat image; + Mat dictionary; + Mat featuresUnclustered; + Mat feature_des; + Mat des_matched; + Mat hist; + vector keypoints; + vector valid_key; + vector< vector > clusterID; + int key_size; + int v_key_size; + + CheckInputArgument(pvApiCtx, 1, 6); //Check on Number of Input Arguments + CheckOutputArgument(pvApiCtx, 1, 1); //Check on Number of Output Arguments + + sciErr = getVarAddressFromPosition(pvApiCtx, 1, &piAddr1); + if (sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + if(!isListType(pvApiCtx, piAddr1)) + { + Scierror(999, "Error: Invalid first argument. List Expected.\n"); + return 0; + } + sciErr = getMatrixOfStringInList(pvApiCtx, piAddr1, 1, &iRows, &iCols, NULL, NULL); + if(sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + piLen = (int*)malloc(sizeof(int) * iRows * iCols); + sciErr = getMatrixOfStringInList(pvApiCtx, piAddr1, 1, &iRows, &iCols, piLen, NULL); + if(sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + pstData = (char**)malloc(sizeof(char*) * iRows * iCols); + for(int iter = 0 ; iter < iRows * iCols ; iter++) + { + pstData[iter] = (char*)malloc(sizeof(char) * (piLen[iter] + 1));//+ 1 for null termination + } + sciErr = getMatrixOfStringInList(pvApiCtx, piAddr1, 1, &iRows, &iCols, piLen, pstData); + if(sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + + if(!(strcmp(pstData[0],"imageSet")==0)) + { + Scierror(999, "Error: The input argument 1 is not of type imageSet.\n"); + return 0; + } + + // Extracting Description attribute of input argument + sciErr = getMatrixOfStringInList(pvApiCtx, piAddr1, 2, &iRows, &iCols, NULL, NULL); + if(sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + if( iRows!= 1 ) + { + Scierror(999,"Expecting an image Set with single type of Images.\n"); + return 0; + } + piLen = (int*)malloc(sizeof(int) * iRows * iCols); + sciErr = getMatrixOfStringInList(pvApiCtx, piAddr1, 2, &iRows, &iCols, piLen, NULL); + if(sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + description = (char**)malloc(sizeof(char*) * iRows * iCols); + for(int iter = 0 ; iter < iRows * iCols ; iter++) + { + description[iter] = (char*)malloc(sizeof(char) * (piLen[iter] + 1));//+ 1 for null termination + } + sciErr = getMatrixOfStringInList(pvApiCtx, piAddr1, 2, &iRows, &iCols, piLen, description); + if(sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + descriptionCount = iRows; + + // Extracting Count attribute of input argument + sciErr = getMatrixOfInteger32InList(pvApiCtx, piAddr1, 3, &iRows, &iCols, &count); + if(sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + if( iRows!= 1 ) + { + Scierror(999,"Expecting an image Set with single type of Images.\n"); + return 0; + } + location = (char***) malloc(sizeof(char**) * descriptionCount); + sciErr = getListItemAddress(pvApiCtx, piAddr1, 4, &piChild); + if(sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + for(int iter = 1; iter<=descriptionCount; iter++) + { + sciErr = getMatrixOfStringInList(pvApiCtx, piChild, iter, &iRows, &iCols, NULL, NULL); + if(sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + piLen = (int*)malloc(sizeof(int) * iRows * iCols); + sciErr = getMatrixOfStringInList(pvApiCtx, piChild, iter, &iRows, &iCols, piLen, NULL); + if(sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + location[iter-1] = (char**)malloc(sizeof(char*) * iRows * iCols); + for(int colIter = 0 ; colIter < iRows * iCols ; colIter++) + { + location[iter-1][colIter] = (char*)malloc(sizeof(char) * (piLen[colIter] + 1));//+ 1 for null termination + } + sciErr = getMatrixOfStringInList(pvApiCtx, piChild, iter, &iRows, &iCols, piLen, location[iter-1]); + if(sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + } + +//.............................................................................................................. + inp_params = *getNbInputArgument(pvApiCtx); + if( inp_params>=2 ) + { + sciErr = getVarAddressFromPosition(pvApiCtx, 2, &piAddr2); + if (sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + if(!isListType(pvApiCtx, piAddr2)) + { + Scierror(999, "Error: Invalid first argument. List Expected.\n"); + return 0; + } + sciErr = getMatrixOfStringInList(pvApiCtx, piAddr2, 1, &iRows, &iCols, NULL, NULL); + if(sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + piLen = (int*)malloc(sizeof(int) * iRows * iCols); + sciErr = getMatrixOfStringInList(pvApiCtx, piAddr2, 1, &iRows, &iCols, piLen, NULL); + if(sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + pstData = (char**)malloc(sizeof(char*) * iRows * iCols); + for(int iter = 0 ; iter < iRows * iCols ; iter++) + { + pstData[iter] = (char*)malloc(sizeof(char) * (piLen[iter] + 1));//+ 1 for null termination + } + sciErr = getMatrixOfStringInList(pvApiCtx, piAddr2, 1, &iRows, &iCols, piLen, pstData); + if(sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + if(!(strcmp(pstData[0],"bagOfFeatures")==0)) + { + Scierror(999, "Error: The input argument 2 is not of type bagOfFeatures.\n"); + return 0; + } + sciErr = getMatrixOfStringInList(pvApiCtx, piAddr2, 2, &iRows, &iCols, NULL, NULL); + if(sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + piLen = (int*)malloc(sizeof(int) * iRows * iCols); + sciErr = getMatrixOfStringInList(pvApiCtx, piAddr2, 2, &iRows, &iCols, piLen, NULL); + if(sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + pstData = (char**)malloc(sizeof(char*) * iRows * iCols); + for(int iter = 0 ; iter < iRows * iCols ; iter++) + { + pstData[iter] = (char*)malloc(sizeof(char) * (piLen[iter] + 1));//+ 1 for null termination + } + sciErr = getMatrixOfStringInList(pvApiCtx, piAddr2, 2, &iRows, &iCols, piLen, pstData); + if(sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + bagOfFeaturesLocation = pstData[0]; + sciErr = getMatrixOfDoubleInList(pvApiCtx, piAddr2, 3, &iRows, &iCols, &vocab_size_bag); + if(sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + sciErr = getMatrixOfDoubleInList(pvApiCtx, piAddr2, 4, &iRows, &iCols, &strength_bag); + if(sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + sciErr = getMatrixOfDoubleInList(pvApiCtx, piAddr2, 5, &iRows, &iCols, &upright_bag); + if(sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + upright = int(upright_bag[0]); + vocab_size = int(vocab_size_bag[0]); + strength = strength_bag[0]; + FileStorage fs(bagOfFeaturesLocation, FileStorage::READ); + fs["dictionary"] >> dictionary; + fs.release(); + +//................................................................................................................ + for( int i=3; i<=inp_params; i++) + { + if( inp_params%2 != 0) + { + Scierror(999,"Either Argument Name or its Value missing\n"); + return 0; + } + sciErr = getVarAddressFromPosition(pvApiCtx, i, &piAddr3); + if(sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + //Check for Argument type + if( !isStringType(pvApiCtx, piAddr3)) + { + Scierror(999, "%s: Wrong type of argument for Name of Optional Argument. A string is expected.\n", fname); + return 0; + } + //Matrix of Stings + sciErr = getMatrixOfString(pvApiCtx, piAddr3, &iRows, &iCols, NULL, NULL); + if(sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + piLen = (int*)malloc(sizeof(int) * iRows * iCols); + //second call to retrieve the length of the string + sciErr = getMatrixOfString(pvApiCtx, piAddr3, &iRows, &iCols, piLen, NULL); + if(sciErr.iErr) + { + printError(&sciErr, 0); + free(piLen); + return 0; + } + arg = (char**)malloc(sizeof(char*) * iRows * iCols); + for(int j=0;j< iRows * iCols; j++) + { + arg[j] = (char*)malloc(sizeof(char) * (piLen[j] + 1)); + } + + //third call to retrieve data + sciErr = getMatrixOfString(pvApiCtx, piAddr3, &iRows, &iCols, piLen, arg); + if(sciErr.iErr) + { + printError(&sciErr, 0); + free(piLen); + free(arg); + return 0; + } + + if(strcmp(arg[0],"Verbose") == 0) + { + if( count_ver != 0) + { + Scierror(999,"Verbose has been called twice.\n"); + return 0; + } + free(arg); + free(piLen); + sciErr = getVarAddressFromPosition(pvApiCtx, i+1, &piAddr4); + if(sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + if( !(isDoubleType(pvApiCtx, piAddr4)||isIntegerType(pvApiCtx, piAddr4))) + { + Scierror(999,"Not a valid type of value for Verbose.\n"); + return 0; + } + //Reading the Value of the argument + if(getScalarDouble(pvApiCtx, piAddr4, &verbose)) + { + Scierror(999,"Not a valid type of value for Verbose.\n"); + return 0; + } + if( !(verbose == 1|| verbose == 0) ) + { + Scierror(999,"Enter a valid value for Verbose (Either 0 or 1)\n"); + return 0; + } + i++; + count_ver += 1; + } + else if(strcmp(arg[0],"SaveFeatureLocations") == 0) + { + if( count_save != 0) + { + Scierror(999,"SaveFeatureLoactions has been called twice.\n"); + return 0; + } + free(arg); + free(piLen); + sciErr = getVarAddressFromPosition(pvApiCtx, i+1, &piAddr4); + if(sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + if( !(isDoubleType(pvApiCtx, piAddr4)||isIntegerType(pvApiCtx, piAddr4))) + { + Scierror(999,"Not a valid type of value for SaveFeatureLoactions.\n"); + return 0; + } + //Reading the Value of the argument + if(getScalarDouble(pvApiCtx, piAddr4, &save)) + { + Scierror(999,"Not a valid type of value for SaveFeatureLoactions.\n"); + return 0; + } + if( !(save == 1|| save == 0) ) + { + Scierror(999,"Enter a valid value for SaveFeatureLoactions (Either 0 or 1)\n"); + return 0; + } + i++; + count_save += 1; + } + else + { + Scierror(999,"Invalid Argument Name\n"); + return 0; + } + } + } + + if(int(verbose)) + { + sciprint("Creating an Inverted image Index Using Bag-Of-Features.\n"); + sciprint("--------------------------------------------------------\n"); + } + + if( inp_params == 1) + { + bagOfFeaturesLocation = "Bag-Of-Features.yml"; + Ptr detector = SURF::create( 400, 4, 2, 1, int(upright) ); + Ptr extractor = SURF::create(400, 4, 2, 1, int(upright)); + + if(int(verbose)) + { + sciprint("Creating Bag-Of-Features from %d image sets.\n\n",descriptionCount); + for(int i=0; idetect(image, keypoints); + sort(keypoints.begin(), keypoints.end(), response); + for( int k=0; k<(keypoints.size()*strength); k++) + { + valid_key.push_back(keypoints[k]); + } + extractor->compute(image, valid_key, feature_des); + featuresUnclustered.push_back(feature_des); + key_size += keypoints.size(); + v_key_size += valid_key.size(); + } + if(int(verbose)) + { + sciprint("done. Extracted %d features.\n",key_size); + sciprint("Keeping %f percent of the strongest features.\n",(strength)*100); + sciprint("Net Extracted features : %d\n\n",v_key_size); + } + } + + vocab_size = featuresUnclustered.rows; + TermCriteria tc(CV_TERMCRIT_ITER, 100, 0.001); + int retries = 3; + BOWKMeansTrainer bowTrainer(int(vocab_size), tc, retries, KMEANS_PP_CENTERS); + + if(int(verbose)) + { + sciprint("Using K-Means Clustering to create a %d word visual vocabulary.\n",int(vocab_size)); + sciprint("Number of Features : %d\n",featuresUnclustered.rows); + sciprint("Number of Clusters : %d\n\n",int(vocab_size)); + } + + dictionary = bowTrainer.cluster(featuresUnclustered); + + if(int(verbose)) + sciprint("Finished creating Bag-Of-Features\n"); + + FileStorage fs(bagOfFeaturesLocation, FileStorage::WRITE); + fs<<"dictionary"< detector = SURF::create( 400, 4, 2, 1, int(upright) ); + Ptr extractor = SURF::create(400, 4, 2, 1, int(upright)); + for( int i=0; idetect(image, keypoints); + extractor->compute(image, keypoints,feature_des); + + key_size_vector.push_back(keypoints.size()); + ImageWords[i] = (double**)malloc(sizeof(double*)*4*1); + ImageWords[i][0] = (double*)malloc(sizeof(double)*keypoints.size()*1); + ImageWords[i][1] = (double*)malloc(sizeof(double)*keypoints.size()*2); + ImageWords[i][2] = (double*)malloc(sizeof(double)*1); + ImageWords[i][3] = (double*)malloc(sizeof(double)*1); + + ImageWords[i][2][0] = vocab_size; + ImageWords[i][3][0] = keypoints.size(); + + for( int j=0; j +#include"opencv2/core/core.hpp" +#include"opencv2/highgui/highgui.hpp" +#include"opencv2/opencv.hpp" +#include"opencv2/shape/shape_transformer.hpp" +#include"opencv2/shape.hpp" +#include"opencv2/imgcodecs.hpp" +#include"opencv2/imgproc/imgproc.hpp" +#include"opencv2/features2d/features2d.hpp" +#include"opencv2/core/utility.hpp" +#include +#include +#include + +using namespace cv; +using namespace std; +extern "C" +{ + #include "api_scilab.h" + #include "Scierror.h" + #include "BOOL.h" + #include + #include "sciprint.h" + #include "../common.h" + + int opencv_inpaintmask(char *fname, unsigned long fname_len) + { + SciErr sciErr; + int i; + + Mat img1,img; + Mat inpainted; + /*int *piAddr2 = NULL;//Variables for 3rd argument + int intErr2 = 0; + double radius = 5; + + int *piAddr3 = NULL;//Variables for 4th argument + int intErr3 = 0; + double methodNum=0; + */ + CheckInputArgument(pvApiCtx, 1, 1);//Checking the number of input arguments + CheckOutputArgument(pvApiCtx, 1, 1);//Checking the number of output arguments + + //To get the argument #2 + /*sciErr = getVarAddressFromPosition(pvApiCtx, 2, &piAddr2); + if(sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + intErr2 = getScalarDouble(pvApiCtx, piAddr2, &radius); + if(intErr2) + { + return intErr2; + } + + //To get the argument #3 + sciErr = getVarAddressFromPosition(pvApiCtx, 3, &piAddr3); + if(sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + intErr3 = getScalarDouble(pvApiCtx,piAddr3, &methodNum); + if(intErr3) + { + return intErr3; + } + */ + try + { + retrieveImage(img1,1);//Retrieving the input image + img1.convertTo(img1,CV_8U);//Converting the image to 8Bit + + cvtColor(img1,img,CV_BGR2GRAY); + threshold(img,img,30,255,THRESH_BINARY_INV); + //retrieveImage(img2,2);//Retrieving the mask for the image + //img2.convertTo(img2,CV_8U);//Converting the mask to 8Bit + //cvtColor(img2,img,CV_BGR2GRAY);//Converting the mask to a grayscale image + + int largest_area=0; + int largest_contour_index=0; + Rect bounding_rect; + vector > contours; // Vector for storing contour + vector hierarchy; + findContours( img, contours, hierarchy,CV_RETR_CCOMP, CV_CHAIN_APPROX_SIMPLE ); + // iterate through each contour. + for( int i = 0; i< contours.size(); i++ ) + { + + // Find the area of contour + double a=contourArea( contours[i],false); + if(a>largest_area){ + largest_area=a;//cout << i<<" area "< +#include "opencv2/core/core.hpp" +#include "opencv2/highgui/highgui.hpp" +#include "opencv2/opencv.hpp" +#include +using namespace cv; +using namespace std; +extern "C" { + #include "api_scilab.h" + #include "Scierror.h" + #include "BOOL.h" + #include + #include "sciprint.h" + #include "../common.h" + + int opencv_integralImage(char *fname, unsigned long fname_len) { + SciErr sciErr; + int intErr = 0; + + + int *piAddr1 = NULL; + + int error; + + // String holding the second argument + int iRet = 0; + char* pstData = NULL; + + // Checking input argument + CheckInputArgument(pvApiCtx, 1, 2); + CheckOutputArgument(pvApiCtx, 3, 3); + + // Get input image + + Mat image; + retrieveImage(image, 1); + image.convertTo(image,CV_8UC1); + cvtColor(image,image,CV_BGR2GRAY); + + + + + // Error Checks + + if (image.channels() > 1) { + sciprint("The image must be grayscale."); + return 0; + } + + // Output variables holding integralImage, squared integralImage, integralImage over rectangle rotated by 45 degrees + Mat new_image, integralimage, squaredimage, rotatedimage; + + integral(image, integralimage, squaredimage, rotatedimage, -1); + + // Get the number of input arguments + int inputarg = *getNbInputArgument(pvApiCtx); + + if (inputarg == 1) + integralimage.copyTo(new_image); + + if (inputarg == 2) + { + sciErr = getVarAddressFromPosition(pvApiCtx, 2, &piAddr1); + + if (sciErr.iErr) { + printError(&sciErr, 0); + return 0; + } + + if (isStringType(pvApiCtx, piAddr1)) { + if (isScalar(pvApiCtx, piAddr1)) { + + iRet = getAllocatedSingleString(pvApiCtx, piAddr1, &pstData); + } + } + if (strcmp(pstData, "rotated") == 0) { + rotatedimage.copyTo(new_image); + } else if (strcmp(pstData, "upright") == 0) { + integralimage.copyTo(new_image); + } else { + sciprint("Unknown Parameter Name:%s\n", pstData); + + } + + } + + + + // new_image is sent to scilab as output + + + string tempstring1 = type2str(new_image.type()); + char *checker1; + checker1 = (char *) malloc(tempstring1.size() + 1); + memcpy(checker1, tempstring1.c_str(), tempstring1.size() + 1); + returnImage(checker1, new_image, 1); + free(checker1); + + string tempstring2 = type2str(squaredimage.type()); + char *checker2; + checker2 = (char *) malloc(tempstring2.size() + 1); + memcpy(checker2, tempstring2.c_str(), tempstring2.size() + 1); + returnImage(checker2, squaredimage, 2); + free(checker2); + + string tempstring3 = type2str(rotatedimage.type()); + char *checker3; + checker3 = (char *) malloc(tempstring3.size() + 1); + memcpy(checker3, tempstring3.c_str(), tempstring3.size() + 1); + returnImage(checker3, rotatedimage, 3); + free(checker3); + + + + //Assigning the list as the Output Variable + AssignOutputVariable(pvApiCtx, 1) = nbInputArgument(pvApiCtx) + 1; + AssignOutputVariable(pvApiCtx, 2) = nbInputArgument(pvApiCtx) + 2; + AssignOutputVariable(pvApiCtx, 3) = nbInputArgument(pvApiCtx) + 3; + //Returning the Output Variables as arguments to the Scilab environment + ReturnArguments (pvApiCtx); + return 0; + +} +/* ==================================================================== */ +} + diff --git a/sci_gateway/cpp/opencv_lab2double.cpp b/sci_gateway/cpp/opencv_lab2double.cpp new file mode 100644 index 0000000..1597d04 --- /dev/null +++ b/sci_gateway/cpp/opencv_lab2double.cpp @@ -0,0 +1,138 @@ +/*-------------------------------------- + function-lab2double + Author :Tess Zacharias +------------------------------------- */ +#include +#include "opencv2/core/core.hpp" +#include "opencv2/highgui/highgui.hpp" +#include "opencv2/opencv.hpp" +#include +#include +#include +#include +using namespace cv; +using namespace std; +extern "C" +{ + #include "api_scilab.h" + #include "Scierror.h" + #include "BOOL.h" + #include + #include "../common.h" + #define REF_X .95047; // Observer= 2°, Illuminant= D65 + #define REF_Y 1.00000; + #define REF_Z 1.08883; + int opencv_lab2double(char *fname, unsigned long fname_len) + { + SciErr sciErr; + int iRows = 0; + int iCols = 0; + int* piAddr=NULL; + int* piAddr1=NULL; + int* piAddr3=NULL; + int i,j; + int error; + float L,a,b; + int *piAddrNew = NULL; + CheckOutputArgument(pvApiCtx,1,1); + int k=0; + double *pstDataR = NULL; + double *pstDataG = NULL; + double *pstDataB = NULL; + sciErr = getVarAddressFromPosition(pvApiCtx,1,&piAddr); + if(sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + if(!isListType(pvApiCtx, piAddr)) + { + Scierror(999,"the input should be a list \n"); + return 0; + + + + } + sciErr = getMatrixOfDoubleInList(pvApiCtx, piAddr, 1, &iRows, &iCols, &pstDataR); + if(sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + sciErr = getVarAddressFromPosition(pvApiCtx,1,&piAddr); + if(sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + sciErr = getMatrixOfDoubleInList(pvApiCtx, piAddr, 2, &iRows, &iCols, &pstDataG); + if(sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + sciErr = getVarAddressFromPosition(pvApiCtx,1,&piAddr); + if(sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + sciErr = getMatrixOfDoubleInList(pvApiCtx, piAddr, 3, &iRows, &iCols, &pstDataB); + if(sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + int m=0; + double *r1,*g1,*b1; + r1=(double *)malloc(sizeof(double)*iRows*iCols); + g1=(double *)malloc(sizeof(double)*iRows*iCols); + b1=(double *)malloc(sizeof(double)*iRows*iCols); + for(int i=0;i +#include +#include "opencv2/core/core.hpp" +#include "opencv2/highgui/highgui.hpp" +#include "opencv2/opencv.hpp" +#include "opencv2/calib3d/calib3d.hpp" +#include +#include +using namespace cv; +using namespace std; +extern "C" +{ + + + + #include "api_scilab.h" + #include "Scierror.h" + #include "BOOL.h" + #include + #include + #include "../common.h" + + + int opencv_matMulDeriv(char *fname, unsigned long fname_len) + { + + SciErr sciErr; + int intErr = 0; + int iRows1=0,iCols1=0;//for matrix1 array + int iRows2=0,iCols2=0;//for matrix2 array + int *piAddrNew = NULL; + int *piAddr1 = NULL; + int *piAddr2 = NULL; + double *matrix1,*matrix2; + int i,j; + + CheckInputArgument(pvApiCtx, 2, 2); + CheckOutputArgument(pvApiCtx, 2, 2); + + int n=*getNbInputArgument(pvApiCtx);//get number of input arguments + +//for matrix1 + sciErr = getVarAddressFromPosition(pvApiCtx,1,&piAddr1); + if (sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + sciErr = getMatrixOfDouble(pvApiCtx, piAddr1, &iRows1, &iCols1, &matrix1); + if(sciErr.iErr) + { + printError(&sciErr,0); + return 0; + } + + + + Mat A(iRows1,iCols1,CV_64F,&matrix1);//get Mat + + + //for matrix2 + sciErr = getVarAddressFromPosition(pvApiCtx,2,&piAddr2); + if (sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + sciErr = getMatrixOfDouble(pvApiCtx, piAddr2, &iRows2, &iCols2, &matrix2); + if(sciErr.iErr) + { + printError(&sciErr,0); + return 0; + } + + + Mat B(iRows2,iCols2,CV_64F,&matrix2);//get Mat + + + //final call + Mat C,D; + + sciprint("yama"); + try{ + cv::matMulDeriv(A,B,C,D); + } + catch(cv::Exception& e) + { + sciprint("%s",e.what()); + + + } + + + + + //return the Mat to scilab memory + + double *partial1;//[iRows1*iCols2][iRows1*iCols1]; + partial1=(double*)malloc(sizeof(double)*iRows1*iCols2*iRows1*iCols1); + for(i=0;i(i,j)); + + double *partial2;//[iRows1*iCols2][iRows2*iCols2]; + partial2=(double*)malloc(sizeof(double)*iRows1*iCols2*iRows2*iCols2); + for(i=0;i(i,j));; + + //Creating Output Arguments + sciErr = createMatrixOfDouble(pvApiCtx, nbInputArgument(pvApiCtx) + 1, iRows1*iCols2, iRows1*iCols1, partial1); + if(sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + sciErr = createMatrixOfDouble(pvApiCtx, nbInputArgument(pvApiCtx) + 2, iRows1*iCols2, iRows2*iCols2, partial2); + if(sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + + + + AssignOutputVariable(pvApiCtx, 1) = nbInputArgument(pvApiCtx) + 1; + AssignOutputVariable(pvApiCtx, 2) = nbInputArgument(pvApiCtx) + 2; + ReturnArguments(pvApiCtx); + return 0; + + + + + + +} + + + + + + +} diff --git a/sci_gateway/cpp/opencv_multiDenoise.cpp b/sci_gateway/cpp/opencv_multiDenoise.cpp new file mode 100644 index 0000000..61af23a --- /dev/null +++ b/sci_gateway/cpp/opencv_multiDenoise.cpp @@ -0,0 +1,365 @@ +/* +This is the .cpp file for the 'multiDenoise' scilab function. +It includes the OpenCV function fastNlMeansDenoisingMulti() +It is used for denoising an image using multiple copies of the image captured in a very minute time interval. +Author : Shubham Lohakare, NITK Surathkal + Ashish Mantosh Barik, NIT Rourkela +*/ +#include +#include"opencv2/core/core.hpp" +#include"opencv2/highgui/highgui.hpp" +#include"opencv2/opencv.hpp" +#include"opencv2/shape/shape_transformer.hpp" +#include"opencv2/shape.hpp" +#include"opencv2/imgcodecs.hpp" +#include"opencv2/imgproc/imgproc.hpp" +#include"opencv2/features2d/features2d.hpp" + +#include"opencv2/core/utility.hpp" +#include +#include +#include +using namespace cv; +using namespace std; +extern "C" +{ + #include "api_scilab.h" + #include "Scierror.h" + #include "BOOL.h" + #include + #include "sciprint.h" + #include "../common.h" + + int opencv_multiDenoise(char *fname, unsigned long fname_len) + { SciErr sciErr; + int i; + + // Checking number of input and output arguments (enviromnet variable, min arguments, max arguments) + CheckInputArgument(pvApiCtx, 10, 12); + CheckOutputArgument(pvApiCtx, 1, 1); + + // variables required to read argument #1 + int *piAddr1 = NULL; + int intErr1 = 0; + double imgToDenoiseIndex = 0; + + // variables required to read argument #2 + int *piAddr2 = NULL; + int intErr2 = 0; + double temporalWindowSize = 0; + + // variables required to read argument #3 + int *piAddr3 = NULL; + int intErr3 = 0; + double filterStrength = 0; + + // variables required to read argument #4 + int *piAddr4 = NULL; + int intErr4 = 0; + double templateWindowSize = 0; + + // variables required to read argument #5 + int *piAddr5 = NULL; + int intErr5 = 0; + double searchWindowSize = 0; + + // variables required to read argument #6 + int *piAddr6 = NULL; + int intErr6 = 0; + double n = 0; + + // variables required to read argument #7 + int *piAddr7 = NULL; + int intErr7 = 0; + double choice = 0; + + + + cv::Mat img1,img2,img3,dst; + + // to get argument #1 + sciErr = getVarAddressFromPosition(pvApiCtx, 1, &piAddr1); + if(sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + intErr1 = getScalarDouble(pvApiCtx, piAddr1, &imgToDenoiseIndex); + if(intErr1) + { + return intErr1; + } + + // to get argument #2 + sciErr = getVarAddressFromPosition(pvApiCtx, 2, &piAddr2); + if(sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + intErr2 = getScalarDouble(pvApiCtx, piAddr2, &temporalWindowSize); + if(intErr2) + { + return intErr2; + } + + // to get argument #3 + sciErr = getVarAddressFromPosition(pvApiCtx, 3, &piAddr3); + if(sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + intErr3 = getScalarDouble(pvApiCtx, piAddr3, &filterStrength); + if(intErr3) + { + return intErr3; + } + // to get argument #4 + sciErr = getVarAddressFromPosition(pvApiCtx, 4, &piAddr4); + if(sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + intErr4 = getScalarDouble(pvApiCtx, piAddr4, &templateWindowSize); + if(intErr4) + { + return intErr4; + } + // to get argument #5 + sciErr = getVarAddressFromPosition(pvApiCtx, 5, &piAddr5); + if(sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + intErr5 = getScalarDouble(pvApiCtx, piAddr5, &searchWindowSize); + if(intErr5) + { + return intErr5; + } + + // to get argument #6 + sciErr = getVarAddressFromPosition(pvApiCtx, 6, &piAddr6); + if(sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + intErr6 = getScalarDouble(pvApiCtx, piAddr6, &n); + if(intErr6) + { + return intErr6; + } + + // to get argument #7 + sciErr = getVarAddressFromPosition(pvApiCtx, 7, &piAddr7); + if(sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + intErr7 = getScalarDouble(pvApiCtx, piAddr7, &choice); + if(intErr7) + { + return intErr7; + } + + Mat img4, img5; + + try{ + vector images; + retrieveImage(img1, 8);//Retrieving image#1 + retrieveImage(img2, 9);//Retrieving image#2 + retrieveImage(img3, 10);//Retrieving image#3 + + img1.convertTo(img1,CV_8U); + + img2.convertTo(img2,CV_8U); + + img3.convertTo(img3,CV_8U); + + if(choice==1){ + + if(n == 3) + { + + images.push_back(img1); + images.push_back(img2); + images.push_back(img3); + + fastNlMeansDenoisingMulti(images, dst, imgToDenoiseIndex, temporalWindowSize, filterStrength, templateWindowSize, searchWindowSize); + } + else if(n == 4) + { + + retrieveImage(img4, 11);//Retrieving image#4 + + img4.convertTo(img4,CV_8U); + + images.push_back(img1); + images.push_back(img2); + images.push_back(img3); + images.push_back(img4); + + fastNlMeansDenoisingMulti(images, dst, imgToDenoiseIndex, temporalWindowSize, filterStrength, templateWindowSize, searchWindowSize); + } + else if(n == 5) + { + + retrieveImage(img4, 11);//Retrieving image#4 + retrieveImage(img5, 12);//Retrieving image#5 + + img4.convertTo(img4,CV_8U); + img5.convertTo(img5,CV_8U); + + images.push_back(img1); + images.push_back(img2); + images.push_back(img3); + images.push_back(img4); + images.push_back(img5); + + fastNlMeansDenoisingMulti(images, dst, imgToDenoiseIndex, temporalWindowSize, filterStrength, templateWindowSize, searchWindowSize); + } + else + { + Scierror(999, "Wrong input for 'number of images'.", 1); + } + + } + else if(choice==2) + { + + if(n == 3) + { vector h; + h.push_back(filterStrength); + + images.push_back(img1); + images.push_back(img2); + images.push_back(img3); + + sciprint("yo"); + fastNlMeansDenoisingMulti(images, dst, imgToDenoiseIndex, temporalWindowSize, h, templateWindowSize, searchWindowSize,NORM_L1); + } + else if(n == 4) + { + vector h; + h.push_back(filterStrength); + + + retrieveImage(img4, 11);//Retrieving image#4 + + img4.convertTo(img4,CV_8U); + + images.push_back(img1); + images.push_back(img2); + images.push_back(img3); + images.push_back(img4); + + fastNlMeansDenoisingMulti(images, dst, imgToDenoiseIndex, temporalWindowSize, h, templateWindowSize, searchWindowSize,NORM_L1); + } + else if(n == 5) + { + vector h; + h.push_back(filterStrength); + + + retrieveImage(img4, 11);//Retrieving image#4 + retrieveImage(img5, 12);//Retrieving image#5 + + img4.convertTo(img4,CV_8U); + img5.convertTo(img5,CV_8U); + + images.push_back(img1); + images.push_back(img2); + images.push_back(img3); + images.push_back(img4); + images.push_back(img5); + + fastNlMeansDenoisingMulti(images, dst, imgToDenoiseIndex, temporalWindowSize, h, templateWindowSize, searchWindowSize,NORM_L1); + } + else + { + Scierror(999, "Wrong input for 'number of images'.", 1); + } + + } + + else if(choice==3) + { vector h; + h.push_back(filterStrength); + if(n == 3) + { + + images.push_back(img1); + images.push_back(img2); + images.push_back(img3); + + sciprint("yo"); + fastNlMeansDenoisingMulti(images, dst, imgToDenoiseIndex, temporalWindowSize, h, templateWindowSize, searchWindowSize,NORM_L2); + } + else if(n == 4) + { + vector h; + h.push_back(filterStrength); + + + retrieveImage(img4, 11);//Retrieving image#4 + + img4.convertTo(img4,CV_8U); + + images.push_back(img1); + images.push_back(img2); + images.push_back(img3); + images.push_back(img4); + + fastNlMeansDenoisingMulti(images, dst, imgToDenoiseIndex, temporalWindowSize, h, templateWindowSize, searchWindowSize,NORM_L2); + } + else if(n == 5) + { + vector h; + h.push_back(filterStrength); + + + retrieveImage(img4, 11);//Retrieving image#4 + retrieveImage(img5, 12);//Retrieving image#5 + + img4.convertTo(img4,CV_8U); + img5.convertTo(img5,CV_8U); + + images.push_back(img1); + images.push_back(img2); + images.push_back(img3); + images.push_back(img4); + images.push_back(img5); + + fastNlMeansDenoisingMulti(images, dst, imgToDenoiseIndex, temporalWindowSize, h, templateWindowSize, searchWindowSize,NORM_L2); + } + else + { + Scierror(999, "Wrong input for 'number of images'.", 1); + } + + } + + + + } + catch(Exception& e) + { + const char* err=e.what(); + sciprint("%s",err); + } + + string tempstring = type2str(dst.type());//Returning the image to scilab console + char* checker = (char *)malloc(tempstring.size() + 1); + memcpy(checker, tempstring.c_str(), tempstring.size() + 1); + returnImage(checker,dst,1); + AssignOutputVariable(pvApiCtx, 1) = nbInputArgument(pvApiCtx) + 1; + ReturnArguments(pvApiCtx); + + return 0; + + } +} diff --git a/sci_gateway/cpp/opencv_multiDenoiseColor.cpp b/sci_gateway/cpp/opencv_multiDenoiseColor.cpp new file mode 100644 index 0000000..d9a2d4c --- /dev/null +++ b/sci_gateway/cpp/opencv_multiDenoiseColor.cpp @@ -0,0 +1,250 @@ +/* +This is the .cpp file for the 'multiDenoiseColor' scilab function. +It includes the OpenCV function fastNlMeansDenoisingColoredMulti() +It is used for removing colored noise from an image using multiple copies of the image captured in a very minute time interval. +Author : Shubham Lohakare, NITK Surathkal + Ashish Manatosh Barik, NIT Rourkela +*/ +#include +#include"opencv2/core/core.hpp" +#include"opencv2/highgui/highgui.hpp" +#include"opencv2/opencv.hpp" +#include"opencv2/shape/shape_transformer.hpp" +#include"opencv2/shape.hpp" +#include"opencv2/imgcodecs.hpp" +#include"opencv2/imgproc/imgproc.hpp" +#include"opencv2/features2d/features2d.hpp" + +#include"opencv2/core/utility.hpp" +#include +#include +#include +using namespace cv; +using namespace std; +extern "C" +{ + #include "api_scilab.h" + #include "Scierror.h" + #include "BOOL.h" + #include + #include "sciprint.h" + #include "../common.h" + + int opencv_multiDenoiseColor(char *fname, unsigned long fname_len) + { SciErr sciErr; + int i; + + // Checking number of input and output arguments (enviromnet variable, min arguments, max arguments) + CheckInputArgument(pvApiCtx, 10, 12); + CheckOutputArgument(pvApiCtx, 1, 1); + + // variables required to read argument #1 + int *piAddr1 = NULL; + int intErr1 = 0; + double imgToDenoiseIndex = 0; + + // variables required to read argument #2 + int *piAddr2 = NULL; + int intErr2 = 0; + double temporalWindowSize = 0; + + // variables required to read argument #3 + int *piAddr3 = NULL; + int intErr3 = 0; + double filterStrength = 0; + + // variables required to read argument #4 + int *piAddr4 = NULL; + int intErr4 = 0; + double filterStrengthColor = 0; + + // variables required to read argument #5 + int *piAddr5 = NULL; + int intErr5 = 0; + double templateWindowSize = 0; + + // variables required to read argument #6 + int *piAddr6 = NULL; + int intErr6 = 0; + double searchWindowSize = 0; + + // variables required to read argument #7 + int *piAddr7 = NULL; + int intErr7 = 0; + double n = 0; + + + cv::Mat img1,img2,img3,dst; + + // to get argument #1 + sciErr = getVarAddressFromPosition(pvApiCtx, 1, &piAddr1); + if(sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + intErr1 = getScalarDouble(pvApiCtx, piAddr1, &imgToDenoiseIndex); + if(intErr1) + { + return intErr1; + } + + // to get argument #2 + sciErr = getVarAddressFromPosition(pvApiCtx, 2, &piAddr2); + if(sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + intErr2 = getScalarDouble(pvApiCtx, piAddr2, &temporalWindowSize); + if(intErr2) + { + return intErr2; + } + + // to get argument #3 + sciErr = getVarAddressFromPosition(pvApiCtx, 3, &piAddr3); + if(sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + intErr3 = getScalarDouble(pvApiCtx, piAddr3, &filterStrength); + if(intErr3) + { + return intErr3; + } + // to get argument #4 + sciErr = getVarAddressFromPosition(pvApiCtx, 4, &piAddr4); + if(sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + intErr4 = getScalarDouble(pvApiCtx, piAddr4, &filterStrengthColor); + if(intErr4) + { + return intErr4; + } + // to get argument #5 + sciErr = getVarAddressFromPosition(pvApiCtx, 5, &piAddr5); + if(sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + intErr5 = getScalarDouble(pvApiCtx, piAddr5, &templateWindowSize); + if(intErr5) + { + return intErr5; + } + + // to get argument #6 + sciErr = getVarAddressFromPosition(pvApiCtx, 6, &piAddr6); + if(sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + intErr6 = getScalarDouble(pvApiCtx, piAddr6, &searchWindowSize); + if(intErr6) + { + return intErr6; + } + + // to get argument #7 + sciErr = getVarAddressFromPosition(pvApiCtx, 7, &piAddr7); + if(sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + intErr7 = getScalarDouble(pvApiCtx, piAddr7, &n); + if(intErr7) + { + return intErr7; + } + + try{ + vector images; + retrieveImage(img1, 8); + retrieveImage(img2, 9); + retrieveImage(img3, 10); + + img1.convertTo(img1,CV_8U); + + + img2.convertTo(img2,CV_8U); + + + img3.convertTo(img3,CV_8U); + + Mat img4,img5; + //denoise_TVL1(src,dst,1,30); + if(n == 3) + { + + images.push_back(img1); + images.push_back(img2); + images.push_back(img3); + + sciprint("yo"); + fastNlMeansDenoisingColoredMulti(images, dst, imgToDenoiseIndex, temporalWindowSize, filterStrength, filterStrengthColor,templateWindowSize, searchWindowSize); + } + else if(n == 4) + { + + retrieveImage(img4, 10); + + img4.convertTo(img4,CV_8U); + + + images.push_back(img1); + images.push_back(img2); + images.push_back(img3); + images.push_back(img4); + + fastNlMeansDenoisingColoredMulti(images, dst, imgToDenoiseIndex, temporalWindowSize, filterStrength, filterStrengthColor,templateWindowSize, searchWindowSize); + } + else if(n == 5) + { + + retrieveImage(img4, 10); + retrieveImage(img5, 11); + + img4.convertTo(img4,CV_8U); + img5.convertTo(img5,CV_8U); + + images.push_back(img1); + images.push_back(img2); + images.push_back(img3); + images.push_back(img4); + images.push_back(img5); + + fastNlMeansDenoisingColoredMulti(images, dst, imgToDenoiseIndex, temporalWindowSize, filterStrength, filterStrengthColor, templateWindowSize, searchWindowSize); + } + else + { + Scierror(999, "Wrong input for 'number of images'.", 1); + } + + + + } + catch(Exception& e) + { + const char* err=e.what(); + sciprint("%s",err); + } + + string tempstring = type2str(dst.type()); + char* checker = (char *)malloc(tempstring.size() + 1); + memcpy(checker, tempstring.c_str(), tempstring.size() + 1); + returnImage(checker,dst,1); + AssignOutputVariable(pvApiCtx, 1) = nbInputArgument(pvApiCtx) + 1; + ReturnArguments(pvApiCtx); + + return 0; + + } +} diff --git a/sci_gateway/cpp/opencv_predictSVM.cpp b/sci_gateway/cpp/opencv_predictSVM.cpp new file mode 100644 index 0000000..1a76076 --- /dev/null +++ b/sci_gateway/cpp/opencv_predictSVM.cpp @@ -0,0 +1,272 @@ +/*************************************************** +Author : Nihar Rao +***************************************************/ +#include +#include +#include +#include "opencv2/core/core.hpp" +#include "opencv2/highgui/highgui.hpp" +#include "opencv2/imgproc/imgproc.hpp" +#include "opencv2/features2d.hpp" +#include "opencv2/xfeatures2d.hpp" +#include "opencv2/ml.hpp" +#include "opencv2/opencv.hpp" + + +using namespace cv; +using namespace cv::xfeatures2d; +using namespace std; +using namespace cv::ml; + +extern "C" +{ + #include "api_scilab.h" + #include "Scierror.h" + #include "BOOL.h" + #include + #include "sciprint.h" + #include "../common.h" + inline bool file_exists_check(const std::string& name) { + struct stat buffer; + return (stat (name.c_str(), &buffer) == 0); + } + int opencv_predictSVM(char *fname, unsigned long fname_len) + { + // Error management variables + SciErr sciErr; + + //------Local variables------// + int upright = 1; + Ptr matcher = DescriptorMatcher::create("FlannBased"); + Ptr detector = SURF::create(400, 4, 2, 1, int(upright)); + Ptr extractor=detector; + Ptr bowDE=makePtr(extractor,matcher); + //SurfFeatureDetector detector(1, 4, 2, 1, int(upright)); + // char *classifierLocation = NULL; + Mat dictionary,features; + double response; + vector keyPoints; + int dictionarySize; + int *piAddr = NULL; + int *piChild = NULL; + int iRows, iCols; + char **pstData = NULL; + int *piLen = NULL; + char **classifierDescription = NULL; + int classifierDescriptionCount; + char *bagOfFeaturesLocation = NULL; + int descriptionCount; + Mat input; + //------Check number of parameters------// + CheckInputArgument(pvApiCtx, 2, 2); + CheckOutputArgument(pvApiCtx, 1, 1); + + //------Get input arguments------// + retrieveImage(input,2); + //cvtColor(input, input, cv::COLOR_RGBA2GRAY); + sciErr = getVarAddressFromPosition(pvApiCtx, 1, &piAddr); + if (sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + if(!isListType(pvApiCtx, piAddr)) + { + Scierror(999, "Error: The input argument #1 is not of type classifier.\n"); + return 0; + } + + // Extracting object type and checking if type is classifier + sciErr = getMatrixOfStringInList(pvApiCtx, piAddr, 1, &iRows, &iCols, NULL, NULL); + if(sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + + piLen = (int*)malloc(sizeof(int) * iRows * iCols); + + sciErr = getMatrixOfStringInList(pvApiCtx, piAddr, 1, &iRows, &iCols, piLen, NULL); + if(sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + + pstData = (char**)malloc(sizeof(char*) * iRows * iCols); + + for(int iter = 0 ; iter < iRows * iCols ; iter++) + { + pstData[iter] = (char*)malloc(sizeof(char) * (piLen[iter] + 1));//+ 1 for null termination + } + + sciErr = getMatrixOfStringInList(pvApiCtx, piAddr, 1, &iRows, &iCols, piLen, pstData); + if(sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + + if(!(strcmp(pstData[0],"classifier")==0)) + { + Scierror(999, "Error: The input argument #1 is not of type classifier.\n"); + return 0; + } + sciErr = getMatrixOfStringInList(pvApiCtx, piAddr, 2, &iRows, &iCols, NULL, NULL); + if (sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + + piLen = (int*) malloc(sizeof(int) * iRows * iCols); + + sciErr = getMatrixOfStringInList(pvApiCtx, piAddr, 2, &iRows, &iCols, piLen, NULL); + if (sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + + pstData = (char**) malloc(sizeof(char*) * iRows * iCols); + for(int iterPstData = 0; iterPstData < iRows * iCols; iterPstData++) + { + pstData[iterPstData] = (char*) malloc(sizeof(char) * piLen[iterPstData] + 1); + } + + sciErr = getMatrixOfStringInList(pvApiCtx, piAddr, 2, &iRows, &iCols, piLen, pstData); + if (sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + + if(iRows!=1 || iCols!=1) + { + Scierror(999, "1x1 Matrix expected for classifier argument."); + return 0; + } + string classifierLocation = string(pstData[0]); + sciErr = getMatrixOfStringInList(pvApiCtx, piAddr, 3, &iRows, &iCols, NULL, NULL); + if (sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + + piLen = (int*) malloc(sizeof(int) * iRows * iCols); + + sciErr = getMatrixOfStringInList(pvApiCtx, piAddr, 3, &iRows, &iCols, piLen, NULL); + if (sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + + pstData = (char**) malloc(sizeof(char*) * iRows * iCols); + for(int iterPstData = 0; iterPstData < iRows * iCols; iterPstData++) + { + pstData[iterPstData] = (char*) malloc(sizeof(char) * piLen[iterPstData] + 1); + } + + sciErr = getMatrixOfStringInList(pvApiCtx, piAddr, 3, &iRows, &iCols, piLen, pstData); + if (sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + + if(iRows!=1 || iCols!=1) + { + Scierror(999, "1x1 Matrix expected for bagOfFeatures argument."); + return 0; + } + bagOfFeaturesLocation = pstData[0]; + sciErr = getMatrixOfStringInList(pvApiCtx, piAddr, 4, &iRows, &iCols, NULL, NULL); + if (sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + + piLen = (int*) malloc(sizeof(int) * iRows * iCols); + + sciErr = getMatrixOfStringInList(pvApiCtx, piAddr, 4, &iRows, &iCols, piLen, NULL); + if (sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + + classifierDescription = (char**) malloc(sizeof(char*) * iRows * iCols); + for(int iterPstData = 0; iterPstData < iRows * iCols; iterPstData++) + { + classifierDescription[iterPstData] = (char*) malloc(sizeof(char) * piLen[iterPstData] + 1); + } + + sciErr = getMatrixOfStringInList(pvApiCtx, piAddr, 4, &iRows, &iCols, piLen, classifierDescription); + if (sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + + //------Actual processing------// + FileStorage fs(bagOfFeaturesLocation, FileStorage::READ); + fs["dictionary"] >> dictionary; + fs.release(); + try{ + + input.convertTo(input,CV_8U); + dictionarySize = dictionary.rows; + + bowDE->setVocabulary(dictionary); + if(!file_exists_check(classifierLocation)) + { + + Scierror(999, "Error: the input File not found!.Please enter correct path!\n"); + return 0; + + } + Ptr svm = Algorithm::load(classifierLocation); + if(!svm->isTrained()) + { + Scierror(999, "Error: the model is not trained!.\n"); + return 0; + + + + + } + detector->detect(input, keyPoints); + bowDE->compute(input, keyPoints, features); + features.convertTo(features,CV_32F); + response = svm->predict(features); + sciprint("\ndone"); + } + catch(cv::Exception& e) + { + const char* err=e.what(); + sciprint("%s",err); + + } + //------Create output arguments------// + sciErr = createList(pvApiCtx, nbInputArgument(pvApiCtx) + 1, 1, &piAddr); + if(sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + sciErr = createMatrixOfStringInList(pvApiCtx, nbInputArgument(pvApiCtx)+1,piAddr,1,1,1,&classifierDescription[(int)response]); + if(sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + //------Return Arguments------// + AssignOutputVariable(pvApiCtx, 1) = nbInputArgument(pvApiCtx)+1; + ReturnArguments(pvApiCtx); + return 0; + } + /* ==================================================================== */ +} diff --git a/sci_gateway/cpp/opencv_predictSVMSGD.cpp b/sci_gateway/cpp/opencv_predictSVMSGD.cpp new file mode 100644 index 0000000..77ad6e7 --- /dev/null +++ b/sci_gateway/cpp/opencv_predictSVMSGD.cpp @@ -0,0 +1,272 @@ +/*************************************************** +Author : Nihar Rao +***************************************************/ +#include +#include +#include +#include "opencv2/core/core.hpp" +#include "opencv2/highgui/highgui.hpp" +#include "opencv2/imgproc/imgproc.hpp" +#include "opencv2/features2d.hpp" +#include "opencv2/xfeatures2d.hpp" +#include "opencv2/ml.hpp" +#include "opencv2/opencv.hpp" + + +using namespace cv; +using namespace cv::xfeatures2d; +using namespace std; +using namespace cv::ml; + +extern "C" +{ + #include "api_scilab.h" + #include "Scierror.h" + #include "BOOL.h" + #include + #include "sciprint.h" + #include "../common.h" + + inline bool file_exists_check(const std::string& name) { + struct stat buffer; + return (stat (name.c_str(), &buffer) == 0); + } + int opencv_predictSVMSGD(char *fname, unsigned long fname_len) + { + // Error management variables + SciErr sciErr; + + //------Local variables------// + int upright = 1; + Ptr matcher = DescriptorMatcher::create("FlannBased"); + Ptr detector = SURF::create(400, 4, 2, 1, int(upright)); + Ptr extractor=detector; + Ptr bowDE=makePtr(extractor,matcher); + //SurfFeatureDetector detector(1, 4, 2, 1, int(upright)); + // char *classifierLocation = NULL; + Mat dictionary,features; + double response; + vector keyPoints; + int dictionarySize; + int *piAddr = NULL; + int *piChild = NULL; + int iRows, iCols; + char **pstData = NULL; + int *piLen = NULL; + char **classifierDescription = NULL; + int classifierDescriptionCount; + char *bagOfFeaturesLocation = NULL; + int descriptionCount; + Mat input; + //------Check number of parameters------// + CheckInputArgument(pvApiCtx, 2, 2); + CheckOutputArgument(pvApiCtx, 1, 1); + + //------Get input arguments------// + retrieveImage(input,2); + //cvtColor(input, input, cv::COLOR_RGBA2GRAY); + sciErr = getVarAddressFromPosition(pvApiCtx, 1, &piAddr); + if (sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + if(!isListType(pvApiCtx, piAddr)) + { + Scierror(999, "Error: The input argument #1 is not of type classifier.\n"); + return 0; + } + + // Extracting object type and checking if type is classifier + sciErr = getMatrixOfStringInList(pvApiCtx, piAddr, 1, &iRows, &iCols, NULL, NULL); + if(sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + + piLen = (int*)malloc(sizeof(int) * iRows * iCols); + + sciErr = getMatrixOfStringInList(pvApiCtx, piAddr, 1, &iRows, &iCols, piLen, NULL); + if(sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + + pstData = (char**)malloc(sizeof(char*) * iRows * iCols); + + for(int iter = 0 ; iter < iRows * iCols ; iter++) + { + pstData[iter] = (char*)malloc(sizeof(char) * (piLen[iter] + 1));//+ 1 for null termination + } + + sciErr = getMatrixOfStringInList(pvApiCtx, piAddr, 1, &iRows, &iCols, piLen, pstData); + if(sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + + if(!(strcmp(pstData[0],"classifier")==0)) + { + Scierror(999, "Error: The input argument #1 is not of type classifier.\n"); + return 0; + } + sciErr = getMatrixOfStringInList(pvApiCtx, piAddr, 2, &iRows, &iCols, NULL, NULL); + if (sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + + piLen = (int*) malloc(sizeof(int) * iRows * iCols); + + sciErr = getMatrixOfStringInList(pvApiCtx, piAddr, 2, &iRows, &iCols, piLen, NULL); + if (sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + + pstData = (char**) malloc(sizeof(char*) * iRows * iCols); + for(int iterPstData = 0; iterPstData < iRows * iCols; iterPstData++) + { + pstData[iterPstData] = (char*) malloc(sizeof(char) * piLen[iterPstData] + 1); + } + + sciErr = getMatrixOfStringInList(pvApiCtx, piAddr, 2, &iRows, &iCols, piLen, pstData); + if (sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + + if(iRows!=1 || iCols!=1) + { + Scierror(999, "1x1 Matrix expected for classifier argument."); + return 0; + } + string classifierLocation = string(pstData[0]); + sciErr = getMatrixOfStringInList(pvApiCtx, piAddr, 3, &iRows, &iCols, NULL, NULL); + if (sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + + piLen = (int*) malloc(sizeof(int) * iRows * iCols); + + sciErr = getMatrixOfStringInList(pvApiCtx, piAddr, 3, &iRows, &iCols, piLen, NULL); + if (sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + + pstData = (char**) malloc(sizeof(char*) * iRows * iCols); + for(int iterPstData = 0; iterPstData < iRows * iCols; iterPstData++) + { + pstData[iterPstData] = (char*) malloc(sizeof(char) * piLen[iterPstData] + 1); + } + + sciErr = getMatrixOfStringInList(pvApiCtx, piAddr, 3, &iRows, &iCols, piLen, pstData); + if (sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + + if(iRows!=1 || iCols!=1) + { + Scierror(999, "1x1 Matrix expected for bagOfFeatures argument."); + return 0; + } + bagOfFeaturesLocation = pstData[0]; + sciErr = getMatrixOfStringInList(pvApiCtx, piAddr, 4, &iRows, &iCols, NULL, NULL); + if (sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + + piLen = (int*) malloc(sizeof(int) * iRows * iCols); + + sciErr = getMatrixOfStringInList(pvApiCtx, piAddr, 4, &iRows, &iCols, piLen, NULL); + if (sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + + classifierDescription = (char**) malloc(sizeof(char*) * iRows * iCols); + for(int iterPstData = 0; iterPstData < iRows * iCols; iterPstData++) + { + classifierDescription[iterPstData] = (char*) malloc(sizeof(char) * piLen[iterPstData] + 1); + } + + sciErr = getMatrixOfStringInList(pvApiCtx, piAddr, 4, &iRows, &iCols, piLen, classifierDescription); + if (sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + + //------Actual processing------// + FileStorage fs(bagOfFeaturesLocation, FileStorage::READ); + fs["dictionary"] >> dictionary; + fs.release(); + try{ + + input.convertTo(input,CV_8U); + dictionarySize = dictionary.rows; + + bowDE->setVocabulary(dictionary); + if(!file_exists_check(classifierLocation)) + { + + Scierror(999, "Error: the input File not found!.Please enter correct path!\n"); + return 0; + + } + + Ptr svmsgd = Algorithm::load(classifierLocation); + if(!svmsgd->isTrained()) + { + Scierror(999, "Error: the model is not trained!.\n"); + return 0; + + } + detector->detect(input, keyPoints); + bowDE->compute(input, keyPoints, features); + features.convertTo(features,CV_32F); + response = svmsgd->predict(features); + sciprint("\ndone"); + } + catch(cv::Exception& e) + { + const char* err=e.what(); + sciprint("%s",err); + + } + //------Create output arguments------// + sciErr = createList(pvApiCtx, nbInputArgument(pvApiCtx) + 1, 1, &piAddr); + if(sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + sciErr = createMatrixOfStringInList(pvApiCtx, nbInputArgument(pvApiCtx)+1,piAddr,1,1,1,&classifierDescription[(int)response]); + if(sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + //------Return Arguments------// + AssignOutputVariable(pvApiCtx, 1) = nbInputArgument(pvApiCtx)+1; + ReturnArguments(pvApiCtx); + return 0; + } + /* ==================================================================== */ +} + diff --git a/sci_gateway/cpp/opencv_stereoCalibrate.cpp b/sci_gateway/cpp/opencv_stereoCalibrate.cpp new file mode 100644 index 0000000..7409c75 --- /dev/null +++ b/sci_gateway/cpp/opencv_stereoCalibrate.cpp @@ -0,0 +1,347 @@ +/*************************************************** +Author : Nihar Rao +***************************************************/ + +#include +#include "opencv2/core/core.hpp" +#include "opencv2/highgui/highgui.hpp" +#include "opencv2/opencv.hpp" +#include "opencv2/core/types_c.h" +#include +using namespace cv; +using namespace std; +extern "C" +{ + #include "api_scilab.h" + #include "Scierror.h" + #include "BOOL.h" + #include + #include + #include "../common.h" + + +int opencv_stereoCalibrate(char *fname, unsigned long fname_len) + { + //variables + + int i,j,k,n,m; + int iRows=0,iCols=0; + int *piAddr=NULL; + double *pdblReal = NULL; + double x,y,rms; + int p; + + + SciErr sciErr; + vector >imagepoints1(1),imagepoints2(1); + vector >objectPoints(1); + + + + Mat cameraMatrix1; + Mat cameraMatrix2; + Mat distCoeffsActual1,distCoeffsActual2; + Mat rotationMatrix; + Mat translationVector; + int num; + + ////////parsing input + + n=*getNbInputArgument(pvApiCtx); + //first + sciErr = getVarAddressFromPosition(pvApiCtx, 1, &piAddr); + if (sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + sciErr = getMatrixOfDouble(pvApiCtx, piAddr, &iRows, &iCols, &pdblReal); + if(sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + //stores + + //objectPoints = (CvPoint3D64f*)cvAlloc( iRows *1* sizeof(CvPoint3D64f)); + for(i = 0; i < iRows; ++i) + objectPoints[0].push_back(Point3d(double(pdblReal[(0 * iRows) + i]), double(pdblReal[(1 * iRows) + i]),0.0)); + + +int pointCount=iRows; + //2nd Input + + + sciErr = getVarAddressFromPosition(pvApiCtx, 2, &piAddr); + if (sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + + if(!isListType(pvApiCtx, piAddr)) + { + + Scierror(999,"\nthe imagepoints1 Argument must be a list of points \n"); + return 0; + } + sciErr = getListItemNumber(pvApiCtx, piAddr, &num); + if(sciErr.iErr) + { + printError(&sciErr, 0); + + return 0; + } + imagepoints1.resize(num); + + //get items from list + + for(int i=1;i<=num;i++) + { + + sciErr=getMatrixOfDoubleInList(pvApiCtx, piAddr,i,&iRows, &iCols, &pdblReal); + + if(sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + + for(j = 0; j < iRows; ++j) + imagepoints1[i-1].push_back( Point2d(double(pdblReal[(0 * iRows) + j]), double(pdblReal[(1 * iRows) + j]))); + + + + } + + //3rd input + sciprint("\n"); + sciErr = getVarAddressFromPosition(pvApiCtx, 3, &piAddr); + if (sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + + if(!isListType(pvApiCtx, piAddr)) + { + + Scierror(999,"\nthe imagepoints2 Argument must be a list of points \n"); + return 0; + } + sciErr = getListItemNumber(pvApiCtx, piAddr, &num); + if(sciErr.iErr) + { + printError(&sciErr, 0); + + return 0; + } + imagepoints2.resize(num); + //get items from list + + for(int i=1;i<=num;i++) + { + sciErr=getMatrixOfDoubleInList(pvApiCtx, piAddr,i,&iRows, &iCols, &pdblReal); + if(sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + + for(j = 0; j < iRows; ++j) + imagepoints2[i-1].push_back( Point2d(double(pdblReal[(0 * iRows) + j]), double(pdblReal[(1 * iRows) + j]))); + + + } + + ///Getting optional arguments + + for(i=4;i<=n;i++) + { + sciErr = getVarAddressFromPosition(pvApiCtx,i,&piAddr); + if (sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + + if(!isDoubleType(pvApiCtx, piAddr)) + { + + Scierror(999,"\nthe input should be of type double\n"); + return 0; + + + } + if(i==4 || i==6) + { + sciErr = getMatrixOfDouble(pvApiCtx, piAddr, &iRows, &iCols, &pdblReal); + if(sciErr.iErr) + { + printError(&sciErr,0); + return 0; + } + + Mat C(3,3,CV_8U,&pdblReal); + if(i==4) + C.copyTo(cameraMatrix1); + else + C.copyTo(cameraMatrix2); + } + + if(i==5 || i==7) + { + sciErr = getMatrixOfDouble(pvApiCtx, piAddr, &iRows, &iCols, &pdblReal); + if(sciErr.iErr) + { + printError(&sciErr,0); + return 0; + } + if(iRows== 1) + p = iCols; + else if (iCols == 1) + p = iRows; + else{ + Scierror(1,"Distortion Points matrix must be a 4 X 1 or 1 X 4 matrix"); + return 0; + } + if(p==4); + else{ + Scierror(1," N must be 4"); + return 0; + } + Mat A(1,p,CV_8U,&pdblReal); + if(i==5) + A.copyTo(distCoeffsActual1); + else + A.copyTo(distCoeffsActual2); + + } + + } + + + + try + { + Size imageSize (600,960); + + rms = fisheye::stereoCalibrate(objectPoints,imagepoints1,imagepoints2, + cameraMatrix1, distCoeffsActual1, + cameraMatrix2, distCoeffsActual2, + imageSize, rotationMatrix, translationVector,fisheye::CALIB_FIX_SKEW | fisheye::CALIB_RECOMPUTE_EXTRINSIC | fisheye::CALIB_FIX_K4, + TermCriteria(CV_TERMCRIT_EPS + CV_TERMCRIT_ITER, 30, DBL_EPSILON)); + + } + catch(cv::Exception& e) + { + + Scierror(999,e.what()); + return 0; + + + + } + sciprint("Calibration done with RMS error=%f\n",rms); + + + + ///Return Arguments to Scilab + + double *pstdata1 = NULL,*pstdata2 = NULL,*pstdata3 = NULL,*pstdata4 = NULL,*pstdata5 = NULL,*pstdata6 = NULL; + pstdata1 = (double*)malloc(sizeof(double) *3* 3); + + for(i=0;i<3;i++) + for(j=0;j<3;j++) + pstdata1[(j * 3) + i]=cameraMatrix1.at(i,j); + + sciErr = createMatrixOfDouble(pvApiCtx, nbInputArgument(pvApiCtx) + 1, 3, 3, pstdata1); + if(sciErr.iErr){ + printError(&sciErr, 0); + return 0; + } + + pstdata2 = (double*)malloc(sizeof(double) *4*1); + + for(i=0;i<4;i++) + pstdata2[i]=distCoeffsActual1.at(0,i); + + sciErr = createMatrixOfDouble(pvApiCtx, nbInputArgument(pvApiCtx) + 2, 1, 4, pstdata2); + if(sciErr.iErr){ + printError(&sciErr, 0); + return 0; + } + + pstdata3 = (double*)malloc(sizeof(double) *3* 3); + + for(i=0;i<3;i++) + for(j=0;j<3;j++) + pstdata3[(j * 3) + i]=cameraMatrix2.at(i,j); + + sciErr = createMatrixOfDouble(pvApiCtx, nbInputArgument(pvApiCtx) + 3, 3, 3, pstdata3); + if(sciErr.iErr){ + printError(&sciErr, 0); + return 0; + } + pstdata4 = (double*)malloc(sizeof(double) *4*1); + for(i=0;i<4;i++) + pstdata4[i]=distCoeffsActual2.at(0,i); + + sciErr = createMatrixOfDouble(pvApiCtx, nbInputArgument(pvApiCtx) + 4, 1, 4, pstdata4); + if(sciErr.iErr){ + printError(&sciErr, 0); + return 0; + } + pstdata5=(double*)malloc(sizeof(double) *rotationMatrix.rows*rotationMatrix.cols); + + for(i=0;i(i,j); + + } + + sciErr = createMatrixOfDouble(pvApiCtx, nbInputArgument(pvApiCtx) + 5, rotationMatrix.rows, rotationMatrix.cols, pstdata5); + if(sciErr.iErr){ + printError(&sciErr, 0); + return 0; + } + + pstdata6=(double*)malloc(sizeof(double) *translationVector.rows*translationVector.cols); + + for(i=0;i(i,j); + + } + + sciErr = createMatrixOfDouble(pvApiCtx, nbInputArgument(pvApiCtx) + 6, translationVector.rows, translationVector.cols, pstdata6); + if(sciErr.iErr){ + printError(&sciErr, 0); + return 0; + } + + + + for(int i=1;i<=6;i++) + AssignOutputVariable(pvApiCtx, i) = nbInputArgument(pvApiCtx) + i; + //Returning the Output Variables as arguments to the Scilab environment + ReturnArguments(pvApiCtx); + return 0; + + + + } +} + + + + + + + + + diff --git a/sci_gateway/cpp/opencv_trainSVMClassifier.cpp b/sci_gateway/cpp/opencv_trainSVMClassifier.cpp new file mode 100644 index 0000000..9659abf --- /dev/null +++ b/sci_gateway/cpp/opencv_trainSVMClassifier.cpp @@ -0,0 +1,614 @@ +/*************************************************** +Author : Nihar Rao +***************************************************/ +#include +#include +#include "opencv2/core/core.hpp" +#include "opencv2/highgui/highgui.hpp" +#include "opencv2/imgproc/imgproc.hpp" +#include "opencv2/features2d.hpp" +#include "opencv2/xfeatures2d.hpp" +#include "opencv2/ml.hpp" +#include "opencv2/opencv.hpp" + + +using namespace cv; +using namespace cv::xfeatures2d; +using namespace std; +using namespace cv::ml; + + + +extern "C" +{ + #include "api_scilab.h" + #include "Scierror.h" + #include "BOOL.h" + #include + #include "sciprint.h" + + double readdouble_from_scilab(int cnt) + { + + SciErr sciErr; + int *piAddr=NULL; + double val=0; + int intErr; + + sciErr = getVarAddressFromPosition(pvApiCtx,cnt,&piAddr); + if (sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + intErr = getScalarDouble(pvApiCtx, piAddr ,&val); + + if(isDoubleType(pvApiCtx, piAddr)) + return val; + else + { + Scierror(999,"Error: the input argument is not of type double"); + return 0; + + + } + + + } + + + + int opencv_trainSVMClassifier(char *fname, unsigned long fname_len) + { + // Error management variables + SciErr sciErr; + + //------Local variables------// + int upright = 1; + Ptr matcher = DescriptorMatcher::create("FlannBased"); + Ptr detector = SURF::create(400, 4, 2, 1, int(upright)); + Ptr extractor=detector; + Ptr bowDE=makePtr(extractor,matcher); + //SurfFeatureDetector detector(1, 4, 2, 1, int(upright)); + char *fileName = NULL; + Mat dictionary,inp,features; + vector keyPoints; + + + int *piAddr = NULL; + int *piChild = NULL; + int iRows, iCols; + char **pstData = NULL; + int *piLen = NULL; + int *count = NULL; + char **description = NULL; + char ***location = NULL; + char *bagOfFeaturesLocation = NULL; + int descriptionCount; + char *classifierLocation = "classifier.yml"; + char *objectType = "classifier"; + int intErr = 0; + char* stringData = NULL; + char* classifierName; + int iRet; + + double C=0,gamma=1,coef=0,degree=0,P=0,Nu=0,kernelType=2,setType=100;//all model paramenter set to their default values + + //default value is false + + //------Check number of parameters------// + CheckInputArgument(pvApiCtx, 3,11); + CheckOutputArgument(pvApiCtx, 1, 1); + + //------Get input arguments------// + int n=*getNbInputArgument(pvApiCtx); + sciErr = getVarAddressFromPosition(pvApiCtx, 1, &piAddr); + if (sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + if(!isListType(pvApiCtx, piAddr)) + { + Scierror(999, "Error: The input argument #1 is not of type imageSet.\n"); + return 0; + } + + // Extracting object type and checking if type is imageSet + sciErr = getMatrixOfStringInList(pvApiCtx, piAddr, 1, &iRows, &iCols, NULL, NULL); + if(sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + + piLen = (int*)malloc(sizeof(int) * iRows * iCols); + + sciErr = getMatrixOfStringInList(pvApiCtx, piAddr, 1, &iRows, &iCols, piLen, NULL); + if(sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + + pstData = (char**)malloc(sizeof(char*) * iRows * iCols); + + for(int iter = 0 ; iter < iRows * iCols ; iter++) + { + pstData[iter] = (char*)malloc(sizeof(char) * (piLen[iter] + 1));//+ 1 for null termination + } + + sciErr = getMatrixOfStringInList(pvApiCtx, piAddr, 1, &iRows, &iCols, piLen, pstData); + if(sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + + if(!(strcmp(pstData[0],"imageSet")==0)) + { + Scierror(999, "Error: The input argument #1 is not of type imageSet.\n"); + return 0; + } + + // Extracting Description attribute of input argument + sciErr = getMatrixOfStringInList(pvApiCtx, piAddr, 2, &iRows, &iCols, NULL, NULL); + if(sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + + piLen = (int*)malloc(sizeof(int) * iRows * iCols); + + sciErr = getMatrixOfStringInList(pvApiCtx, piAddr, 2, &iRows, &iCols, piLen, NULL); + if(sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + + description = (char**)malloc(sizeof(char*) * iRows * iCols); + + for(int iter = 0 ; iter < iRows * iCols ; iter++) + { + description[iter] = (char*)malloc(sizeof(char) * (piLen[iter] + 1));//+ 1 for null termination + } + + sciErr = getMatrixOfStringInList(pvApiCtx, piAddr, 2, &iRows, &iCols, piLen, description); + if(sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + descriptionCount = iRows; + int i=0; + // Extracting Count attribute of input argument + sciErr = getMatrixOfInteger32InList(pvApiCtx, piAddr, 3, &iRows, &iCols, &count); + if(sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + + location = (char***) malloc(sizeof(char**) * descriptionCount); + sciErr = getListItemAddress(pvApiCtx, piAddr, 4, &piChild); + if(sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + for(int iter = 1; iter<=descriptionCount; iter++) + { + sciErr = getMatrixOfStringInList(pvApiCtx, piChild, iter, &iRows, &iCols, NULL, NULL); + if(sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + + piLen = (int*)malloc(sizeof(int) * iRows * iCols); + + sciErr = getMatrixOfStringInList(pvApiCtx, piChild, iter, &iRows, &iCols, piLen, NULL); + if(sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + + location[iter-1] = (char**)malloc(sizeof(char*) * iRows * iCols); + + for(int colIter = 0 ; colIter < iRows * iCols ; colIter++) + { + location[iter-1][colIter] = (char*)malloc(sizeof(char) * (piLen[colIter] + 1));//+ 1 for null termination + } + + sciErr = getMatrixOfStringInList(pvApiCtx, piChild, iter, &iRows, &iCols, piLen, location[iter-1]); + if(sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + } + // Second argument + sciErr = getVarAddressFromPosition(pvApiCtx, 2, &piAddr); + if (sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + if(!isListType(pvApiCtx, piAddr)) + { + Scierror(999, "Error: The input argument #2 is not of type bagOfFeatures.\n"); + return 0; + } + + // Extracting object type and checking if type is bagOfFeatures + sciErr = getMatrixOfStringInList(pvApiCtx, piAddr, 1, &iRows, &iCols, NULL, NULL); + if(sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + + piLen = (int*)malloc(sizeof(int) * iRows * iCols); + + sciErr = getMatrixOfStringInList(pvApiCtx, piAddr, 1, &iRows, &iCols, piLen, NULL); + if(sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + + pstData = (char**)malloc(sizeof(char*) * iRows * iCols); + + for(int iter = 0 ; iter < iRows * iCols ; iter++) + { + pstData[iter] = (char*)malloc(sizeof(char) * (piLen[iter] + 1));//+ 1 for null termination + } + + sciErr = getMatrixOfStringInList(pvApiCtx, piAddr, 1, &iRows, &iCols, piLen, pstData); + if(sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + + if(!(strcmp(pstData[0],"bagOfFeatures")==0)) + { + Scierror(999, "Error: The input argument #2 is not of type bagOfFeatures.\n"); + return 0; + } + // Extracting name of next argument takes three calls to getMatrixOfString + sciErr = getMatrixOfStringInList(pvApiCtx, piAddr, 2, &iRows, &iCols, NULL, NULL); + if (sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + + piLen = (int*) malloc(sizeof(int) * iRows * iCols); + + sciErr = getMatrixOfStringInList(pvApiCtx, piAddr, 2, &iRows, &iCols, piLen, NULL); + if (sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + + pstData = (char**) malloc(sizeof(char*) * iRows * iCols); + for(int iterPstData = 0; iterPstData < iRows * iCols; iterPstData++) + { + pstData[iterPstData] = (char*) malloc(sizeof(char) * piLen[iterPstData] + 1); + } + + sciErr = getMatrixOfStringInList(pvApiCtx, piAddr, 2, &iRows, &iCols, piLen, pstData); + if (sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + + if(iRows!=1 || iCols!=1) + { + Scierror(999, "1x1 Matrix expected for bagOfFeatures argument."); + return 0; + } + // Handling 3rd argument. + sciErr = getVarAddressFromPosition(pvApiCtx, 3, &piAddr); + if(sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + if(isStringType(pvApiCtx, piAddr)) + { + if(isScalar(pvApiCtx, piAddr)) + { + iRet = getAllocatedSingleString(pvApiCtx, piAddr, &stringData); + if(!iRet) + { + classifierName = stringData; + } + else + { + Scierror(999, "Error: Could not assign input arg #3 to local var.\n"); + return 0; + } + } + else + { + Scierror(999, "Error: The input argument #3 is not scalar type.\n"); + return 0; + } + } + else + { + Scierror(999, "Error: The input argument #3 is not a string.\n"); + return 0; + } + bagOfFeaturesLocation = pstData[0]; + + classifierLocation = classifierName; + strcat(classifierLocation, ".yml"); + //------Actual processing------// + FileStorage fs(bagOfFeaturesLocation, FileStorage::READ); + fs["dictionary"] >> dictionary; + fs.release(); + if(dictionary.rows==0 || dictionary.cols==0) + { + sciprint("Error: The provided file for bagOfFeatures may be invalid.\n"); + } + sciprint("Training an image category classifier for %d categories.\n",descriptionCount); + sciprint("-------------------------------------------------------\n\n"); + for(int i=0;isetVocabulary(dictionary); + for(int i=0; idetect(inp,keyPoints); + bowDE->compute(inp,keyPoints,features); + trainingData.push_back(features); + labels.push_back((int)i); + } + sciprint("done.\n"); + } + int cnt=4; + switch(n-1) + { + case 3: + + C=readdouble_from_scilab(cnt); + cnt++; + break; + case 4: + + C=readdouble_from_scilab(cnt); + cnt++; + coef=readdouble_from_scilab(cnt); + cnt++; + break; + case 5: + + C=readdouble_from_scilab(cnt); + cnt++; + coef=readdouble_from_scilab(cnt); + cnt++; + degree=readdouble_from_scilab(cnt); + cnt++; + break; + case 6: + + C=readdouble_from_scilab(cnt); + cnt++; + coef=readdouble_from_scilab(cnt); + cnt++; + degree=readdouble_from_scilab(cnt); + cnt++; + gamma=readdouble_from_scilab(cnt); + cnt++; + break; + case 7: + + C=readdouble_from_scilab(cnt); + cnt++; + coef=readdouble_from_scilab(cnt); + cnt++; + degree=readdouble_from_scilab(cnt); + cnt++; + gamma=readdouble_from_scilab(cnt); + cnt++; + kernelType=readdouble_from_scilab(cnt); + cnt++; + if(kernelType>5 || kernelType<-1) + { + Scierror(999,"Error: the kernel should be [-1,5]"); + return 0; + + } + break; + case 8: + + C=readdouble_from_scilab(cnt); + cnt++; + coef=readdouble_from_scilab(cnt); + cnt++; + degree=readdouble_from_scilab(cnt); + cnt++; + gamma=readdouble_from_scilab(cnt); + cnt++; + kernelType=readdouble_from_scilab(cnt); + cnt++; + if(kernelType>5 || kernelType<-1) + { + Scierror(999,"Error: the kernel should be [-1,5]"); + return 0; + + } + Nu=readdouble_from_scilab(cnt); + cnt++; + break; + + case 9: + + C=readdouble_from_scilab(cnt); + cnt++; + coef=readdouble_from_scilab(cnt); + cnt++; + degree=readdouble_from_scilab(cnt); + cnt++; + gamma=readdouble_from_scilab(cnt); + cnt++; + kernelType=readdouble_from_scilab(cnt); + cnt++; + if(kernelType>5 || kernelType<-1) + { + Scierror(999,"Error: the kernel should be between -1 and 5 \n"); + return 0; + + } + Nu=readdouble_from_scilab(cnt); + cnt++; + P=readdouble_from_scilab(cnt); + cnt++; + break; + case 10: + + C=readdouble_from_scilab(cnt); + cnt++; + coef=readdouble_from_scilab(cnt); + cnt++; + degree=readdouble_from_scilab(cnt); + cnt++; + gamma=readdouble_from_scilab(cnt); + cnt++; + kernelType=readdouble_from_scilab(cnt); + cnt++; + if(kernelType>5 || kernelType<-1) + { + Scierror(999,"Error: the kernel should be between -1 and 5 \n"); + return 0; + + } + Nu=readdouble_from_scilab(cnt); + cnt++; + P=readdouble_from_scilab(cnt); + cnt++; + setType=(int)readdouble_from_scilab(cnt); + cnt++; + if(setType<100 || setType>104) + { + Scierror(999,"Error: the type should be 100-104"); + return 0; + + + } + break; + } + + + + + + + + + + + sciprint("\n# Training the category classifier..."); + + + + + try{ + + Ptr svm = ml::SVM::create(); + svm->setType(setType); + svm->setGamma(gamma); + svm->setTermCriteria(cvTermCriteria(CV_TERMCRIT_ITER,100,0.000001)); + svm->setDegree(degree); + svm->setP(P); + svm->setCoef0(coef); + svm->train( trainingData , ml::ROW_SAMPLE , labels ); + transpose(trainingData,trainingData); + if(!svm->isTrained()) + { + Scierror(999,"\nthere was an error while training the model,please try again!\n"); + return 0; + + } + if(svm->isTrained()) + svm->save(classifierLocation); + sciprint("\ndone"); + + } + catch(cv::Exception& e) + { + const char* err=e.what(); + sciprint("%s",err); + + } + + + + + + + + + + + //------Create output arguments------// + sciErr = createList(pvApiCtx, nbInputArgument(pvApiCtx) + 1, 4, &piAddr); + if(sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + sciErr = createMatrixOfStringInList(pvApiCtx, nbInputArgument(pvApiCtx)+1, piAddr, 1, 1, 1, &objectType); + if(sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + sciErr = createMatrixOfStringInList(pvApiCtx, nbInputArgument(pvApiCtx)+1, piAddr, 2, 1, 1, &classifierLocation); + if(sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + sciErr = createMatrixOfStringInList(pvApiCtx, nbInputArgument(pvApiCtx)+1, piAddr, 3, 1, 1, &bagOfFeaturesLocation); + if(sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + sciErr = createMatrixOfStringInList(pvApiCtx, nbInputArgument(pvApiCtx)+1, piAddr, 4, descriptionCount, 1, description); + if(sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + + //------Return Arguments------// + AssignOutputVariable(pvApiCtx, 1) = nbInputArgument(pvApiCtx)+1; + ReturnArguments(pvApiCtx); + return 0; + } + /* ==================================================================== */ +} + + diff --git a/sci_gateway/cpp/opencv_trainSVMSGDClassifier.cpp b/sci_gateway/cpp/opencv_trainSVMSGDClassifier.cpp new file mode 100644 index 0000000..46e5fd8 --- /dev/null +++ b/sci_gateway/cpp/opencv_trainSVMSGDClassifier.cpp @@ -0,0 +1,569 @@ +/*************************************************** +Author : Nihar Rao +***************************************************/ +#include +#include +#include "opencv2/core/core.hpp" +#include "opencv2/highgui/highgui.hpp" +#include "opencv2/imgproc/imgproc.hpp" +#include "opencv2/features2d.hpp" +#include "opencv2/xfeatures2d.hpp" +#include "opencv2/ml.hpp" +#include "opencv2/opencv.hpp" + + +using namespace cv; +using namespace cv::xfeatures2d; +using namespace std; +using namespace cv::ml; + + + +extern "C" +{ + #include "api_scilab.h" + #include "Scierror.h" + #include "BOOL.h" + #include + #include "sciprint.h" + + double readdoubles_from_scilab(int cnt) + { + + SciErr sciErr; + int *piAddr=NULL; + double val=0; + int intErr; + + sciErr = getVarAddressFromPosition(pvApiCtx,cnt,&piAddr); + if (sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + intErr = getScalarDouble(pvApiCtx, piAddr ,&val); + + if(isDoubleType(pvApiCtx, piAddr)) + return val; + else + { + Scierror(999,"Error: the input argument is not of type double"); + return 0; + + + } + + + } + + + + int opencv_trainSVMSGDClassifier(char *fname, unsigned long fname_len) + { + // Error management variables + SciErr sciErr; + + //------Local variables------// + int upright = 1; + Ptr matcher = DescriptorMatcher::create("FlannBased"); + Ptr detector = SURF::create(400, 4, 2, 1, int(upright)); + Ptr extractor=detector; + Ptr bowDE=makePtr(extractor,matcher); + //SurfFeatureDetector detector(1, 4, 2, 1, int(upright)); + char *fileName = NULL; + Mat dictionary,inp,features; + vector keyPoints; + + + int *piAddr = NULL; + int *piChild = NULL; + int iRows, iCols; + char **pstData = NULL; + int *piLen = NULL; + int *count = NULL; + char **description = NULL; + char ***location = NULL; + char *bagOfFeaturesLocation = NULL; + int descriptionCount; + char *classifierLocation = "classifier.yml"; + char *objectType = "classifier"; + int intErr = 0; + char* stringData = NULL; + char* classifierName; + int iRet; + + double initStepSize=0.2,marginreg=0,optimalParam=0,stepDecreasingPower=0.1;//all model paramenter set to their default values + int marginType=0,svmsgdType=0; + + + //------Check number of parameters------// + CheckInputArgument(pvApiCtx, 3,9); + CheckOutputArgument(pvApiCtx, 1, 1); + + //------Get input arguments------// + int n=*getNbInputArgument(pvApiCtx); + sciErr = getVarAddressFromPosition(pvApiCtx, 1, &piAddr); + if (sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + if(!isListType(pvApiCtx, piAddr)) + { + Scierror(999, "Error: The input argument #1 is not of type imageSet.\n"); + return 0; + } + + // Extracting object type and checking if type is imageSet + sciErr = getMatrixOfStringInList(pvApiCtx, piAddr, 1, &iRows, &iCols, NULL, NULL); + if(sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + + piLen = (int*)malloc(sizeof(int) * iRows * iCols); + + sciErr = getMatrixOfStringInList(pvApiCtx, piAddr, 1, &iRows, &iCols, piLen, NULL); + if(sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + + pstData = (char**)malloc(sizeof(char*) * iRows * iCols); + + for(int iter = 0 ; iter < iRows * iCols ; iter++) + { + pstData[iter] = (char*)malloc(sizeof(char) * (piLen[iter] + 1));//+ 1 for null termination + } + + sciErr = getMatrixOfStringInList(pvApiCtx, piAddr, 1, &iRows, &iCols, piLen, pstData); + if(sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + + if(!(strcmp(pstData[0],"imageSet")==0)) + { + Scierror(999, "Error: The input argument #1 is not of type imageSet.\n"); + return 0; + } + + // Extracting Description attribute of input argument + sciErr = getMatrixOfStringInList(pvApiCtx, piAddr, 2, &iRows, &iCols, NULL, NULL); + if(sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + + piLen = (int*)malloc(sizeof(int) * iRows * iCols); + + sciErr = getMatrixOfStringInList(pvApiCtx, piAddr, 2, &iRows, &iCols, piLen, NULL); + if(sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + + description = (char**)malloc(sizeof(char*) * iRows * iCols); + + for(int iter = 0 ; iter < iRows * iCols ; iter++) + { + description[iter] = (char*)malloc(sizeof(char) * (piLen[iter] + 1));//+ 1 for null termination + } + + sciErr = getMatrixOfStringInList(pvApiCtx, piAddr, 2, &iRows, &iCols, piLen, description); + if(sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + descriptionCount = iRows; + + // Extracting Count attribute of input argument + sciErr = getMatrixOfInteger32InList(pvApiCtx, piAddr, 3, &iRows, &iCols, &count); + if(sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + + location = (char***) malloc(sizeof(char**) * descriptionCount); + sciErr = getListItemAddress(pvApiCtx, piAddr, 4, &piChild); + if(sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + for(int iter = 1; iter<=descriptionCount; iter++) + { + sciErr = getMatrixOfStringInList(pvApiCtx, piChild, iter, &iRows, &iCols, NULL, NULL); + if(sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + + piLen = (int*)malloc(sizeof(int) * iRows * iCols); + + sciErr = getMatrixOfStringInList(pvApiCtx, piChild, iter, &iRows, &iCols, piLen, NULL); + if(sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + + location[iter-1] = (char**)malloc(sizeof(char*) * iRows * iCols); + + for(int colIter = 0 ; colIter < iRows * iCols ; colIter++) + { + location[iter-1][colIter] = (char*)malloc(sizeof(char) * (piLen[colIter] + 1));//+ 1 for null termination + } + + sciErr = getMatrixOfStringInList(pvApiCtx, piChild, iter, &iRows, &iCols, piLen, location[iter-1]); + if(sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + } + // Second argument + sciErr = getVarAddressFromPosition(pvApiCtx, 2, &piAddr); + if (sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + if(!isListType(pvApiCtx, piAddr)) + { + Scierror(999, "Error: The input argument #2 is not of type bagOfFeatures.\n"); + return 0; + } + + // Extracting object type and checking if type is bagOfFeatures + sciErr = getMatrixOfStringInList(pvApiCtx, piAddr, 1, &iRows, &iCols, NULL, NULL); + if(sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + + piLen = (int*)malloc(sizeof(int) * iRows * iCols); + + sciErr = getMatrixOfStringInList(pvApiCtx, piAddr, 1, &iRows, &iCols, piLen, NULL); + if(sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + + pstData = (char**)malloc(sizeof(char*) * iRows * iCols); + + for(int iter = 0 ; iter < iRows * iCols ; iter++) + { + pstData[iter] = (char*)malloc(sizeof(char) * (piLen[iter] + 1));//+ 1 for null termination + } + + sciErr = getMatrixOfStringInList(pvApiCtx, piAddr, 1, &iRows, &iCols, piLen, pstData); + if(sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + + if(!(strcmp(pstData[0],"bagOfFeatures")==0)) + { + Scierror(999, "Error: The input argument #2 is not of type bagOfFeatures.\n"); + return 0; + } + // Extracting name of next argument takes three calls to getMatrixOfString + sciErr = getMatrixOfStringInList(pvApiCtx, piAddr, 2, &iRows, &iCols, NULL, NULL); + if (sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + + piLen = (int*) malloc(sizeof(int) * iRows * iCols); + + sciErr = getMatrixOfStringInList(pvApiCtx, piAddr, 2, &iRows, &iCols, piLen, NULL); + if (sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + + pstData = (char**) malloc(sizeof(char*) * iRows * iCols); + for(int iterPstData = 0; iterPstData < iRows * iCols; iterPstData++) + { + pstData[iterPstData] = (char*) malloc(sizeof(char) * piLen[iterPstData] + 1); + } + + sciErr = getMatrixOfStringInList(pvApiCtx, piAddr, 2, &iRows, &iCols, piLen, pstData); + if (sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + + if(iRows!=1 || iCols!=1) + { + Scierror(999, "1x1 Matrix expected for bagOfFeatures argument."); + return 0; + } + // Handling 3rd argument. + sciErr = getVarAddressFromPosition(pvApiCtx, 3, &piAddr); + if(sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + if(isStringType(pvApiCtx, piAddr)) + { + if(isScalar(pvApiCtx, piAddr)) + { + char* stringData = NULL; + + iRet = getAllocatedSingleString(pvApiCtx, piAddr, &stringData); + if(!iRet) + { + classifierName = stringData; + } + else + { + Scierror(999, "Error: Could not assign input arg #3 to local var.\n"); + return 0; + } + } + else + { + Scierror(999, "Error: The input argument #3 is not scalar type.\n"); + return 0; + } + } + else + { + Scierror(999, "Error: The input argument #3 is not a string.\n"); + return 0; + } + bagOfFeaturesLocation = pstData[0]; + classifierLocation = classifierName; + strcat(classifierLocation, ".yml"); + //------Actual processing------// + FileStorage fs(bagOfFeaturesLocation, FileStorage::READ); + fs["dictionary"] >> dictionary; + fs.release(); + if(dictionary.rows==0 || dictionary.cols==0) + { + sciprint("Error: The provided file for bagOfFeatures may be invalid.\n"); + } + sciprint("Training an image category classifier for %d categories.\n",descriptionCount); + sciprint("-------------------------------------------------------\n\n"); + for(int i=0;isetVocabulary(dictionary); + for(int i=0; idetect(inp,keyPoints); + bowDE->compute(inp,keyPoints,features); + trainingData.push_back(features); + labels.push_back((int)i); + } + sciprint("done.\n"); + } + int cnt=4; + switch(n-1) + { + case 3: + + initStepSize=readdoubles_from_scilab(cnt); + cnt++; + break; + case 4: + + initStepSize=readdoubles_from_scilab(cnt); + cnt++; + marginreg=readdoubles_from_scilab(cnt); + cnt++; + break; + case 5: + + initStepSize=readdoubles_from_scilab(cnt); + cnt++; + marginreg=readdoubles_from_scilab(cnt); + cnt++; + marginType=(int)readdoubles_from_scilab(cnt);//default type of scalar is double in scilab.so typecasting is needed + if(marginType>1 || marginType<0) + { + Scierror(999,"Error: the marginType should be either 0 or 1"); + return 0; + + } + cnt++; + break; + case 6: + + initStepSize=readdoubles_from_scilab(cnt); + cnt++; + marginreg=readdoubles_from_scilab(cnt); + cnt++; + marginType=(int)readdoubles_from_scilab(cnt);//default type of scalar is double in scilab.so typecasting is needed + if(marginType>1 || marginType<0) + { + Scierror(999,"Error: the marginType should be either 0 or 1"); + return 0; + + } + cnt++; + optimalParam=readdoubles_from_scilab(cnt); + cnt++; + break; + case 7: + + initStepSize=readdoubles_from_scilab(cnt); + cnt++; + marginreg=readdoubles_from_scilab(cnt); + cnt++; + marginType=(int)readdoubles_from_scilab(cnt);//default type of scalar is double in scilab.so typecasting is needed + if(marginType>1 || marginType<0) + { + Scierror(999,"Error: the marginType should be either 0 or 1"); + return 0; + + } + cnt++; + optimalParam=readdoubles_from_scilab(cnt); + cnt++; + stepDecreasingPower=readdoubles_from_scilab(cnt); + cnt++; + break; + case 8: + + initStepSize=readdoubles_from_scilab(cnt); + cnt++; + marginreg=readdoubles_from_scilab(cnt); + cnt++; + marginType=(int)readdoubles_from_scilab(cnt);//default type of scalar is double in scilab.so typecasting is needed + if(marginType>1 || marginType<0) + { + Scierror(999,"Error: the marginType should be either 0 or 1"); + return 0; + + } + cnt++; + optimalParam=readdoubles_from_scilab(cnt); + cnt++; + stepDecreasingPower=readdoubles_from_scilab(cnt); + cnt++; + svmsgdType=(int)readdoubles_from_scilab(cnt);//default type of scalar is double in scilab.so typecasting is needed + if(svmsgdType>1 || svmsgdType<0) + { + Scierror(999,"Error: the marginType should be either 0 or 1"); + return 0; + + } + + break; + + + } + sciprint("\n# Training the category classifier..."); + + + + + try{ + + cv::Ptr svmsgd = SVMSGD::create(); + svmsgd->setInitialStepSize(initStepSize); + svmsgd->setMarginRegularization(marginreg); + svmsgd->setMarginType(marginType); + svmsgd->setOptimalParameters(svmsgdType,marginType); + svmsgd->setStepDecreasingPower(stepDecreasingPower); + svmsgd->setSvmsgdType(svmsgdType); + svmsgd->setTermCriteria(cvTermCriteria(CV_TERMCRIT_ITER,100,0.000001)); + svmsgd->train( trainingData , ml::ROW_SAMPLE , labels ); + transpose(trainingData,trainingData); + if(!svmsgd->isTrained()) + { + Scierror(999,"\nthere was an error while training the model,please try again!\n"); + return 0; + + } + if(svmsgd->isTrained()) + svmsgd->save(classifierLocation); + sciprint("\ndone"); + + } + catch(cv::Exception& e) + { + const char* err=e.what(); + sciprint("%s",err); + + } + + + + + + + + + + + //------Create output arguments------// + sciErr = createList(pvApiCtx, nbInputArgument(pvApiCtx) + 1, 4, &piAddr); + if(sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + sciErr = createMatrixOfStringInList(pvApiCtx, nbInputArgument(pvApiCtx)+1, piAddr, 1, 1, 1, &objectType); + if(sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + sciErr = createMatrixOfStringInList(pvApiCtx, nbInputArgument(pvApiCtx)+1, piAddr, 2, 1, 1, &classifierLocation); + if(sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + sciErr = createMatrixOfStringInList(pvApiCtx, nbInputArgument(pvApiCtx)+1, piAddr, 3, 1, 1, &bagOfFeaturesLocation); + if(sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + sciErr = createMatrixOfStringInList(pvApiCtx, nbInputArgument(pvApiCtx)+1, piAddr, 4, descriptionCount, 1, description); + if(sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + + //------Return Arguments------// + AssignOutputVariable(pvApiCtx, 1) = nbInputArgument(pvApiCtx)+1; + ReturnArguments(pvApiCtx); + return 0; + } + /* ==================================================================== */ +} + diff --git a/sci_gateway/cpp/opencv_undistortPoints.cpp b/sci_gateway/cpp/opencv_undistortPoints.cpp new file mode 100644 index 0000000..5e7ef58 --- /dev/null +++ b/sci_gateway/cpp/opencv_undistortPoints.cpp @@ -0,0 +1,202 @@ +/*************************************************** +Author : Nihar Rao +***************************************************/ + +#include +#include "opencv2/core/core.hpp" +#include "opencv2/highgui/highgui.hpp" +#include "opencv2/opencv.hpp" +#include +using namespace cv; +using namespace std; +extern "C" +{ + #include "api_scilab.h" + #include "Scierror.h" + #include "BOOL.h" + #include + #include + #include "../common.h" + + int opencv_undistortPoints(char *fname, unsigned long fname_len) + { + //variables + + int i,j,k,n,m; + int iRows=0,iCols=0; + int *piAddr1 = NULL; + int *piAddr2 = NULL; + int *piAddr3 = NULL; + int *piAddr4 = NULL; + int *piAddr5 = NULL; + + double *pdblReal = NULL; + + SciErr sciErr; + + //function varible + std::vector< Point2d > Src; + std::vector< Point2d > dst; + double cameraMatrix [3][3]; + double newCameraMatrix [3][3]; + double *distCoeffs = NULL; + double RectificationMatrix[3][3]; + + /*------------------------------------------- Checking Input Argument ----------------------------------------------------*/ + + CheckInputArgument(pvApiCtx, 5, 5); + CheckOutputArgument(pvApiCtx, 1, 1) ; + + /*------------------------------------- Source matrix :- First argument of the input -------------------------------------*/ + + sciErr = getVarAddressFromPosition(pvApiCtx, 1, &piAddr1); + if (sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + sciErr = getMatrixOfDouble(pvApiCtx, piAddr1, &iRows, &iCols, &pdblReal); + if(sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + // For 1 X N single channel + for(i = 0; i < iRows; ++i) + Src.push_back( Point2d(pdblReal[(0 * iRows) + i], pdblReal[(1 * iRows) + i])); + + /* ------------------------------------ Camera matrix :- Second argument of the input -------------------------------------*/ + + sciErr = getVarAddressFromPosition(pvApiCtx, 2, &piAddr2); + if (sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + sciErr = getMatrixOfDouble(pvApiCtx, piAddr2, &iRows, &iCols, &pdblReal); + if(sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + Mat cameraMat(3, 3, CV_64F); + for(i=0;i<3;i++) + for(j=0;j<3;j++) + cameraMat.at(i,j) = pdblReal[(j * 3) + i]; + + + /* ------------------------------------ Distortion Coefficient matrix :- Third argument of the input -------------------------------------*/ + + sciErr = getVarAddressFromPosition(pvApiCtx,3,&piAddr3); + if (sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + sciErr = getMatrixOfDouble(pvApiCtx, piAddr3, &iRows, &iCols, &pdblReal); + if(sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + + if(iRows== 1) + n = iCols; + else if (iCols == 1) + n = iRows; + else{ + Scierror(1,"Points matrix (arg 4) must be a 2 X N matrix"); + return 0; + } + if(n==4 or n==5 or n==8); + else{ + Scierror(1," n must be 4 or 5 or 8"); + return 0; + } + + + + Mat distCoeffsActual(1,n,CV_64F); + for(i=0;i(0,i) = pdblReal[i]; + + + /* ------------------------------------ Rectification matrix :- Fourth argument of the input -------------------------------------*/ + + sciErr = getVarAddressFromPosition(pvApiCtx, 4, &piAddr4); + if (sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + sciErr = getMatrixOfDouble(pvApiCtx, piAddr4, &iRows, &iCols, &pdblReal); + if(sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + Mat RectMat(3, 3, CV_64F); + for(i=0;i<3;i++) + for(j=0;j<3;j++) + RectMat.at(i,j) =pdblReal[(j*3)+i]; + + + /* ------------------------------------ New Camera matrix :- Fifth argument of the input -------------------------------------*/ + + sciErr = getVarAddressFromPosition(pvApiCtx,5,&piAddr5); + if (sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + sciErr = getMatrixOfDouble(pvApiCtx, piAddr5, &iRows, &iCols , &pdblReal); + if(sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + + Mat newCameraMat(3,3,CV_64F); + for(i=0;i<3;i++) + for(j=0;j<3;j++) + newCameraMat.at(i, j) =pdblReal[(j*3)+i]; + + + + /* opencv function for undistortPoints */ + try + { + fisheye::undistortPoints(Src, dst, cameraMat, distCoeffsActual, RectMat, newCameraMat); + } + catch(cv::Exception& e) + { + + sciprint("%s",e.what()); + + + } + /* Writing to Scilab */ + double *pstdata = NULL; + pstdata = (double*)malloc(sizeof(double) * dst.size() * 2); + + for(i = 0; i < dst.size(); i++) + { + pstdata[i + 0 * dst.size()] = dst[i].x; + pstdata[i + 1 * dst.size()] = dst[i].y; + } + + sciErr = createMatrixOfDouble(pvApiCtx, nbInputArgument(pvApiCtx) + 1, dst.size(), 2, pstdata); + if(sciErr.iErr){ + printError(&sciErr, 0); + return 0; + } + + //Assigning the list as the Output Variable + AssignOutputVariable(pvApiCtx, 1) = nbInputArgument(pvApiCtx) + 1; + //Returning the Output Variables as arguments to the Scilab environment + ReturnArguments(pvApiCtx); + return 0; + + } +/* ==================================================================== */ +} \ No newline at end of file diff --git a/sci_gateway/cpp/opencv_xyz2rgb.cpp b/sci_gateway/cpp/opencv_xyz2rgb.cpp new file mode 100644 index 0000000..cafe54a --- /dev/null +++ b/sci_gateway/cpp/opencv_xyz2rgb.cpp @@ -0,0 +1,280 @@ +/* ==================================================================== */ +/* Author :Tess Zacharias */ +/* ==================================================================== */ +/* overloaded function */ +/* Syntax : return_matrix_3_xyz_values=lab2xyz(matrix_of_3_labvalues a) */ +/* Syntax : return_matrix_3_xyz_values=lab2xyz(matrix_of_3_labvalues a,String1 Name,String2 value) */ +/* ==================================================================== */ +/* ==================================================================== */ +#include +#include "opencv2/core/core.hpp" +#include "opencv2/highgui/highgui.hpp" +#include "opencv2/opencv.hpp" +#include +#include +#include +#include +using namespace cv; +using namespace std; + extern "C" + { + #include "api_scilab.h" + #include "Scierror.h" + #include "BOOL.h" + #include + // #include "../common.h" + #define REF_X .95047; // Observer= 2°, Illuminant= D65 +#define REF_Y 1.00000; +#define REF_Z 1.08883; + +struct Color +{ + float X,Y,Z,R,G,B; +}; + +Color xyz2rgb1(float X, float Y, float Z) +{ + + float x = X; + float y = Y; + float z = Z; + float R1 = 3.2404542*x-1.5371385*y-0.4985314*z; + float G1 =-0.9692660*x+1.8760108*y+0.0415560 *z; + float B1 = 0.0556434*x-0.2040259*y+1.0572252*z; + if( R1 > 0.0031308 ) + R1 = 1.055 * ( pow( R1, 1./2.4 ) ) - 0.055; + else + R1 = 12.92 * R1; + if( G1 > 0.0031308 ) + G1 = 1.055 * ( pow( G1, 1./2.4 ) ) - 0.055; + else + G1 = 12.92 * G1; + if( B1 > 0.0031308 ) + B1 = 1.055 * ( pow( B1, 1./2.4 ) ) - 0.055; + else + B1= 12.92 * B1; + + /*R1 = R1*REF_X; + G1 = G1*REF_Y; + B1 = B1*REF_Z; */ + /* R1 = R1 * 255; + G1 = G1 * 255; + B1 = B1 * 255;*/ + Color rgb; + rgb.R= R1; + rgb.G= G1; + rgb.B= B1; + return rgb; + +} + Color xyz2rgb2(float X, float Y, float Z,char *s) +{ + double REF_X1; + double REF_Y1; + double REF_Z1; + if(!strcmp(s,"a")) + { + REF_X1=1.0985; + REF_Y1= 1.0000; + REF_Z1=0.3558; + } + else if(!strcmp(s,"c")) + { + REF_X1=0.9807; + REF_Y1= 1.0000; + REF_Z1=1.1822; + } + else if(!strcmp(s,"d50")) + { + REF_X1=0.9642; + REF_Y1= 1.0000; + REF_Z1=0.8251; + } + else if(!strcmp(s,"d65")) + { + REF_X1=0.9504; + REF_Y1= 1.0000; + REF_Z1= 1.0888; + } + else if(!strcmp(s,"icc")) + { + REF_X1=0.962; + REF_Y1=1.000; + REF_Z1= 0.8249; + } + else if(!strcmp(s,"e")) + { + REF_X1=1.000; + REF_Y1=1.000; + REF_Z1=1.000; + } + float x = X; + float y = Y; + float z = Z; + float R1 = 3.2406*x-1.5372*y-0.4986*z; + float G1 =-0.9689*x+1.8758*y+0.0415 *z; + float B1 = 0.0557*x-0.2040*y+1.0570*z; + if( R1 > 0.0031308 ) + R1 = 1.055 * ( pow( R1, 1./2.4 ) ) - 0.055; + else + R1 = 12.92 * R1; + if( G1 > 0.0031308 ) + G1 = 1.055 * ( pow( G1, 1./2.4 ) ) - 0.055; + else + G1 = 12.92 * G1; + if( B1 > 0.0031308 ) + B1 = 1.055 * ( pow( B1, 1./2.4 ) ) - 0.055; + else + B1= 12.92 * B1; + + /*R1 = R1*REF_X; + G1 = G1*REF_Y; + B1 = B1*REF_Z;*/ + /* R1 = R1 * 255; + G1 = G1 * 255; + B1 = B1 * 255; */ + Color rgb; + rgb.R= R1; + rgb.G= G1; + rgb.B= B1; + return rgb; + + +} + int opencv_xyz2rgb(char *fname, unsigned long fname_len) + { + // Error management variable + SciErr sciErr; + //variable info + int iRows = 0; + int iCols = 0; + int piRows = 0; + int piCols = 0; + int* piAddr=NULL; + int* piAddr1=NULL; + int* piAddr3=NULL; + double *value=NULL; + int* piLen = NULL; + char **val; + int i,j; + int error; + Color out; + double check; + Mat img,dst; + float X,Y,Z; + int *piAddrNew = NULL; + //checking output argument + CheckOutputArgument(pvApiCtx,1,1); + //checking if number of input arguments are 3 + + int k=0; + // SciErr getMatrixOfDoubleInList(void* _pvCtx, int* _piParent, int _iItemPos, int* _piRows, int* _piCols, double** _pdblReal) + double *pstDataR = NULL; + double *pstDataG = NULL; + double *pstDataB = NULL; + sciErr = getVarAddressFromPosition(pvApiCtx,1,&piAddr); + if(sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + //retrive the matrix of the R values + sciErr = getMatrixOfDoubleInList(pvApiCtx, piAddr, 1, &iRows, &iCols, &pstDataR); + if(sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + //retrive address of the list + sciErr = getVarAddressFromPosition(pvApiCtx,1,&piAddr); + if(sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + //retrive the matrix of the G values + sciErr = getMatrixOfDoubleInList(pvApiCtx, piAddr, 2, &iRows, &iCols, &pstDataG); + if(sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + //retrive address of the list + sciErr = getVarAddressFromPosition(pvApiCtx,1,&piAddr); + if(sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + //retrive the matrix of the B values + sciErr = getMatrixOfDoubleInList(pvApiCtx, piAddr, 3, &iRows, &iCols, &pstDataB); + if(sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + int m=0; + double *r,*g,*b; + r=(double *)malloc(sizeof(double)*iRows*iCols); + g=(double *)malloc(sizeof(double)*iRows*iCols); + b=(double *)malloc(sizeof(double)*iRows*iCols); + for(int i=0;i(i,j); + X= (pstDataR[k]); + Y= (pstDataG[k]); + Z= (pstDataB[k++]); + out=xyz2rgb1(X,Y,Z); + //cout< +#include "opencv2/core/core.hpp" +#include "opencv2/highgui/highgui.hpp" +#include "opencv2/opencv.hpp" +#include "opencv2/imgproc/imgproc.hpp" //new header file for cvtColor function of opencv +#include +using namespace cv; +using namespace std; +extern "C" +{ +#include "api_scilab.h" +#include "Scierror.h" +#include "BOOL.h" +#include +#include +#include "../common.h" +int rgb2gray(char *fname, unsigned long fname_len) +{ + + // Error management variable + SciErr sciErr; + //checking input argument + CheckInputArgument(pvApiCtx,1,1); + //checking output argument + CheckOutputArgument(pvApiCtx, 1, 1) + Mat img,grayimg; + //calling function + retrieveImage(img,1); + cvtColor(img, grayimg, CV_BGR2GRAY ); + string tempstring = type2str(grayimg.type()); + char* checker = (char *)malloc(tempstring.size() + 1); + memcpy(checker, tempstring.c_str(), tempstring.size() + 1); + returnImage(checker,grayimg,1); + //returning output variable + AssignOutputVariable(pvApiCtx, 1) = nbInputArgument(pvApiCtx) + 1; + ReturnArguments(pvApiCtx); + return 0; +} + +/* ==================================================================== */ +} diff --git a/sci_gateway/loader_gateway.sce b/sci_gateway/loader_gateway.sce new file mode 100644 index 0000000..6809d99 --- /dev/null +++ b/sci_gateway/loader_gateway.sce @@ -0,0 +1,24 @@ +// This file is released under the 3-clause BSD license. See COPYING-BSD. +// Generated by builder_gateway.sce: Please, do not edit this file + +try + v = getversion("scilab"); +catch + v = [ 5 0 ]; // or older +end +if (v(1) <= 5) & (v(2) < 3) then + // new API in scilab 5.3 + error(gettext("Scilab 5.3 or more is required.")); +end + +sci_gateway_dir = get_absolute_file_path("loader_gateway.sce"); +current_dir = pwd(); + +chdir(sci_gateway_dir); +if ( isdir("cpp") ) then + chdir("cpp"); + exec("loader.sce"); +end + +chdir(current_dir); +clear sci_gateway_dir current_dir v; From a5d76ca6cd716a0ee73b81093253393e9c136b07 Mon Sep 17 00:00:00 2001 From: shubham0108 Date: Thu, 27 Jul 2017 16:44:58 +0530 Subject: [PATCH 2/6] Second Commit --- sci_gateway/cpp/opencv_findContours.cpp | 6 ++---- 1 file changed, 2 insertions(+), 4 deletions(-) diff --git a/sci_gateway/cpp/opencv_findContours.cpp b/sci_gateway/cpp/opencv_findContours.cpp index 785a587..d7f28f6 100644 --- a/sci_gateway/cpp/opencv_findContours.cpp +++ b/sci_gateway/cpp/opencv_findContours.cpp @@ -45,8 +45,6 @@ extern "C" Mat src; retrieveImage(src,1);//Retrieving the input image src.convertTo(src,CV_8U);//Converting the input image to 8-bit image - cvtColor(src,src,CV_BGR2GRAY);//Converting to grayscale - //threshold(src,src,0,255,THRESH_BINARY); sciErr = getVarAddressFromPosition(pvApiCtx,2,&piAddr2); if (sciErr.iErr) { @@ -142,8 +140,8 @@ extern "C" for(j=0;j Date: Thu, 27 Jul 2017 16:49:41 +0530 Subject: [PATCH 3/6] Second Commit with images --- images/apple.png | Bin 0 -> 705 bytes images/b1.jpeg | Bin 0 -> 51993 bytes images/b2.jpeg | Bin 0 -> 49824 bytes images/cnoise.jpeg | Bin 0 -> 39690 bytes images/cnoise1.jpg | Bin 0 -> 58034 bytes images/cnoise2.jpg | Bin 0 -> 58034 bytes images/cnoise3.jpg | Bin 0 -> 58034 bytes images/cnoise4.jpg | Bin 0 -> 58034 bytes images/cnoise5.jpg | Bin 0 -> 58034 bytes images/colnoise.jpeg | Bin 0 -> 39690 bytes images/colnoise1.jpeg | Bin 0 -> 39690 bytes images/colnoise2.jpeg | Bin 0 -> 39690 bytes images/colnoise3.jpeg | Bin 0 -> 39690 bytes images/colnoise4.jpeg | Bin 0 -> 39690 bytes images/colnoise5.jpeg | Bin 0 -> 39690 bytes images/happy.jpg | Bin 0 -> 10105 bytes images/image1.jpg | Bin 0 -> 186417 bytes images/image2.jpg | Bin 0 -> 186417 bytes images/image3.jpg | Bin 0 -> 186417 bytes images/image4.jpg | Bin 0 -> 186417 bytes images/image5.jpg | Bin 0 -> 186417 bytes images/images.jpeg | Bin 0 -> 3296 bytes images/lena1.jpeg | Bin 0 -> 10076 bytes images/lena_noiseImg.jpg | Bin 0 -> 186417 bytes images/man.jpg | Bin 0 -> 18282 bytes images/orig.jpg | Bin 0 -> 15744 bytes images/photo.jpg | Bin 0 -> 12275 bytes images/photo1.jpg | Bin 0 -> 54769 bytes images/taj.jpg | Bin 0 -> 61041 bytes images/water.jpg | Bin 0 -> 13379 bytes 30 files changed, 0 insertions(+), 0 deletions(-) create mode 100644 images/apple.png create mode 100644 images/b1.jpeg create mode 100644 images/b2.jpeg create mode 100644 images/cnoise.jpeg create mode 100644 images/cnoise1.jpg create mode 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| 19 +++++++++++++++++++ 1 file changed, 19 insertions(+) create mode 100644 azure-pipelines.yml diff --git a/azure-pipelines.yml b/azure-pipelines.yml new file mode 100644 index 0000000..aa91291 --- /dev/null +++ b/azure-pipelines.yml @@ -0,0 +1,19 @@ +# Starter pipeline +# Start with a minimal pipeline that you can customize to build and deploy your code. +# Add steps that build, run tests, deploy, and more: +# https://aka.ms/yaml + +trigger: +- master + +pool: + vmImage: 'ubuntu-latest' + +steps: +- script: echo Hello, world! + displayName: 'Run a one-line script' + +- script: | + echo Add other tasks to build, test, and deploy your project. + echo See https://aka.ms/yaml + displayName: 'Run a multi-line script' From 743740adb837b69f4d9579047c65e0df7452e679 Mon Sep 17 00:00:00 2001 From: Shubham Lohakare Date: Fri, 1 May 2020 14:51:17 +0530 Subject: [PATCH 5/6] Create ccpp.yml --- .github/workflows/ccpp.yml | 23 +++++++++++++++++++++++ 1 file changed, 23 insertions(+) create mode 100644 .github/workflows/ccpp.yml diff --git a/.github/workflows/ccpp.yml b/.github/workflows/ccpp.yml new file mode 100644 index 0000000..e323326 --- /dev/null +++ b/.github/workflows/ccpp.yml @@ -0,0 +1,23 @@ +name: C/C++ CI + +on: + push: + branches: [ master ] + pull_request: + branches: [ master ] + +jobs: + build: + + runs-on: ubuntu-latest + + steps: + - uses: actions/checkout@v2 + - name: configure + run: ./configure + - name: make + run: make + - name: make check + run: make check + - name: make distcheck + run: make distcheck From 68cddb2ca8dabddfe47251ac6647011acb849a2c Mon Sep 17 00:00:00 2001 From: Shubham Lohakare Date: Fri, 1 May 2020 14:53:39 +0530 Subject: [PATCH 6/6] Update ccpp.yml --- .github/workflows/ccpp.yml | 7 +------ 1 file changed, 1 insertion(+), 6 deletions(-) diff --git a/.github/workflows/ccpp.yml b/.github/workflows/ccpp.yml index e323326..2fc4e5a 100644 --- a/.github/workflows/ccpp.yml +++ b/.github/workflows/ccpp.yml @@ -13,11 +13,6 @@ jobs: steps: - uses: actions/checkout@v2 - - name: configure - run: ./configure - - name: make - run: make - - name: make check - run: make check + - name: make distcheck run: make distcheck

    • ?vN0tY_oS9X__b=GdcBystDo zpB?BS!}|AL5%&$|sByY?z@Id8ULWxMY`eLA3fc6m@&4?dvTtn0{q`M=J%>(=w{4%x ztN4)=Xla{#PNLlkmK=QOpK0!XL2y!#)cXgA9Cm2 z0c_y=oQ8ideCREFU>99{Q8W4z%&@U+{oSW+wZI4QQH%Iqq+#c(=n2u&4aJ^$Pdx0= zXU2r*G|$t9%li#3U};=4IW;P)_2~Ts`HQg%Tq19u6Qy3 z8;y+j3o!6|gLD2-ITIu2md_5?E9Q{y0*FY}Dir7px6b&Usd#DN_1mWgLm&ObJ&8#ZF!*(bbsE=)9L z&b6~1cjTCRn4g#B?x@E4ilffsSJjwz2x3oh15ejgk4MkO;1%&8YC@l2!#Fx;_ba)g zx6J#WecI0j>FtZKL5!(CK8Js!JX}lkh=u-sR)kOD0CVIn>3&&cKkTX0#QD&7=(|6d zOY=c@Q7_vzx)3&rpV-MIj$@yb3;FWdWkuvGH|BkVx%lqEm@D3~#kd>zDGuaAti(>N z#?d&i2QyD!uotl&CL(w#KDqpmP1iAgj2C*yxYnsJ@QJp`0bLWZf<^8-$UjtnP1iD; z#dtj2C`aixnSV(JyukL!MwT%-a;JBK{gwFrp{D9sh~pUs%|%T5vT^RaMs(Z!A&)=q z_^Zyhd=V;LO?5UF%z;Z+^tGIj3m5AEyNmRY`zQWi-Uf@eMCgIR2O{jeAi{@x1Rs3Q zMqr!)^a#Y5wadDq-g_c=%+Yt`n(htAvR?3m4En5N^pU4Gh-Y)ORh5JBTC773S7Jw} zUsb~@RnWMt7HRE^LB1AXVSE?WOkx4w>8%vsPa8X6l;V3+yk+tAI=&xl*)LqPT|IkE zx)#JhEj(WIF0@Q7v4;=p$}_lgy(+@bqfzToUF#c7KIHh3h@SCY7T3~?;?wK#-H(0% zb1-2qWFFjDOYmG5)(XUaYfPyF^7vqmF>~;YIWh6POwIm_HBspG^|_iCT(5}0tSh?v z=fMG=1GtXAP7iChFJ1Bmr%xI?FYE4g%3SVzi04o4_pm6F`)w@B{u zo2-S?Tr={IXFXWtejCl5kLWC_JGFM*&+7T)>%KQv_b=p^x^td9UaN;^z=PI(ws$(W zPNH|{7xxZl(#iME;rm$JGrp8xddJ_HJl-=Ne9!nddS})~_eA=So^${4j(gnxlS+Mk zrI#~$=nYZae{yGDJX1&Ih50|cEctn5wcP9vM&&U5@JUd_!I?~4>0Yo%PvSKuyj!v6 z!Q@R*nK{3mFZKEu1zqUyZra8}Bxg%g^@ZLdxrkp5g!wd4b*a=9w{c Hr@8+POI7A6 literal 0 HcmV?d00001 diff --git a/macros/circle.sci b/macros/circle.sci new file mode 100644 index 0000000..918ea76 --- /dev/null +++ b/macros/circle.sci @@ -0,0 +1,69 @@ +// Copyright (C) 2015 - IIT Bombay - FOSSEE +// +// This file must be used under the terms of the CeCILL. +// This source file is licensed as described in the file COPYING, which +// you should have received as part of this distribution. The terms +// are also available at +// http://www.cecill.info/licences/Licence_CeCILL_V2-en.txt +// Author: Abhilasha Sancheti & Nihar Rao +// Organization: FOSSEE, IIT Bombay +// Email: toolbox@scilab.in +function [out]=circle(input_image , x_coordinate_of_centre , y_coordinate_centre , radius, r_value,g_value,b_value,varargin) +// This function circle draws a simple or filled circle on an image with a given center and radius. +// +// Calling Sequence +// cir=circle(inputImage,xcor,ycor,radius,r,g,b); +// cir=circle(inputImage,xcor,ycor,radius,r,g,b,thickness); +// cir=circle(inputImage,xcor,ycor,radius,r,g,b,thickness,linetype); +// cir=circle(inputImage,xcor,ycor,radius,r,g,b,thickness,linetype,shift); +// +// Parameters +// cir: The output image with the circle drawn in it. +// inputImage: The input image on which the circle should be drawn. +// xcor: X-coordinate of the center +// ycor: Y-coordinate of the center +// r: red color value of the circle.It should be in the range 0-255. +// b: blue color value of the circle.It should be in the range 0-255. +// g: green color value of the circle.It should be in the range 0-255. +// thickness: Line thickness. +// linetype: Type of the circle boundary.It can be 0 or 4 or 8. +// shift: Number of fractional bits in the point coordinates. +// +// Description +// This function circle draws a simple or filled circle on an image with a given center and radius. +// +// +// Examples +// +// //read the input image +// z=imread("lena.jpeg"); +// //call the function +// cir=circle(z,100,100,15,255,0,0,1,8,0); +// finally show the circle drawn +// imshow(cir) + + + input_image1=mattolist(input_image); + [lhs,rhs]=argn(0); + if lhs>1 + error(msprintf(" Too many output arguments")); + elseif rhs>10 + error(msprintf(" Too many input arguments,maximum number of arguments is 10\n")); + elseif rhs<7 + error(msprintf("the function needs atleast 11 arguments")); + end + if rhs==7 + a=raw_circle(input_image1 , x_coordinate_of_centre , y_coordinate_centre , radius, r_value,g_value,b_value); + elseif rhs==8 + a=raw_circle(input_image1 , x_coordinate_of_centre , y_coordinate_centre , radius, r_value,g_value,b_value,varargin(1)); + elseif rhs==9 + a=raw_circle(input_image1 , x_coordinate_of_centre , y_coordinate_centre , radius, r_value,g_value,b_value,varargin(1),varargin(2)); + elseif rhs==10 + a=raw_circle(input_image1 , x_coordinate_of_centre , y_coordinate_centre , radius, r_value,g_value,b_value,varargin(1),varargin(2),varargin(3)); + end + dimension=size(a); + for i = 1:dimension + out(:,:,i)=a(i); + end + +endfunction; diff --git a/macros/correctMatches.bin b/macros/correctMatches.bin new file mode 100644 index 0000000000000000000000000000000000000000..34d6e5c7c54ddb1c285b1e7fc1af59c728a16c7c GIT binary patch literal 7764 zcmdtn%WfS-5C&i;+=4Mq97t?)Y#4_C!HA0t*b<2VA;bf)V8NCJD|jMahZRqO2nqxV z5kRm(g!;_B%JUfR6AxVf~lym9H^^XS6D!pWl5 zTN+)OfaNqvw%%vS_tvsc5sv{#p?py{}7exkj?~@U3Hm9(gn?l7HkDYtCjXPmV3N zqe~A(ZoTG-p|y9W`1G=?M*nX?# z?CtjZ_PU~Lr7z~#O-v_>_gWF1VAs`rOkVHo6_MZR$9XuVUf27)_`{QLaD2YzH)=or z$8c+79Fq~(c2RJs>B0Pwnu}LXFjhIjqg<;S8M#W=Q|TyMMnF4 zr(g9&>jSp@;Hfcr{;l!(RvY$SElM6aA7gpLW?pRYVC&mHc7FIs?iXrKFSTpqOOIqs z4~jGOOTJ`+n|*v323PC$OpWEy=6t!gGbSrHc8B%&Cvr}1EpBRkH}ZbAx1$zQ&h0!5 za*xsv_Ha}iwbFCOr;ErW_A#vWS6iFo#5h)`yB#AxZH%=%I6vwHho9;k$XEUF^eh}& zY;vdP?EO;7(;dd!o^!T>ZS?5`YxbRYzH{H?tciu}@LYXUv9@vLp2)o+p2Y85v*(Pu zd&uNY5kni3yI36YXD{`47pJ$$h>Lt|CdW1(GGCSqKXkexydQc$>?ddXV!lvB28QX2tCEa-c`un!-)Vy9~_HNdAEo8qCvZ{*1)K6CP9 z#%$7cZgz|K+AAV^x#*>$EB!k5+j!{e=Ti4hUV3ky+!XxD@GD1gbVXzDEmP_-#m=xc zZQj8Y4^FA8G3(sBtzLRb-haXJSxA+LA&hl7q4RJ_sP04+zyIp?X zEP@H&FZSc@Vi;m5hAIAsdPD#6?uycb>A4{`>cpq_LN@HfH~lp1nXPME8U%btYLpW_O9@7zyD+T z-m1Aga^J~a?DBNqdbYrn{a1QQztKxw$il*2FrtIUHre!7?6OVf`-(&CksaFC?_c!K zL$=j}J#zWJDDK1{ez}WVP5GtoEck2}y-<`mx|+B7i39HZw6XBbHreDT4swq-eERME zr}y}Z9(gk9Gku#_@@$`HAFs6ym)DDeuUcBmFZP0QYA1%&Aw8SEPu}=^k!1%4xvRq? zi=R00@e)gXB#vilkBr=Nm#4Sc89OI>d#6aB!Cq`ecFeuI=>fg$HxlQ^zPi|VFQkTI zg_(XE_CV?voT9@{dYpcI%R&6vJ1Y0CCZc{ ztuKy?owMT}{H}be8~wy0w)C)j@wm3(H^ugL$+dUwhqZ?BZV@bD(iMpnzvc0>P5HV9Gbiud=sSM!hxdVAQ`6Yps(H?ThF-#P3iWh^J))UI?J=!+H9y$>oFbp(bX@DtKwU>O`@uQyq2c>FNOaK4? literal 0 HcmV?d00001 diff --git a/macros/correctMatches.sci b/macros/correctMatches.sci new file mode 100644 index 0000000..7dfc2da --- /dev/null +++ b/macros/correctMatches.sci @@ -0,0 +1,55 @@ +// Copyright (C) 2015 - IIT Bombay - FOSSEE +// +// This file must be used under the terms of the CeCILL. +// This source file is licensed as described in the file COPYING, which +// you should have received as part of this distribution. The terms +// are also available at +// http://www.cecill.info/licences/Licence_CeCILL_V2-en.txt +// Author: Nihar Rao +// Organization: FOSSEE, IIT Bombay +// Email: toolbox@scilab.in + +function [newPoints1, newPoints2] = correctMatches(F, points1, points2) +// This function Refines coordinates of corresponding points +// +// Calling Sequence +// [newPoints1, newPoints2] = correctMatches(F, points1, points2) +// +// Parameters +// F – 3x3 fundamental matrix. +// points1 – 2xN array containing the first set of points. +// points2 – 2xN array containing the second set of points. +// newPoints1 – The optimized points1. +// newPoints2 – The optimized points2. +// +// Description +// The function implements the Optimal Triangulation Method (see Multiple View Geometry for details). For each given point correspondence points1[i] <-> points2[i], and a fundamental matrix F, it computes the corrected correspondences newPoints1[i] <-> newPoints2[i] that minimize the geometric error d(points1[i], newPoints1[i])^2 + d(points2[i],newPoints2[i])^2 (where d(a,b) is the geometric distance between points a and b ) subject to the epipolar constraint newPoints2^T * F * newPoints1 = 0 . +// +// Examples +// //read first image +// I=imread("oscarSelfie.jpg",0); +// //increase stack size of scilab +// stacksize('max') +// // get points from first image +// cornerPoints1=detectMSERFeatures(I); +// //read second image +// I2=imread("oscarSelfie.jpg",0); +// //get points for 2nd image +// cornerPoints2=detectMSERFeatures(I2); +// fundamentalMat=estimateFundamentalMat(cornerPoints1.Location,cornerPoints2.Location); +// [new1 new2]=correctMatches(fundamentalMat,cornerPoints2.Location,cornerPoints1.Location); + [lhs rhs]=argn(0); + + if lhs>2 + error(msprintf(" Too many output arguments,maximum number of output arguments is 2")); + elseif rhs>3 + error(msprintf(" Too many input arguments,maximum number of arguments is 3`")); + elseif rhs<3 + error(msprintf("the function needs atleast 3 arguments")); + end + + [newPoints1, newPoints2]=raw_correctMatches(F, points1, points2); + + + +endfunction diff --git a/macros/cv_imread.sci~ b/macros/cv_imread.sci~ new file mode 100644 index 0000000..de70a07 --- /dev/null +++ b/macros/cv_imread.sci~ @@ -0,0 +1,11 @@ +function[dstMat] = imread(matA) + + out = opencv_imread(matA) + + channel = size(out) + + for i = 1: channel + dstMat(:,:,i) = out(i) + end + +endfunction diff --git a/macros/cvtColor.bin b/macros/cvtColor.bin new file mode 100644 index 0000000000000000000000000000000000000000..be515eb8a4cf22c663f5fd8c0ba3987cec97d971 GIT binary patch literal 12984 zcmeI3O>Y}j6oyUtHf~5=k{E0!E{Q~F140D}7DbJ^;ajR;!@BLSL2US4{S8nMR4gh% z1c4PIypJ=ldvZH7nTb8qCc@Iu+`0FBzUSOCi;2w8mheDnty?unaqbfSMnL|m_kEXNu?yd;7r>S3OBY`rdGoiQ;Q2e3wG z^o2Rw#b0FJ6*)H=&c^tN-hJf>K76#F*ue+Zf6+QRUlWlJ#;n_Jp6-d(k;OlF!3|kr z{7w4O99-2ryv!3fHt>m9-xS@I48Ga6Mk1y^*V%X)|*^`HEmCjW_*7^y#FM-8NLX=;|EIQD+{ zRrru+?*nQB+|bFDdGB}f^qmNt@@(&9YxqG8pbI2iJdlj6Fjj_WXJmdp%j|3-lS_WO%WDXhYCQjR8KJH8RjawOix?Z$zcQXFJ zRkyZ_zm5@`?x_=vsTb-1{fsT+e#SiO_`{X@Gkz)l+=GE-(M3$I8^?eT#u~rS7i*DT z4Cy($m4|dpPoW^!i%)km=#Ly;Y(Jq)p9Ln%Yv0W5qH!@toHl?)A zQtZJk*1&15vsg!8KDmj#$o0 z@1pneo#2lwu6w#V)|28FbK53<(QaFPtSWxHsu}Os^qTJ9n1j52)>Qq){aF?l_9JiH zFRbM~Gh;2?oCAxP<0kiFjIRzB(Z8l@Fk<;-4J>1xs4Mn4vGKg;%JaObXG65zRKHK_ z((ir#{=&Nq?{K{D6SLnNc}G4erZL}Tn0n8GGjpQU~pt(MyydsUjJ(1J4Eb7(S90Vtl6fX z$FWA{!7b*msr^(Hx9H1h=tB>(UepwBZPZa(yVSMgiZwQGAF|G-u!^-aZy)-kW*>5F zZS^7Ii+M_O*hbyN+L#Bgn75{C<2byc4{h|F&ui3I%q8_jt?`}etbL#4eK`KDEXEmY z?OF}&VqV+AF50ZxhpNV2=kL@Jzc%|)SuBscPkmUUc2fLeUhk?_n|QwjpE~$OpNeWN z?wxu24!`s98*5YX$6iMtrpNj31^hNx_Ip|UU9HY~;H&V}0Cx$9|-7w^3)YcIx&W`wf0EuT9lXQQxs2DSpu>*7Cmd$N0rEI}g><7@0rS zL)p{FGROYq`~l|y_`b;4f6L`80)2;%$N!(je0VMk?7);>32sl)S{mu_5bTk1o!W@T_2OSRa4?XN?-XC_)c*IGX|=XTl#-SK#^(jSd&B)jJM ziQmQsKd1V)9u?No3>)g}8xgh`b1jQc%Trmf37GD_qkHP|TDDHC;695p$B!6iQ63}D zushl6<(#Dl3+y;&_?BWZSWgi=1X8RsERM$X!tQmg5z}tQv&eXk*5uxG{4YAYUzBTP z$}k}wWAco~bup31^mA!)h{Fxtr8QiHYs}lIznS~L3Po|bhS}ev&7|2jU}v${L57~4HwR0RE-g(zvsx;!8SyK^_&EG- U%Tn3@mJk=%eI#;Txgy8)KXjLKZ~y=R literal 0 HcmV?d00001 diff --git a/macros/cvtColor.sci b/macros/cvtColor.sci new file mode 100644 index 0000000..6f235e2 --- /dev/null +++ b/macros/cvtColor.sci @@ -0,0 +1,84 @@ +// Copyright (C) 2015 - IIT Bombay - FOSSEE +// +// This file must be used under the terms of the CeCILL. +// This source file is licensed as described in the file COPYING, which +// you should have received as part of this distribution. The terms +// are also available at +// http://www.cecill.info/licences/Licence_CeCILL_V2-en.txt +// Author: Shubheksha Jalan & Nihar Rao +// Organization: FOSSEE, IIT Bombay +// Email: toolbox@scilab.in + +function new_image = cvtColor(image, code, varargin) +// This function is used to transform a image from one space to other like rgb to gray and vice versa. +// +// Calling Sequence +// +// inputImage=imread("lena.jpeg"); +// outputImage=cvtColor(inputImage,codeString); +// outputImage=cvtColor(inputImage,codeString,dstCn); +// +// +// Parameters +// dstCn: number of channels in the destination image; if the parameter is 0, the number of the channels is derived automatically from src and code +// codeString: A string which specifies the type of conversion.The different types are listed below. +// "CV_BGR2GRAY": Conversion is from BGR(blue-green-red) space to GRAY. +// "CV_RGB2GRAY": Conversion is from RGB(red-green-blue) space to GRAY. +// "CV_GRAY2BGR": Conversion is from BGR(blue-green-red) space. +// "CV_GRAY2RGB": Conversion is from to GRAY to RGB(blue-green-red) space. +// "CV_BGR2XYZ" : Conversion is from BGR(blue-green-red) space to CIE XYZ. +// "CV_RGB2XYZ" : Conversion is from RGB(red-green-blue) space to CIE XYZ. +// "CV_XYZ2BGR" : Conversion is from to CIE XYZ to BGR space. +// "CV_XYZ2RGB" : Conversion is from to CIE XYZ to RGB(red-green-blue) space. +// "CV_BGR2YCrCb": Conversion is from BGR(blue-green-red) space to luma-chroma. +// "CV_RGB2YCrCb" :Conversion is from RGB(red-green-blue) space to luma chroma. +// "CV_YCrCb2BGR" :Conversion is from luma-chroma to BGR(blue-green-red) space. +// "CV_YCrCb2RGB" :Conversion is from luma-chroma to RGB(red-green-blue) space. +// "CV_BGR2HSV": Conversion is from BGR(blue-green-red) space to HSV. +// "CV_RGB2HSV": Conversion is from RGB space to HSV. +// "CV_HSV2BGR": Conversion is from to HSV to BGR(blue-green-red) space. +// "CV_HSV2RGB": Conversion is from to HSV to RGB(red-green-blue) space. +// "CV_BGR2HLS": Conversion is from BGR(blue-green-red) space to HLS. +// "CV_RGB2HLS": Conversion is from RGB space to HSV. +// "CV_HLS2BGR": Conversion is from HLS to BGR(blue-green-red) space. +// "CV_HLS2RGB": Conversion is from HLS to RGB(red-green-blue) space. +// "CV_BGR2Lab": Conversion is from BGR(blue-green-red) space to CIE Lab. +// "CV_RGB2Lab": Conversion is from RGB space to CIE Lab. +// "CV_Lab2BGR": Conversion is from CIE Lab to BGR(blue-green-red) space. +// "CV_Lab2RGB": Conversion is from CIE Lab to RGB space. +// "CV_BGR2Luv": Conversion is from BGR(blue-green-red) space to CIE Luv. +// "CV_RGB2Luv": Conversion is from RGB space to CIE Luv. +// "CV_Luv2BGR": Conversion is from CIE Luv to BGR(blue-green-red) space. +// "CV_Luv2RGB": Conversion is from CIE Luv to RGB space. +// +// Description +// +// This function is used to transform a image from one space to other like rgb to gray and vice versa. +// +// Examples +// +// z=imread("lena.jpeg",0); +// ss=cvtColor(z,"CV_GRAY2BGR"); +// imshow(ss) + + + + [ lhs, rhs ] = argn(0) + + image_list = mattolist(image) + + select rhs + case 2 then + + out = raw_cvtColor(image_list, code) + + case 3 then + out = raw_cvtColor(image_list, code, varargin(1)) + end + + sz=size(out); + for i=1:sz + new_image(:, :, i) = out(i) + end + +endfunction diff --git a/macros/deconvlucy.bin b/macros/deconvlucy.bin new file mode 100644 index 0000000000000000000000000000000000000000..28860427cf39b4e10c3161465fcc53a616cc66d2 GIT binary patch literal 5636 zcmdtm%Z^l46b9e|Z&=U;lEMPu^SC>|i_}&(BR~wXX5Qr$(c*v3C%<6}l4o;?A8r=QB=2yURT? 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The terms +// are also available at +// http://www.cecill.info/licences/Licence_CeCILL_V2-en.txt +// Author: Nihar Rao +// Organization: FOSSEE, IIT Bombay +// Email: toolbox@scilab.in +function [varargout] = detectGFTTFeatures(image, varargin) +// This function is used to detect GFTT Features in a grayscale Image. +// +// Calling Sequence +// result = detectGFTTFeatures(Image); +// result = detectGFTTFeatures(Image,Name,Value,....) +// +// Parameters +// result: a struct containing features and keypoints +// Image: a grayscale image whose GFTT features is to be found +// blocksize: the blocksize to be used for detecting the keypoints +// minDistance: the minimum distance between the points for feature computation +// useHarrisDetector: an option to use the HarrisDetector.default value is false. +// maxCorners: the maximum number of corners that should be used for feature computation. +// ROI or Mask : (Optional) Region Of Interest. This is taken as a vector [u v width height]. When specified, the function detects the key points within region of area width*height with u and v being the top left corner coordinates. +// Description +// This function is used to detect GFTT Features in a grayscale Image. +// Examples +// +// //read image in grayscale +// z=imread("people.jpg",0); +// image=imread("pls.jpg",0); +// stacksize('max') +// //call the function to detect features for image- z +// pls=detectGFTTFeatures(z,"minDistance",4); +// // call the function to detect features for image- image +// pls1=detectGFTTFeatures(image); +// //match features using the features detected using the above function +// [op ir]=matchFeatures(pls.Features,pls1.Features); +// //finally draw those matches +// final=drawMatch(z,image,pls.KeyPoints,pls1.KeyPoints,op,ir); +// imshow(final) + + + + image_list = mattolist(image); + [ lhs, rhs ] = argn(0) + if rhs > 15 then + error(msprintf("Too many input arguments")) + end + if lhs > 1 then + error(msprintf("Too many output arguments")) + end + + select rhs + case 1 then + [a b c d e]= raw_detectGFTTFeatures(image_list) + case 3 then + [a b c d e]= raw_detectGFTTFeatures(image_list, varargin(1), varargin(2)) + case 5 then + [a b c d e]= raw_detectGFTTFeatures(image_list, varargin(1), varargin(2), varargin(3), varargin(4)) + case 7 then + [a b c d e]= raw_detectGFTTFeatures(image_list, varargin(1), varargin(2), varargin(3), varargin(4), varargin(5), varargin(6)) + case 9 then + [a b c d e]= raw_detectGFTTFeatures(image_list, varargin(1), varargin(2), varargin(3), varargin(4), varargin(5), varargin(6), varargin(7), varargin(8)) + case 11 then + [a b c d e]= raw_detectGFTTFeatures(image_list, varargin(1), varargin(2), varargin(3), varargin(4), varargin(5), varargin(6), varargin(7), varargin(8),varargin(9),varargin(10)) + case 13 then + [a b c d e]= raw_detectGFTTFeatures(image_list, varargin(1), varargin(2), varargin(3), varargin(4), varargin(5), varargin(6), varargin(7), varargin(8),varargin(9),varargin(10),varargin(11),varargin(12)); + case 15 then + [a b c d e]= raw_detectGFTTFeatures(image_list, varargin(1), varargin(2), varargin(3), varargin(4), varargin(5), varargin(6), varargin(7), varargin(8),varargin(9),varargin(10),varargin(11),varargin(12),varargin(13),varargin(14)); + + end +varargout(1) = struct("Type","binaryFeatures",'Features',a,'NumBits',b,'NumFeatures',c,'KeyPoints',d,'keypointsCount',e); +endfunction diff --git a/macros/detectKAZEFeatures.bin b/macros/detectKAZEFeatures.bin new file mode 100644 index 0000000000000000000000000000000000000000..a837f081a188f41298054f58819acdf56ecfcd62 GIT binary patch literal 14516 zcmeI(+m0Mp6$ao=I5{29#2$Q@&@-kPEXz#nNo26YIgL16@EUmqUV$s#0xr1cEfCKT z3B;L1$N|CyLYVc9>mTnfS0AR~!V~pKE46Fyb^O;_yQ*u)JG+Owmk&Sq=)Dgg?~D&` zO?D6Np8oBOMx&RCK0ls}Cs+1w9X_2t`|r!Ows&KEW%q36+2EN))n8lhz$LcB6IPP{rG~9+?67H?vIM_vgQ7I5qW%nE&Vs@YMzYw zFBb)y8lH_|L*^eP6FqdrK6&fE>wNxPjrmJw@H39?J2l21YU3hDx0tOz=&ptnYH zw=b2xq1caW{*9ve_^`A4BKi20^6AfA4&)A|=6=)UCAgcH&z8iP_+G8C*#6kbre>ly zb!uJ>MK1YRlr!sUgl=;5;N@3a^Tz2VJY-T&xu&kz7AqdSbhY-`vZmJ3d)I1AMi0DR z#8&ju(Z=+Rx~F5PF4}n3?Jaity+!}DNH6h)eg2v6*RZ*DVrGXP{9?*pBe&5_k9n8{ zpXBoUHAfcj7mDaG4xceRPm0ppc>4AtBL{4^`;4{dmNPu51OD@kJvxo~wvJDD^s?uJ z=fI^RezGs;iRHM)c(Z@Ni+#SZuQr06xpoiyVcnC39lpq@19>F(zhFaeTL*3Y%WR$} zp411d;N0RZ9{1vq7uPl?VslT<^Ab-mFg8!-xF|JszsCH_GZnuY;74j-eWb41_4Fyd zEiP=3ZF&2;*u*CuWB$oAVn2Dd7CVWJT>O7jV?6d*Inc-NcYCC|qKhB=gU{b<%^Z0) z$+XWeu|!Y$k~|x2zUjl)_7BYIrq6nOj}Pw6i;?ZN?=o(6B*vcYY! z4{dG3&%OBC{m?#c-a7s22_+tL;&x?Azo?s&qW&}PVa=ts&ZCc9>i7>e=Fjh|9@UNK zxBE8Ff2ldRu;rb=`gv zVquG{al4jve#9o<=)e!xcF(BWvwm&IiG%L!w`BRiCf!5N82*Yq@2=#BdI=xwmemy- zse|lcVu)|Sj16vxf9SW$BHUjoelor- z*u&}a9D;9jvJ-4;csBN1p6pv4@eK}i1SfIOXO92Y$+YpU6IblV<`+xHgH8|qecPVZ zzp9wT!Di|^F~Q@rMb_EJYajA=T=Yg!Y|7oB`VVq_=#kbAPLdS%^Speyx3hTh~&Jh7L3WD({k9k19E z+x>1XbxWVzEb7gEU#{v&__7B>wL&la*$+m^N&h`3we@oG%KuA6{TlmP&51X;F}~>e zflumDkI8-VHLbB2+kC<0|DCfTANtt;pz|fz$7eMv2kAq;ud3fXE7R=aEWTMp4hGJ~=t&OJBk+K@#582>V$stYFUktOVI{3>?aR0dFV6Qe2_`F#JAEd7SRY2+oWA(7A2gs@EHW%Ni zd%7PKS)bc;2KIz@&zX#;w|554vxoKoIalwl>Tl>ATPfGlXlJ0NvvzsO+N(>}#!J?o z$K}$Dk8rWqp9h!uz4Gxp^0MfBeh4RhI0j_F1^R`ty*g>?GH z`{c#yn>(}jRZ5ZHb=$rv5Vn2Odyn3%Z{~aNXrtbn*KvCz9jp4+x6t&j?`RjRe~)K7 z^}|R1e!FPfzXig!e?M0JJHH3q*=P@#*Kv0v9jo>c-{-TB_)gjGBfb^C*xzkVW^Z-- z$gF(b?jr@lb|2a9BUJ^y^XdKPzb|gKkIe5y#~bZM^E&Qrq+`{7W)H}I=KbPD-_Q7) zzaMqq{l8li*~{8*_wdX2TW2Ikb?@xMzHQ#sdtuI|au$Ve)p;~|-%nQY!GF=W^_&&Z z<-1J#|CxVO{_?9m16%a{zSSe1R?j;AEjlx3_4@t0&N;An7oAVE`e1*p$TfL!MwMJ7 zZvW0KXID8BWMk2DHa74a98PXs?jQKpIfrwF{04x%XS%*;)75i)(Z4gauGY}I-SxjY CXs{Xp literal 0 HcmV?d00001 diff --git a/macros/detectKAZEFeatures.sci b/macros/detectKAZEFeatures.sci new file mode 100644 index 0000000..37f6170 --- /dev/null +++ b/macros/detectKAZEFeatures.sci @@ -0,0 +1,79 @@ +// Copyright (C) 2015 - IIT Bombay - FOSSEE +// +// This file must be used under the terms of the CeCILL. +// This source file is licensed as described in the file COPYING, which +// you should have received as part of this distribution. The terms +// are also available at +// http://www.cecill.info/licences/Licence_CeCILL_V2-en.txt +// Author: Nihar Rao +// Organization: FOSSEE, IIT Bombay +// Email: toolbox@scilab.in +function [varargout] = detectKAZEFeatures(image, varargin) +// This function is used to detect KAZE Features in a grayscale Image. +// +// Calling Sequence +// result = detectKAZEFeatures(Image); +// result = detectKAZEFeatures(Image,Name,Value,....) +// Parameters +// result=a struct containing features and keypoints +// Image=a grayscale image whose KAZE features is to be found +// extended-Set to enable extraction of extended (128-byte) descriptor. +// upright-Set to enable use of upright descriptors (non rotation-invariant) +// Threshold-response threshold to accept point +// NumLayers-Default number of sublevels per scale level +// NumOctaves : (Optional)The number of Octaves that the detector uses. (Default - 4) The value must be an integer scalar in between 1 and 4. +// diffusivity:-KAZE's diffusivity' +// ROI or Mask : (Optional) Region Of Interest. This is taken as a vector [u v width height]. When specified, the function detects the key points within region of area width*height with u and v being the top left corner coordinates. +// +// +// Description +// This function is used to detect KAZE Features in a grayscale Image. +// +// Examples +// +// //read image in grayscale +// z=imread("people.jpg",0); +// image=imread("pls.jpg",0); +// stacksize('max') +// //call the function to detect features for image- z +// pls=detectKAZEFeatures(z,"diffusivity",2.1); +// // call the function to detect features for image- image +// pls1=detectKAZEFeatures(image); +// //match features using the features detected using the above function +// [op ir]=matchFeatures(pls.Features,pls1.Features); +// //finally draw those matches +// final=drawMatch(z,image,pls.KeyPoints,pls1.KeyPoints,op,ir); +// imshow(final) + + + + image_list = mattolist(image); + [ lhs, rhs ] = argn(0) + if rhs > 15 then + error(msprintf("Too many input arguments")) + end + if lhs > 1 then + error(msprintf("Too many output arguments")) + end + + select rhs + case 1 then + [a b c d e]= raw_detectKAZEFeatures(image_list) + case 3 then + [a b c d e]= raw_detectKAZEFeatures(image_list, varargin(1), varargin(2)) + case 5 then + [a b c d e]= raw_detectKAZEFeatures(image_list, varargin(1), varargin(2), varargin(3), varargin(4)) + case 7 then + [a b c d e]= raw_detectKAZEFeatures(image_list, varargin(1), varargin(2), varargin(3), varargin(4), varargin(5), varargin(6)) + case 9 then + [a b c d e]= raw_detectKAZEFeatures(image_list, varargin(1), varargin(2), varargin(3), varargin(4), varargin(5), varargin(6), varargin(7), varargin(8)) + case 11 then + [a b c d e]= raw_detectKAZEFeatures(image_list, varargin(1), varargin(2), varargin(3), varargin(4), varargin(5), varargin(6), varargin(7), varargin(8),varargin(9),varargin(10)) + case 13 then + [a b c d e]= raw_detectKAZEFeatures(image_list, varargin(1), varargin(2), varargin(3), varargin(4), varargin(5), varargin(6), varargin(7), varargin(8),varargin(9),varargin(10),varargin(11),varargin(12)); + case 15 then + [a b c d e]= raw_detectKAZEFeatures(image_list, varargin(1), varargin(2), varargin(3), varargin(4), varargin(5), varargin(6), varargin(7), varargin(8),varargin(9),varargin(10),varargin(11),varargin(12),varargin(13),varargin(14)); + + end +varargout(1) = struct("Type","binaryFeatures",'Features',a,'NumBits',b,'NumFeatures',c,'KeyPoints',d,'keypointsCount',e); +endfunction diff --git a/macros/detectMSERFeatures.bin b/macros/detectMSERFeatures.bin new file mode 100644 index 0000000000000000000000000000000000000000..a5698055a6b6b2995338ef3f3c7a804ff1a24b90 GIT binary patch literal 12708 zcmeI(&2C*+6$kJezM9@Tu4Cf(hU@FvNf9L!s|u71K-3Hv0wabDP$#@WhYV1~1Mmh+ zcn979cnP3IKr2~u* z_tA~%Vt>B5_sa5jV=|dsE1GX^ZO?YQ$&Xmee?L>a?c39>&1Npcm!|XSd~16*=Q;jh zV={TM^j<1DDte{poyU(K->lM>#-q;+T zImg(?sRj9b)-us7(S>m-Lc&JdHfa?3 zJcH%mYEJ#h$}KjBY&;HqxWdDHyDolI=c(ZbrQ7eB zS35o)EcLNkrA|XS=`((;wbWN{WX+3LJba7O(LQxl^w09;T;C>-yESGn{lFG|y-7BE zQ*5piFa3+gDjq(>EQYLwU)PwOHkQb?wu6Bj*>MibU|Xljg@)`r=nLCWqA9eq%pz&epTse}*v6 zegQWzrM~KtwUz$NS|CfVl^^PdwvUYCpDr8ht7q0n>f@fv9J$n#Y%p_FW5>jQP-C|A zPI?wUy^AMC=dpFso@i^Y-t6Y6KiSUuaX&bAowje>FQUJW9$)m@zWQxvhb{N4@PtXf z@6*e$6z34`Y&^?eY~vM^8fU*2OFsv57tJHrIyF8hvY#M5%#Jaf@QvYu2N!!38FP63 zp3Ytr49VtNLPsykhdsLZ>BZP&Ll5e2{`70?+B4Gkbn(Q|#tN(WNF2_yhUgiyWz05x zvX{LEvlE}ja$zrdim~t4I`DIUs(&9AWqq%@#= z-5u3YAIRMp#^EIoamdX&!E5ocPh_4AbtSVdKCMl)RfyN$QdO=?*<#rv^hjI;--6NA|_+YvSqaWev!YoIGJd zZY=)vX@8GV3mDMHOP)WgF?+~5(gS4JNsi|6KdwHr*U9ONMR1Z!e5+q_X!pc1xzs89 zHH=`J9KYa)G6!;`U^(95-#oH=&r^WVoVcHSx; 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+ end + imageList=mattolist(image); + select rhs-1 + case 0 then + [pixelIdxList count location axes orientation]=raw_detectMSERFeatures(imageList); + case 2 then + [pixelIdxList count location axes orientation]=raw_detectMSERFeatures(imageList,varargin(1),varargin(2)); + case 4 then + [pixelIdxList count location axes orientation]=raw_detectMSERFeatures(imageList,varargin(1),varargin(2),varargin(3),varargin(4)); + case 6 then + [pixelIdxList count location axes orientation]=raw_detectMSERFeatures(imageList,varargin(1),varargin(2),varargin(3),varargin(4),varargin(5),varargin(6)); + case 8 then + [pixelIdxList count location axes orientation]=raw_detectMSERFeatures(imageList,varargin(1),varargin(2),varargin(3),varargin(4),varargin(5),varargin(6),varargin(7),varargin(8)); + end + //for i=1:size(pixelIdxList) + // regions(i)=struct('Count',1,'Location',location(i,:),'Axes',axes(i,:),'Orientation',orientation(i,:),'PixelIdxList',pixelIdxList(i)); + //end + regions=struct('Type','MSERObject','Count',count,'Location',location,'Axes',axes,'Orientation',orientation,'PixelIdxList',pixelIdxList), +endfunction diff --git a/macros/detectMinEigenFeatures.bin b/macros/detectMinEigenFeatures.bin new file mode 100644 index 0000000000000000000000000000000000000000..9bc5a3a1625ec0a0cc7b2f2efc7c1ecd1c7261be GIT binary patch literal 7520 zcmeI%&2C#&5C?Gc-I~NrLKC|k`)`?fS2F}cpbzO@CJyF zLMuUA5GzEPUvmG>jdSgMENDSk8r|bFGygO5pE>8=YcCHbgQdy6)#0PnmBH}ga(}Wl z9&GOHEcbf7XG)ev`nrsbo?@KPoZDuWiqk@1R87^nBPG!(-1kdbsrC zW}dGx`%5Ks@qv}tGRLl8(vD}NnOmtVJT{3fest#VRoM4 z!anO{j(zfiD|Y%Cf%wZ(-?^TEDaV|a^ryxG{O z2VZfzrrvFSy101Q#3FCL;!!^sYV~HxFJ*JBu5Xnjws&j%w8ZvK6U)yH?`kCe%y-o~ zI<<_<=2)s}zAx8UzIU57aD=n072eI`Ej+zm<3&7OZ}fTs27fh3{o3__qbFe-vq_KY zA35`1v|i#;S9WTf7>wcQH|vUrP4<<1vyaTvTix)^Q@w3h>c5;TV#`NrQPH-Je{#(Tk9}h6aBUhL=N?`ivVITJz`GmLkYs?1UVu>$I_0V_b^{KhD@FvFa1p~Ko zFc+?8bAM1i$%k$1&GBCpGu?6AB##%$w#~pQ(#u`zEB9y@dGHRT_C&l&XQU>U=TU--lc8+l}Zv$IYxe2+a_x?me82Kk7U zy;#{Achvy*T|Icd@$npj6FBOJZ|72Sj<2)S8tUnKv-zGilP?_H*uS?*#N34~u2)K| zha0xnO4`pgPxCWZg}TQpehAK9EXl{aM7=N^d0+6_@K0H9-<7(> zZ*O<6Pe#jI>!YJZS9AL8KRvA02mQaVbH=fw`?y4%^~G#`oOOAhqtAJ+mg@FLt+%MJ z+04E#nX^}dp{}rV59oT2;$zRSWk=Ev>CvZc?^K9;pRX!VG5Q@P{NjGz?=h+QUY+}s z$!L9Tb23xvlkDw1{QIj%d<7*AXVTZz0MFM|U9C5-4@dM`^ddStewlvxr&T@vrQuQ_llkwWp455u~eYDh{ ztc{M`+xT_lx0}7=etw$#?E3?r9^Ap zc0aGR_0bz8|3;n<*XrEf8GhPY9mZHW6UK4%R_oMTe?FOdk9NPTwbk2({lDHtLho$# zKHM`G&(t%AF-B*?IIi#NuZC&govZOb)pwZnS--g7Z{E}Nn|rl;qW8T#b9nCbJe2oX z&+(o|-FM78ll|W73WwyK4~KGchI-cBt}8t60Onx^*K-kEI%B^DdtS=(PM($c;p%>) z=kK0Q&z27y+|RqO<$epxe)qelbzxW=4qO=X?wf54XNUhK@-7s9_|Lm1$DhsSWW2T1 zapQImlxxnW^EJk^I9>Pe`Q870m3mrJ`Ka&g^XJW)gLAzkbvUlR>66dOXQz?)p0tMg zMofA|44!Mlz4hVw&hA#pZ10%UbFQadyX|{i55;!9*1?^%x_T}7i0OKXyb|BM-U@c! iiIYEGtg{HStJi{;eV9FHPwR92tuO6uH6))l*S`T^^WvZY literal 0 HcmV?d00001 diff --git a/macros/detectMinEigenFeatures.sci b/macros/detectMinEigenFeatures.sci new file mode 100644 index 0000000..5a6ad2a --- /dev/null +++ b/macros/detectMinEigenFeatures.sci @@ -0,0 +1,59 @@ +// Copyright (C) 2015 - IIT Bombay - FOSSEE +// +// This file must be used under the terms of the CeCILL. +// This source file is licensed as described in the file COPYING, which +// you should have received as part of this distribution. The terms +// are also available at +// http://www.cecill.info/licences/Licence_CeCILL_V2-en.txt +// Author: Rohit Suri & Sridhar Reddy +// Organization: FOSSEE, IIT Bombay +// Email: toolbox@scilab.in + +function [cornerPoints]=detectMinEigenFeatures(image,varargin) +// This function is used to find corner points in an image using Minimum Eigen Value algorithm. +// +// Calling Sequence +// points = detectMinEigenFeatures(I); +// points = detectMinEigenFeatures(I, Name, Value, ...); +// +// Parameters +// points: Structure of corner points +// I: Input image to detectHarrisFeatures() +// MinQuality: (Optional) Minimum accepted quality of corners (Default- 0.01) +// FilterSize: (Optional) Dimension of Gaussian Filter (Default: 5) +// ROI: (Optional) Rectangular region for corner detection +// +// Description +// This function detects corners in an image I. These corner points are used to extract features and hence recognize the contents of an image. +// +// Examples +// I = imread('sample.jpg'); +// points = detectMinEigenFeatures(I); +// + + + [lhs rhs]=argn(0); + if lhs>1 + error(msprintf(" Too many output arguments")); + elseif rhs>7 + error(msprintf(" Too many input arguments")); + elseif modulo(rhs,2)==0 + error(msprintf("Either Argument Name or its Value missing")); + end + imageList=mattolist(image); + select rhs-1 + case 0 then + [location metric count]=raw_detectMinEigenFeaturess(imageList); + case 2 then + [location metric count]=raw_detectMinEigenFeatures(imageList,varargin(1),varargin(2)); + case 4 then + [location metric count]=raw_detectMinEigenFeatures(imageList,varargin(1),varargin(2),varargin(3),varargin(4)); + case 6 then + [location metric count]=raw_detectMinEigenFeatures(imageList,varargin(1),varargin(2),varargin(3),varargin(4),varargin(5),varargin(6)); + end + //disp(count(1,1)); + cornerPoints=struct('Type','cornerPoints','Location',location,'Metric',metric,'Count',count); + //for i=1:count(1,1) + // cornerPoints(i)=struct('Type','cornerPoints','Location',location(i,:),'Metric',metric(i,:),'Count',1); + //end +endfunction diff --git a/macros/ellipse.bin b/macros/ellipse.bin new file mode 100644 index 0000000000000000000000000000000000000000..bdf3b7cc9fb4be7acea2f21c3c437c411de113a4 GIT binary patch literal 12008 zcmeI&&2Ai76$kJRpP>_XJk8kMp}P|&V}Z$p83Zuz>|g2qB>npsWCMex3Rc*X1f>k1!}RZt19QoqIn2=iFPjyKA<$H^04}9rZsu zlgZ>-(elowKefHTS#$Hn?K_*p`TlhGr2f6bo6F^DXTF$jW{1mLhc{=7&8kH1xBM{6 z+O7F&y*ZrTo3Bs0TF-7S7dxjXriW82O9!#TM&ckxmoIj5-`bS} zz1V2uOAbRm$R*BYxY>nd+pAR_xx%{e)*u=u_mx}Hc$v3&;-5=luU-K7w@Vr|NpwEpEa7jMa|UHUSXec->=6uRU*oAMlMpK0dwWB<8^ zf6&ck&%w($c3sY>+aUaWi}eZy{W&|Bh#4p8i=U@%-k09FKJ-5An%2Yeww-vr}U1=RBm#Cfwx9u6p8~g&o|+ z)#K9&Vn6nFWbvtj|WBQjFd+>&hc%2R9ERW>%m+FBr9K@zZ@>K_RTwxpx5`W)5 zetOy%R{V;AO=AR?7VpP(PaZ!$$s5DE??miZS=`dy%}~ z=xo8H?X9tV*;c#A#^;NW>$kdGVV3$C%Uz$y4VLPnH(kx+`<|~4@$=mh|DrX_denQK zS8B=*zUK&g?DLbD+Gj!VrbCyG_}z=OU31|Vd-7V*hl)PhQQQ09E*^b;f{SrK*AF5# z-|4W?-@&H8mskt%`yk?z^^soGpKy4&2rhb1Z=>M%r|SFkaeDMT`fbmCv+TiKkG8hh zX}>qcr*m)1r~6*lZq`cHYW6~F4<7vV*EdYEHlv^1YigSdd%^P~1H9|SYcY7-$z<<< zgL4WDlJ_4gZ~KWeZT6A)X!ECsFGjJl!5$g;;lnzynB-|kD!*z82cJUM>w z5#RQ^$nZxl{nO@M?03(aY_Rp$$}_Tf?6Ji+JI2XHuJ&`EjGxw+oqRtcpWMj65Dr7w z&=Y&`JE(DV8TpIopb%a?V8PnJ&lz0E5a@Fj-aw|3>gW^A%8EMEWUpJY^DZT)1NOM5|e!Rr<>C*p4LqfhRYqDMu^p^t;#qJLGm z@*_5OvY`ru{kK7JW$({skJ^j=;r%arEV~7dvB=z?6*Bh zm%X+x(o3=1j{$alY~`aSA+?3a*nfL}uRf{it<3&(vsv!V*ZqG8|5-9HQ;QFGvhKy} zs<#^Z*V_NhYHAycI6mg4`-rLjWIOdA8{Hv)uZ}n2|&&AGZO-=UBn1jppqFkcZ=A`I?I~k!+%ri?Kz|7$bEiuvX1X}JagI4vaiUS zyuPw0@I!{a`qL+)Kg6@YzP*|+Hn-Y3jNvMFIg;^3u57mWexvTsi?6i=ulItjy(BfeSL3Y9)Itnw=l({G)kn?Dsjb-0 zTT60$sH-vD?So$^;^+NQ>rZcM{kY3Vj^8WNGp`r*YyFwx>2=Rt*usSj%wdvq3f$n0 zN5+*rvabeHYl=PnWX`=gykIUS;}>=PRp{H#uWKWMtNwx6^`fW$I6l@>J{Mo7&ujOn zboC;fe%jf=OYO{!Js;ZV&)9n=t<2avC#}rb`zNi;*t;mL%-DM=t<2avDy_`e`zo!> z*t;vO%-DM@t<2avEv?LIdT=-!cu&Y)Z_mne-da*qYr)mCZ94Fbz^bWjy)WKFN89z^ z_R!DD7CZLas~+l}&m-?Vov7=``%JCOf1`&^p5@+o)A}BJXKL*HKeyr@vOjPDl>c@z`0VeIBmoubh5i_#EGR-!A(* z^ZnUkJzw^J#HgulEFZ6{_}bqM#C4WlO>ePzSXZ*J`D)R8hB#H~ts(n(}A> literal 0 HcmV?d00001 diff --git a/macros/ellipse.sci b/macros/ellipse.sci new file mode 100644 index 0000000..3dece5c --- /dev/null +++ b/macros/ellipse.sci @@ -0,0 +1,76 @@ +// Copyright (C) 2015 - IIT Bombay - FOSSEE +// +// This file must be used under the terms of the CeCILL. +// This source file is licensed as described in the file COPYING, which +// you should have received as part of this distribution. The terms +// are also available at +// http://www.cecill.info/licences/Licence_CeCILL_V2-en.txt +// Author: Sukul Bagai +// Organization: FOSSEE, IIT Bombay +// Email: toolbox@scilab.in +function [out]=ellipse(input_image , x_coordinate_of_centre , y_coordinate_centre , first_axis, second_axis, angle, startAngle, endAngle, r_value,g_value,b_value,varargin) +// This function draws a simple or thick elliptic arc or fills an ellipse sector. +// +// +// Calling Sequence +// elli=ellipse(inputImage,xcor,ycor,firstAxis,secondAxis,angle,startAngle,endAngle,r,g,b); +// elli=ellipse(inputImage,xcor,ycor,firstAxis,secondAxis,angle,startAngle,endAngle,r,g,b,thickness); +// elli=ellipse(inputImage,xcor,ycor,firstAxis,secondAxis,angle,startAngle,endAngle,r,g,b,thickness,linetype); +// elli=ellipse(inputImage,xcor,ycor,firstAxis,secondAxis,angle,startAngle,endAngle,r,g,b,thickness,linetype,shift); +// +// Parameters +// elli: The output image with the ellipse drawn in it. +// inputImage: The input image on which the ellipse should be drawn. +// xcor: X-coordinate of the center +// ycor: Y-coordinate of the center +// firstAxis: the first axis of the ellipse. +// secondAxis: the second axis of the ellipse. +// angle: Ellipse rotation angle in degrees. +// startAngle: Starting angle of the elliptic arc in degrees. +// endAngle: Ending angle of the elliptic arc in degrees. +// r: red color value of the ellipse.It should be in the range 0-255. +// b: blue color value of the ellipse.It should be in the range 0-255. +// g: green color value of the ellipse.It should be in the range 0-255. +// thickness: Line thickness. +// linetype: Type of the ellipse boundary.It can be 0 or 4 or 8. +// shift: Number of fractional bits in the point coordinates. +// +// Description +// +// This function draws a simple or thick elliptic arc or fills an ellipse sector. +// +// Examples +// // read the input image on which the ellipse shpuld be drawn. +// z=imread("lena.jpeg",0); +// call the function +// elli=ellipse(z,0,0,45,45,45,0,45,255,0,0,1,0); +// // show the image drawn on it. +// imshow(elli) + + + input_image1=mattolist(input_image); + [lhs,rhs]=argn(0); + if lhs>1 + error(msprintf(" Too many output arguments")); + elseif rhs>14 + error(msprintf(" Too many input arguments,maximum number of arguments is 14\n")); + elseif rhs<11 + error(msprintf("the function needs atleast 11 arguments")); + end + if rhs==11 + a=raw_ellipse(input_image1 , x_coordinate_of_centre , y_coordinate_centre , first_axis, second_axis, angle, startAngle, endAngle, r_value,g_value,b_value); + elseif rhs==12 + a=raw_ellipse(input_image1 , x_coordinate_of_centre , y_coordinate_centre , first_axis, second_axis, angle, startAngle, endAngle, r_value,g_value,b_value,varargin(1)); + elseif rhs==13 + a=raw_ellipse(input_image1 , x_coordinate_of_centre , y_coordinate_centre , first_axis, second_axis, angle, startAngle, endAngle, r_value,g_value,b_value,varargin(1),varargin(2)); + elseif rhs==14 + a=raw_ellipse(input_image1 , x_coordinate_of_centre , y_coordinate_centre , first_axis, second_axis, angle, startAngle, endAngle, r_value,g_value,b_value,varargin(1),varargin(2),varargin(3)); + end + + + dimension=size(a) + for i = 1:dimension + out(:,:,i)=a(i); + end + +endfunction; diff --git a/macros/erode.bin b/macros/erode.bin new file mode 100644 index 0000000000000000000000000000000000000000..39385e79016b109b59cfbbcdf8237b2b174c9868 GIT binary patch literal 3788 zcmeH~%We}v5JhdmLk#hd4Dln_V@wh$A%KJe0vTF@$!J=y8l|}JQaZf=jpXNRffQh&Oluj+DK)YWJ>S&sO$(dpb*{YR4bk|W8N`Fy^uwUSI49X?aZ zP_ikhCD=z2bi|!2ZrteTxs*7*(B6K;4J7EcB=`}3PqNqSsYNWl#NmezF|62jCB%XU zKQOZLY#(rfiG0S*9$lK7Tzv^E_*kh;j+YYir0rr4Pt^LQ-oZvZlIH#@JNX_;sPEih zV&9hAeC^AAA|WTZz)lSH;Q5K*xQ08< z0vp)roxM4rZ=V%woLhQHeT^3zb)1hpKHGTCX?(1Ot*t+E_FQ&+ax-Bp^b8)(0u1oM zGkbLA*53p$d-i>9%$55kj-2>`7YtzXyrn(iOAXJE@jsRhU*;n>x9-8dU?-1jQQ!E< z1IEZXwW#r1^Vn7+o~LW%@bI1(kH4$ei3e=!up0~W1Rv%Z4kF*=z-}(E$JxyFOWaIC zF2|T_Y}T3Yb#oJWexX?6`NolhIDaR2j@aqReR6)x9y958mAJP4$l=)~2R^P7xnfUV z?8Mj?PT&>cUBE^>^A>y2;kuJ_9^Tjjw0`TyE`?ch@gxH&sHxl&SWW{zY z@m+*o5$5-XBzGtNBhF;L@EH_!J?dAJ^k)56KGfrGz0vsc%sjJFGvx2aTd_rZYzenH&PRtAEl=4zUGQvLPCFd7$Osf6mA2dzA ztIp@6iuI~NIh^P>OTfU^IPPe}9e^G#|9-qvr20C(eubmejq@9 u#4z`5x{JAWaIzB1-(tQKyB{NeIgYR5kNM91-sF9tFSy%l_I~%^o&7((-XkOc literal 0 HcmV?d00001 diff --git a/macros/erode.sci b/macros/erode.sci new file mode 100644 index 0000000..d65cb3e --- /dev/null +++ b/macros/erode.sci @@ -0,0 +1,47 @@ +// Copyright (C) 2015 - IIT Bombay - FOSSEE +// +// This file must be used under the terms of the CeCILL. +// This source file is licensed as described in the file COPYING, which +// you should have received as part of this distribution. The terms +// are also available at +// http://www.cecill.info/licences/Licence_CeCILL_V2-en.txt +// Author: Sukul Bagai +// Organization: FOSSEE, IIT Bombay +// Email: toolbox@scilab.in + +function [out]=erode(input_image ,kernel,anchorX,anchorY,iterations) +// This function Erodes an image by using a specific structuring element. +// +// Calling Sequence +// +// z=imread("lena.jpeg"); +// ero=erode(inputImage,kernel,anchorX,anchorY,iterations); +// +// Parameters +// +// z: input image which should be eroded. +// ero: the output eroded image +// kernel: structuring element used for erosion +// anchorX: x coordinate of Anchor. +// anchorY: y coordinate of Anchor. +// Anchor: position of the anchor within the element. +// Iterations: number of times erosion is applied. +// +// Description +// +// This function Erodes an image by using a specific structuring element. +// +// Examples +// +// z=imread("lena.jpeg"); +// ero=erode(z,[6 4],1,1,4); + + +input_image1=mattolist(input_image); + a=raw_erode(input_image1 ,kernel,anchorX,anchorY,iterations); + dimension=size(a) + for i = 1:dimension + out(:,:,i)=a(i); + end + +endfunction; diff --git a/macros/estimateFundamentalMat.bin b/macros/estimateFundamentalMat.bin new file mode 100644 index 0000000000000000000000000000000000000000..3f318a113dd5d236cc637741af6b7d91f5561253 GIT binary patch literal 6712 zcmeI%$!=U#5C-5*m`sy&5+`;$v^&m(WD=A`AUmY=1~zOEufT={3pUyFDm)Kw!Jt5p z5COyr5$dz=Zy(?IdWy3_SSsB!)bQ6|r%vD8OxEYitK<3P>3n*AygHfA$16|9^Uclk zqtWP0$%Sj}`fT~e=Jww!wO4lME=|rqUR$2d*Uxkt_1Lq1c6WVaJR8q0E>Cw?wntyS zUUACbM#(27nZ1+muD!JK>t=SWY5B72# zm#mhswZ@mVl@j{)%&m*NTymqt-no*s66?VT)75T0G1wSiEMdnNyNp}x(d7e9y7b~R z`_{z@Z#CQ*^T+1T;xM_$C$_=yL+#7^?GmxVfxL|4J2l~x9EZav9R_&sm+%X>IXo@D z_MVphQR~zCZfo;y&#!#Kv6?@w82Aq#;nI2kprplgRNJ#2y(b@g!4zI@cI$YS107F2 z5sWZfZ~N5UArI?AcM{I*e_wdgcXB?=j*WhU)qQC$m)NQKcO}k&dt#`Mofo$FVDozk z8^V_y`Jesa@a@E*6mY}#|P zUo16DPtzA)oLeQqlsX3o9>aahA$z)f7`J=!$r(HBZf|S#b>j=3j-=9jn zi@9_4vp!imU~lM-X7@|k>q-6iM~U8)U;i8o`JgNJU`|bfS>25B%O{R;K##53rl;Gp z@L9LN-|s4u9G}K~vVkSGc%mZ)9rNTE44K=Hy`1dRhaXPw@efL(7r&mcw|8C3DSLkTle>8Q zd0Gpf{P3N6Tc-oNz5dyUjXhk!${siT8>e@jkHn0BYpF%@tEHV>?eXDE2d6c7;F6PC z80QSePk#Sn7d<@5#oXR$ycfeLZtfl!6EC>Jh1htblRj$k^lQ=j#T#8Yz>Yt0;!}(^ zzwqQN1*0{X=viZ*dp;QL(<9+8=UL43m2vLg?5jm^C6}xv-u2QE!`xml^Obn*JyOd% zXTm!pJ9nMD!iV@dkK*PW1cQFKU+amN+}O*Gnh`oS@6DW&cx~Sw&*Y)r&rYwm$<>Rny7Dj@2Ka* zS@iqQj(vRM-x@#O5svFyo=5TBav^`cQlFi6{`jenQ_p>y@`dW3!tJcTR^mGnU4j!& zy)?VD-v6w%HLtDF$^m<@ER}rI#h|Z8_&vxcywOOQ#60(#THNf`)W@8SzLPUu_0vCMSZAx3>C(}^u&l0Moz>^T3w?6-;}mW-li6%- z);Fm6kd1h3)nPmxt^*!O{w`nH#?RimoIWZ?uXbZt4yyq>obJ|Qw76Guym;TRkM}Ju z2ELd6U3Dmx=XIKIr>)LxeEs%hpYOK#5hv#qF1)n-41LcnwJofBb6HwEtaZ8E==M)D zm%Tms+e6rgz7Y@Aeyc_Y@FAb@p{_5+$Hm2`01Br@_ZwAEU*~;1rMH)bqtS zy|VbceBkt*lK(2Fd+V}v;<~I|olMVd?6&{*f6vUv`a>;J7x&R|>w10 + error(msprintf(" Too many input arguments")); + + end + select rhs + case 2 then + [fundamentalMatrix]=raw_estimateFundamentalMat(matchedPoints1,matchedPoints2); + case 3 then + [fundamentalMatrix]=raw_estimateFundamentalMat(matchedPoints1,matchedPoints2,varargin(1)); + case 4 then + [fundamentalMatrix]=raw_estimateFundamentalMat(matchedPoints1,matchedPoints2,varargin(1),varargin(2)); + case 5 then + [fundamentalMatrix]=opencv_estimateFundametanlMatrix(matchedPoints1,matchedPoints2,varargin(1),varargin(2),varargin(3)); + + + end +endfunction diff --git a/macros/extractFeatures.bin b/macros/extractFeatures.bin new file mode 100644 index 0000000000000000000000000000000000000000..3884232cf99b4f59e13e3a02d73d8c80be4d0a3b GIT binary patch literal 28664 zcmeI)$&Y3CRR{16VJMf&JA^qPL?VO$iC|bn zfDj5S0s$5b5(o*QY(OkPC|kx2Y_iFpfFURWBd~$M0z`8@@7-_L@7>|OS8bQNT&gFX zzW4rq=bYb}&+iUh+gJ8>H@Eg)+TPr|w7Y%rT7LJPI(6#H3htjzJiooQcVRb^b$tGw zvpe^F;r!0|y?q+fUtTmj=QdAoH@G={@WKFnHnnwj^Wq|xImPQYcQpb>x9^T(w=lBKQ(#^rapG@dm9p7Bn@cAV&Sf6fRsCD~#)8$41 zn#a4Nb3D;sE_k@Wnp1Xvsncglrmrp9e=VGIb%etX_(j$+e~>Hl?8%mBjkk0ERCC7h zZh1c6jiZZ=-&E%TI$ke`t?Tsm`Mq^+p1tsnEwV-%TVx53XF58xWBNYY&70$IdXp`2 zIYtv3SVw&E9~yckKgdgW>yp<|-FU3vKWZ)4Y#u$X);WG+96ny?*#>U%I6My`FZy+5 zP25I?*zp~m9C%H|Mr`@dr5`=nfL_k&j#duPfu3#tnlr|h$$v5=PjgJZqGkKogT3I; 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zP1QtuO?c{%`P51G8|I98?|@!?T!qKBQ}4^#dw=(){w}k1yyxIsa2 + error(msprintf(" Too many output arguments")); + elseif rhs>13 + error(msprintf(" Too many input arguments")); + end + imageList=mattolist(image); + + //default values + blockSize=0; + upright=1; + surfSize=64; + if (class=="cornerPoints" | class=="BRISKPoints") + method="FREAK"; + elseif (class=="MSERRegions" | class=="SURFPoints") + method="SURF"; + elseif (class=="Matrix") + method="Block"; + else + error(msprintf(" Invalid class type, check documentation for the list of valid types")); + end + + //Count to ensure argument called only once + count_metric=0,count_orientation=0,count_scale=0,count_axes=0,count_signOfLaplacian=0; + count_method=0, count_block=0, count_surf=0, count_upright=0; + blockSize=1; + metric=1; + //Parsing input arguments + for i=1:2:rhs-3 + if (varargin(i)=="Metric") + if(count_metric==0) + i=i+1; + metric=varargin(i); + count_metric=1; + else + error(msprintf(" Metric argument has been called twice")); + end + elseif (varargin(i)=="Orientation") + if(count_orientation==0) + + i=i+1; + orientation=varargin(i); + count_orientation=1; + + else + error(msprintf(" Orientation argument has been called twice")); + end + elseif (varargin(i)=="Scale") + if(count_scale==0) + i=i+1; + scale=varargin(i); + count_scale=1; + else + error(msprintf(" Scale argument has been called twice")); + end + elseif (varargin(i)=="Axes") + if(count_axes==0) + i=i+1; + axes=varargin(i); + count_axes=1; + else + error(msprintf(" Axes argument has been called twice")); + end + elseif (varargin(i)=="SignOfLaplacian") + if(count_signOfLaplacian==0) + i=i+1; + signOfLaplacian=varargin(i); + count_signOfLaplacian=1; + else + error(msprintf("SignOfLaplacian argument has been called twice")); + end + elseif (varargin(i)=="Method") + if(count_method==0) + i=i+1; + method=varargin(i); + count_method=1; + else + error(msprintf("Method argument has been called twice")); + end + elseif (varargin(i)=="BlockSize") + if(count_block==0) + i=i+1; + blockSize=varargin(i); + count_block=1; + else + error(msprintf("BlockSize argument has been called twice")); + end + elseif (varargin(i)=="SurfSize") + if(count_surf==0) + i=i+1; + surfSize=varargin(i); + count_surf=1; + else + error(msprintf("SurfSize argument has been called twice")); + end + elseif (varargin(i)=="Upright") + if(count_upright==0) + i=i+1; + upright=varargin(i); + count_upright=1; + else + error(msprintf("Upright argument has been called twice")); + end + else + error(msprintf("Wrong argument, check documentation for the list of valid arguments")); + end + end + + + select class + case "cornerPoints" then + if(count_metric==0) + error(msprintf("For cornerPoints Class Metric argument is necessary")); + end + [featureVectors ValidPoints numBits numFeatures count metric]= raw_extractFeatures(imageList, points, "Class", class, "Method", method, "surfSize", surfSize, "blockSize", blockSize, "upright", upright, "Metric",metric); + + case "BRISKPoints" then + if(count_metric==0 | count_scale==0 | count_orientation==0) + error(msprintf("For BRISKPoints Class Metric, Orientation and Scale arguments are necessary")); + end + [featureVectors ValidPoints numBits numFeatures scale metrix orientation count]= raw_extractFeatures(imageList, points, "Class", class, "Method", method, "surfSize", surfSize, "blockSize", blockSize, "upright", upright, "Metric",metric,"Orientation",orientation,"Scale",scale); + + case "MSERRegions" then + + if( count_orientation==0 | count_axes==0) + error(msprintf("For MSERRegions Class Orientation Matrix and Axes Matrix arguments are necessary.")); + end + + [featureVectors, ValidPoints, numBits, numFeatures, count, axes, orientation]=raw_extractFeatures(imageList, points, "Class", class, "Method", method, "surfSize", surfSize, "blockSize", blockSize, "upright", upright, "Orientation",orientation,"Axes",axes); + + + case "SURFPoints" then + if(count_scale==0 | count_metric==0 | count_signOfLaplacian==0 | count_orientation==0) + error(msprintf("For SURFPoints Class Metric, Orientation, Scale and SignOfLaplacian arguments are necessary")); + end + [featureVectors ValidPoints numBits numFeatures count scale metrix signOfLaplacian orientation]= raw_extractFeatures(imageList, points, "Class", class, "Method", method, "surfSize", surfSize, "blockSize", blockSize, "upright", upright, "Metric",metric,"Orientation",orientation,"Scale",scale,"SignOfLaplacian",signOfLaplacian); + + + case "Matrix" then + if(count_block==0) + error(msprintf("For Matrix Class BlockSize argument is necessary")); + end + [featureVectors ValidPoints numBits numFeatures]= raw_extractFeatures(imageList, points, "Class", class, "Method", method, "surfSize", surfSize, "blockSize", blockSize, "upright", upright,"BlockSize",blockSize); + end + + + + featureVector=struct("Type","binaryFeatures",'Features',featureVectors,'NumBits',numBits,'NumFeatures',numFeatures); + +endfunction diff --git a/macros/fastNlMeansDenoising.sci b/macros/fastNlMeansDenoising.sci new file mode 100644 index 0000000..033a4f1 --- /dev/null +++ b/macros/fastNlMeansDenoising.sci @@ -0,0 +1,59 @@ +// Copyright (C) 2015 - IIT Bombay - FOSSEE +// +// This file must be used under the terms of the CeCILL. +// This source file is licensed as described in the file COPYING, which +// you should have received as part of this distribution. The terms +// are also available at +// http://www.cecill.info/licences/Licence_CeCILL_V2-en.txt +// Author: Shubham Lohakare, Ashish Manatosh Barik +// Organization: FOSSEE, IIT Bombay +// Email: toolbox@scilab.in +// +function [out] = fastNlMeansDenoising(src, strengthFilter, tempWindowSize, searchWindowSize, choice) +//Removes gaussian white noise from images +// +//Calling Sequence +//outputImage=fastNlMeansDenoising(src, strengthFilter, tempWindowSize, searchWindowSize, choice) +// +//Parameters +//src : Input 8-bit 1-channel, 2-channel, 3-channel or 4-channel image. +//strengthFilter : Parameter regulating filter strength. +//templateWindowSize : Size in pixels of the template patch that is used to compute weights. Should be odd. +//searchWindowSize : Size in pixels of the window that is used to compute weighted average for given pixel. Should be odd. +//choice : Chooses the method +// +//Description +//Perform image denoising using Non-local Means Denoising algorithm with several computational optimizations. Noise expected to be a gaussian white noise. +// +//Examples +//a = imread("man.jpg"); +//strengthFilter = 30; +//tempWindowSize = 7; +//searchWindowSize = 40; +//choice=2; +//k = fastNlMeansDenoising(a, strengthFilter, tempWindowSize, searchWindowSize,choice); +// +//Examples +//a = imread("noise.jpg"); +//strengthFilter = 100; +//tempWindowSize = 7; +//searchWindowSize = 50; +//choice = 3; +//k = fastNlMeansDenoising(a, strengthFilter, tempWindowSize, searchWindowSize,choice); +// +//Authors +//Shubham Lohakare, NITK Surathkal +//Ashish Mantosh, NIT Rourkela + srcMat = mattolist(src) + + output = raw_fastNlMeansDenoising(srcMat, strengthFilter, tempWindowSize, searchWindowSize,choice) + + channels = size(output) + + for i = 1 : channels + out(:,:,i) = (output(i)) + end + out = double(out) + +endfunction + diff --git a/macros/findContours.sci b/macros/findContours.sci new file mode 100644 index 0000000..15e60c1 --- /dev/null +++ b/macros/findContours.sci @@ -0,0 +1,49 @@ +// Copyright (C) 2015 - IIT Bombay - FOSSEE +// +// This file must be used under the terms of the CeCILL. +// This source file is licensed as described in the file COPYING, which +// you should have received as part of this distribution. The terms +// are also available at +// http://www.cecill.info/licences/Licence_CeCILL_V2-en.txt +// Author: Abhilasha Sancheti, Shubham Lohakare, Sukul Bagai +// Organization: FOSSEE, IIT Bombay +// Email: toolbox@scilab.in +// +function [outputMat]= findContours(inputImage, Mode, method, point_x, point_y) +//Finds contours in an image +// +//Calling Sequence +//outputMat = findContours(inputImage, Mode, method, point_x, point_y) +// +//Parameters +//inputImage : The input image +//Mode : Contour retrieval mode (Enter 1 for CV_RETR_EXTERNAL, 2 for CV_RETR_LIST, 3 for CV_RETR_CCOMP, 4 for CV_RETR_TREE) +//method : Contour approximation method (Enter 1 for CV_CHAIN_APPROX_NONE, 2 for CV_CHAIN_APPROX_SIMPLE, 3 for CV_CHAIN_APPROX_TC89_L1, 4 for CV_CHAIN_APPROX_TC89_KCOS) +//point_x : x-coordinate for point offset +//point_y : y-coordinate for point offset +// +//Description +//The function retrieves contours from the images using the algorithm [Suzuki85]. The contours are a useful tool for shape analysis and object detection and recognition. +// +//Examples +//a = imread("lena.jpeg"); +//k = finContours(a,3,2,10,10); +// +//Examples +//a = imread("photo.jpeg"); +//k = findContours(a,1,1,40,60); +// +//Examples +//a = imread("photo1.jpg"); +//k = findContours(a,2,3,50,50); +// +//Authors +//Abhilasha Sancheti +//Shubham Lohakare +//Sukul Bagai + inputList=mattolist(inputImage); + outputList=raw_findContours(inputList,Mode, method, point_x, point_y) + for i=1:size(outputList) + outputMat(:,:,i)=outputList(i) + end +endfunction diff --git a/macros/findHomography.bin b/macros/findHomography.bin new file mode 100644 index 0000000000000000000000000000000000000000..f00ebaf4fc6e905fb58ad62006cfacf52c0bce7a GIT binary patch literal 8316 zcmdtnTW?fV6bJAD6>AZCG4$dTX)7^U5VcAOY66MTXT!TsCO#RzrB8kgG+q<%5}#CD zzv2AH?O{$kU@=IOm9zI=_y1aZotf#<>iVhM>uVd!x4E&pes=5FR40pj=f|_1KF=+V7st!1>(hg7@yD~H(NftvSM)*Ag`!(` z@7`Uh=W5YbclJ}Ay;SS`FpD<_|$T`h7Y}8D`z@%QSx7| zHU3w{XY0ix_$3B8TgUc(t;w@1Cb@aC6Aa*mzgzTu=QkMfyHmstn~6gmZkOylHeW4S zKFCI&eK_dHw~L1O$BVaDbg?KoU90u~JtsM>tG}a{t6W&rE`)xX8=j zT{Jh~k(q&)IR$U~)Frykt=YiKeWsT^+nI;*pEdvbcbVMKdaAWEWP+9V}?dn{_>f`mlqkdG|QwD=xXgTfXphc37TQI+^zV zXVc3triasl9*cTRnkVefK8#ic??w*PH>%#rFqVI})7P2-U z@XbSh`@JI%nBXVgU_I2Q{Wum%S3HU1hw>?x_+t+*eVtn4XD0reIJV0U|2{XJ=+=qF zyALkk7X25P-0b|Prs*HJ=f0^s4BGn+3-?K{z+Ejo<%O4iQLF7D__Bc?ANnRZzEEp2 z=7Ct+yFv$#Y~($iljS38=VZlz=iJ(JR-fja44<)UpF3)ux|6Y%pLODD=SsdS>1(lx zgIw^lZ)XX6!7rZ!5(j<#n>g(g13QVatruIV8NJxFCMTcV6=$($-H&Y+W^CwP^1&vx z9g_D>%so_Ny1x`YaAD7xoW;V1IIQIhpXh#GYr6R!O5Yw|-eiY*h)i-7FTb;LNDqmD zO?!4DKMNyqkRv00`!6R0 ze!lP=suwKcGxt5UOda?OR>3fs&61H*&gZS68P(SDuo~ubO>i_5`8`T3lS7+-AKTB$ zCv4y7$lC0oqfe1DxE(elw@Zdk*yfI@4_oa!L*KLIEbkXM^P`4*Ss&ET{IElg4SMmb zkA`|%EPSaCU2!_goqDF$&lTnKrgOFvPh_2oA$IzD2gNS7{#|5msE^y2_ezew{<&5p zE;SM(O!teDJACxhgZxgHe$>l9cK6kp&z5`ycUX(rjEasPo>xze$X_aIv18AfJW=MJ zocbhhpMmptycYFi^nJfY`$_uGil0Be{LW1l$-|SM@yb^JXY9$oSfeus@Wi!H^hG&g z+n>H*_aHrTf5(64y4c<;q9@i5i`Yp&=RWe0Ic%<~OL{c#D7D`$(jVy!x#~-OVvX1K zR_>%eq@Nm#XKib9T>lwZ>H{+C^*y{JxY^T<2*{2p_P>bwO)>?gL&C7Xe$sQl>uC+P$ zWYl*wsqed8KKkfpkv@5?NYAwOeWmvLt^F=V2F~#I4#bC*`{OLNfIl)@gCp$8^MPlN z=ZqeVJ?E*><5-Uhee!p!5`^jNMesrkMJH+w^=IGwck^ED_REgk)$Vc;KW`TC0av`C z|4;s2{)^qn-2cDIR%X1oeST@i|4Gdze)67>lX%q8)2tZ!|7o!%u|D{0TA1{1oB#E) z#g6ysQRffK_PrzDq5tC!&1yOaVFIqFAT2~J&qXuvks#hkD?B+ aPaQlTv<{^*`P;1l2+ONQu1 + error(msprintf(" Too many output arguments")); + elseif rhs>4 + error(msprintf(" Too many input arguments,maximum number of arguments is 4")); + elseif rhs<2 + error(msprintf("the function needs atleast 2 arguments")); + end + + if rhs==2 then + homography_matrix=raw_findHomography(points1,points2); + elseif rhs==3 + homography_matrix=raw_findHomography(points1,points2,varargin(1)); + elseif rhs==4 + homography_matrix=raw_findHomography(points1,points2,varargin(1),varargin(2)); + end + + + +endfunction diff --git a/macros/fitellipse.bin b/macros/fitellipse.bin new file mode 100644 index 0000000000000000000000000000000000000000..b314a18ef9aea54f63f909ffc03222f49adb1457 GIT binary patch literal 3312 zcmeI#+fEcg5C-4{Bt}HgHOOIiP|+AfV+i^R`XXNWtUiNRns{SKJcKJF*0;{TnI$ve zt%)R+uCA*7>)5@+=D69|+8XapHx3v6ZjDBxrJ|kvW%LPjb9h#9#c9>qjtN z7e5sD^Hv9kjdO5dn1{?c9X_+p#+lSLYwAmv`Z&wJJL~RhVh#>_{@Ihsmp^eh--mNq zo!R%*ijVI6$d&C-Pg0}Ps=FCs*Ny3_`G(DB@=ae#H1CnxvU5+^u_qIo+VZIe`1GI; z=l|RFr_Pz9)cs$0yKYo(&A_*sfrqua1MaroyBnE{zP{5rd)yM#6x)k9-mmu+V`5TUc<$8QA~I-wO9n zZ^g*Jv#`FDzq6tbMe0b_eQU(!Uhx4tcfZTib>FJX;(#T0G4O@YI|h@?JH{^_E*pNu z@9>FG4cedger+u*1NUn4TMc#R}q30K#v-08t!S+@UeFOe1 zj8e~RCTkBKZ}xm={wf>ak*h`Z$vCsc^Ji7VW;I`xi)*Py&9y~Yb~D{dc8lvwx4bCJ zZl+txZgHhc-eMJ>ny8VUtDRibq#3|SO@_`pJ3BuRU-$g=vNa?8rbl@5IFDnX27ik) zk7uCHT^#jrFT~>gFdyQX<#Rp@-rh=Gcxo)N~z}a`nKhN E1N;B|c>n+a literal 0 HcmV?d00001 diff --git a/macros/fitellipse.sci b/macros/fitellipse.sci new file mode 100644 index 0000000..3eabc50 --- /dev/null +++ b/macros/fitellipse.sci @@ -0,0 +1,37 @@ +// Copyright (C) 2015 - IIT Bombay - FOSSEE +// +// This file must be used under the terms of the CeCILL. +// This source file is licensed as described in the file COPYING, which +// you should have received as part of this distribution. The terms +// are also available at +// http://www.cecill.info/licences/Licence_CeCILL_V2-en.txt +// Author: Nihar Rao & Priyanka Gandhi +// Organization: FOSSEE, IIT Bombay +// Email: toolbox@scilab.in +function [out]=fitellipse(InputArraypoints) +// The function calculates the ellipse that fits (in a least-squares sense) a set of 2D points best of all. +// +// Calling Sequence +// +// felli=fitellipse(points); +// +// Parameters +// felli: a struct containing all the details about the ellipse Params. +// points: Input 2D point set +// +// Description +// +// The function calculates the ellipse that fits (in a least-squares sense) a set of 2D points best of all. +// +// Examples +// +// // read image +// z=imread("lena.jpeg",0); +// //get points using KAZE detector or the points can also be hardcoded. +// pio=detectKAZEFeatures(z); +// // call function +// sss=fitellipse(pio.KeyPoints) + + [t1 t2 t3 t4 t5]= raw_fitellipse(InputArraypoints); + out=struct("size1",t1,"size2",t2,"center1",t3,"center2",t4,"angle",t3); +endfunction; diff --git a/macros/graycoprops.bin b/macros/graycoprops.bin new file mode 100644 index 0000000000000000000000000000000000000000..2ff408479b670c8404d32851d5f00c869de3c954 GIT binary patch literal 10468 zcmeI%O>bOh6$kK1%1f9U*D;DcW<05zb`jD*OF)T0sEH5=i3N+USh1;C&}F{`V#!Bf z+i!yS6huOF0TCcpfH}YM{oBu6-#cTwCaO?JI(lBt`~RHhx!2b_^Xa{<*};5vaCpD{ zeRVRK+$cI+Oc$%16RDec^R2(^?X+4a^Vg^I>3nB*zt34rCzIDo@Aaae7TquUFmwu%--__HE=^z2*j6&)0jC%0V`JJxL5qw}ZoHLsB#9sAa?-|CVP z2fdvlauxpMUeULT?i7)ii_yA`iwqm$MB-xukxy>s^yI<5SjfotjiT=q1+$u-&gDh# zAC(h5{t-R4#f<;F_T2e0H5d|)XSI;p)FvY$M@*~!G$pDPA3>5YdSU!JkWSNiJJ zn#ZSoGQq-Hyy3?;8F5Dr24d4Ic(L=`VQ|&jj8`dG1-(qzi{W%ePBHn zgF8WO+B^87{lu)@{o9v|idO!?`M_-DsjWuU6XO?U*OHIGm>0D>;Ubd!UZhOF4 zLt@pZa?aUH|B{d1SS{LqNWMQQTlD^4^9?5Y4_590qkLPO^b1V;=O#E6>-2upgY0^j zPz$v&vdtztM*Ho(Sj$rzV|V<+l41LwT|INRvE|wAJg`rue@?}azRxI6vUu&?&PM-C zUM82EEzg&J%zVRwz2Gc{oV&zhjGTDnNY^`0aQ|h^$@Oy$=D{a1@EN;mU`;0PUiR?C z!iRYui(qG;yjW1O0>%}-koyu7Q*pFMVS zx0@$M`ti*N-Sp1;HD^0{k>w|OwAiJti8pnDn>l}ZcW&{+qiZj**h_wi-MZBiv$Y;# zTU=z4i_toIEk1oL;i67t@%XgX2V%Bo&4!%$ZSC>34$rpUKkxL@`+OxwHiAd%52p4v zVbqT+bvx>GH~ExDdL;hF&Q0l?4{Q7 z?AJMVe%tAO{&)6S52jCpU;fSxMlgmqT*>GUbNkl8I<+91yIv3J8~tMcD(`Za`I{%Q zVoAS>F?Vp@4dslVGh#ny>>_s~`Sva-Q>Xpe&c9L%dH=2C;mR-j@XI~pe5F6}$iLfB z&UtilhovU;)I*N+a@OHa$6D^>VF}t&SxafUk9*R@k;xvl0?0+)tE0&#NEpZW#Gx}kD1QU9M;C23xaXd%=LM zR~uUw>Gc!4!#T8e)yOkSe9jKr>U6J&jWLW`8)Exwm#6zpzHH?Dx);sWC3eT^61#jK zF6MW)2KrOoVVg7PS=;uux{v+8rdR|0IeGSRfh^{S9bXMs?}Zmn#WeOmouOV7(=w0U zH@DAs+2*@M9$T|JgO^FMCiB_RD9;(=dz}m$WY+m01Lt>&$o6qwJsoFRmgo{^b^3MH zi=H2h*;%JY?(FW^dB*<_isJtlHD^amxl3~9Jg@YbcRD@iQ0BcrZ|g<9P9JaV86KYZ zuISri*FBhT36Zn+MiKjLW~6UT&bbh;x%_)$zRWdOAc2R0@ROWTb z=I>U~kN$mp3`f7q_tlH1`bxi~uYT3p$@{&Y!W(-|=B~P~dt%*lP8_-KJP-QkaCUd# zqO6*i=xKe1;vBfFj(!AlV`^j z`(!A@`{|QaKmWUaT=jG7)Aaoy=E-MM-+LaX@4sC0m(%wr?`!Q{`-k%F{Jd9`ntxXN z-d&;Zja}crGSpPX*4u;i>3E-?i2^RY`m)Z%s-K-tbM^-7o_sc)J@2PEdsq4U)H%uT cdH1gU!`iSP3je+OgU0##al?y@@q=#vzn3AP_y7O^ literal 0 HcmV?d00001 diff --git a/macros/graycoprops.sci b/macros/graycoprops.sci new file mode 100644 index 0000000..ae4b002 --- /dev/null +++ b/macros/graycoprops.sci @@ -0,0 +1,83 @@ +// Copyright (C) 2015 - IIT Bombay - FOSSEE +// +// This file must be used under the terms of the CeCILL. +// This source file is licensed as described in the file COPYING, which +// you should have received as part of this distribution. The terms +// are also available at +// http://www.cecill.info/licences/Licence_CeCILL_V2-en.txt +// Author: Nihar Rao +// Organization: FOSSEE, IIT Bombay +// Email: toolbox@scilab.in +function[stats] = graycoprops(srcImg, varargin) +// This function computes the Properties of gray-level co-occurrence matrix. +// +// Calling Sequence +// z=imread("lena.jpeg"); //in grayscale or color +// //Note: z can be a image or simply a Matrix. +// gray=graycoprops(z) //get all 4 properties +// gray=graycoprops(z,"contrast") //compute only contrast +// gray=graycoprops(z,["contrast" "energy"]) //compute contrast and energy.the properties can be passed in any order +// gray=graycoprops(z,["contrast" "correlation" "energy"]) +// gray=graycoprops(z,["contrast" "correlation" "energy" "homogeneity"]) +// +// Parameters +// +// gray: A struct containing all the parameters +// z: A image or a matrix +// contrast: a measure of the intensity contrast between a pixel and its neighbor over the whole image. +// energy: the sum of squared elements +// homogeneity: a value that measures the closeness of the distribution of elements. +// correlation:a measure of how correlated a pixel is to its neighbor over the whole image +// +// Description +// This function computes the Properties of gray-level co-occurrence matrix.The properties being "correlation","contrast","energy" and "homogeneity". +// +// +// Examples +// //compute for a image +// z=imread("lena.jpeg",0); +// sss=graycoprops(z,["contrast"]) +// +// //compute for a matrix +// glcm = [0 1 2 3;1 1 2 3;1 0 2 0;0 0 0 3] +// sss=graycoprops(glcm,["contrast" "energy" "correlation"]) + + + [lhs, rhs] = argn(0) + + srcMat = mattolist(srcImg) + + select rhs + case 1 then + [contrast correlation energy homo] = raw_graycoprops(srcMat); + stats=struct('Contrast',contrast,'Correlation',correlation,'Energy',energy,'Homogeniety',homo); + case 2 then + [rows cols]=size(varargin(1)); + n=rows*cols; + if n>4 + error(msprintf("the string matrix must have maximimum of 4 entries")); + end + inputString=varargin(1); + if n==1 + [out]=raw_graycoprops(srcMat,varargin(1)); + stats=struct(inputString(1),out); + elseif n==2 + [out out1]=raw_graycoprops(srcMat,varargin(1)); + stats=struct(inputString(1),out,inputString(2),out1); + + elseif n==3 + [out out1 out2]=raw_graycoprops(srcMat,varargin(1)); + stats=struct(inputString(1),out,inputString(2),out1,inputString(3),out2); + + elseif n==4 + [out out1 out2 out3]=raw_graycoprops(srcMat,varargin(1)); + stats=struct(inputString(1),out,inputString(2),out1,inputString(3),out2,inputString(4),out3); + + end + + + end + + + +endfunction diff --git a/macros/histeq.sci b/macros/histeq.sci new file mode 100644 index 0000000..9a6f4b6 --- /dev/null +++ b/macros/histeq.sci @@ -0,0 +1,49 @@ +// Copyright (C) 2015 - IIT Bombay - FOSSEE +// +// This file must be used under the terms of the CeCILL. +// This source file is licensed as described in the file COPYING, which +// you should have received as part of this distribution. The terms +// are also available at +// http://www.cecill.info/licences/Licence_CeCILL_V2-en.txt +// Author: Priyanka Hiranandani, Shubham Lohakare +// Organization: FOSSEE, IIT Bombay +// Email: toolbox@scilab.in +// +function [out]=histeq(src) +//Equalizes the histogram of an image +// +//Calling Sequence +//outputImage = histeq (inputImage) +// +//Parameters +//inputImage : The input image for which the histogram has to be equalised +// +//Description +//The function equalizes the histogram of the input image using the following algorithm: 1. Calculate the histogram H for src. 2. Normalize the histogram so that the sum of histogram bins is 255. 3. Compute the integral of the histogram. 4. Transform the image using H' as a look-up table: dst(x,y) = H'(src(x,y)). The algorithm normalizes the brightness and increases the contrast of the image. +// +//Examples +//a = imread("lena.jpeg"); +//k = histeq(a); +//imshow(k); +// +//Examples +//a = imread("bryan.jpg"); +//k = histeq(a); +//imshow(k); +// +//Examples +//a = imread("photo.jpg"); +//k = histeq(a); +//imshow(k); +// +//Authors +//Shubham Lohakare, NITK Surathkal +//Priyanka Hiranandani, NIT Surat + srcMat=mattolist(src) + output=raw_histeq(srcMat) + channels = size(output) + for i = 1: channels + out(:,:,i)=(output(i)) + end + out = double(out) +endfunction; diff --git a/macros/imadd.sci b/macros/imadd.sci new file mode 100644 index 0000000..66aaaa6 --- /dev/null +++ b/macros/imadd.sci @@ -0,0 +1,51 @@ +// Copyright (C) 2015 - IIT Bombay - FOSSEE +// +// This file must be used under the terms of the CeCILL. +// This source file is licensed as described in the file COPYING, which +// you should have received as part of this distribution. The terms +// are also available at +// http://www.cecill.info/licences/Licence_CeCILL_V2-en.txt +// Author: Tess Zacharias, Shubham Lohakare +// Organization: FOSSEE, IIT Bombay +// Email: toolbox@scilab.in +// +function [out] = imadd(srcImg1, srcImg2) +//Add the contents of 2 matrices or images and store it in another +// +//Calling Sequence +//outputMat = imadd(input1, input2) +// +//Parameters +//input1 : First input matrix or an image +//input2 : Second input matrix or image +// +//Description +//Z = imadd(X,Y) adds each element in array X with the corresponding element in array Y and returns the sum in the corresponding element of the output array Z. X and Y are real, nonsparse numeric arrays with the same size and class, or Y is a scalar double. Z has the same size and class as X, unless X is logical, in which case Z is double. +// +//Examples +//a = [1 5 6;4 2 3]; +//b = [8 10 15;5 1 9]; +//c = imadd(a,b); +// +//Examples +//a = imread("lena.jpeg"); +//b = imread("lena1.jpeg"); +//c = imadd(a,b); +//imshow(c) +// +//Authors +//Tess Zacharias +//Shubham Lohakare + + srcMat1=mattolist(srcImg1) + srcMat2=mattolist(srcImg2) + + output = raw_imadd(srcMat1, srcMat2) + channels = size(output) + + for i = 1: channels + out(:,:,i)= (output(i)) + end + out=double(out) + +endfunction diff --git a/macros/imcomplement.sci b/macros/imcomplement.sci new file mode 100644 index 0000000..3e4cef0 --- /dev/null +++ b/macros/imcomplement.sci @@ -0,0 +1,47 @@ +// Copyright (C) 2015 - IIT Bombay - FOSSEE +// +// This file must be used under the terms of the CeCILL. +// This source file is licensed as described in the file COPYING, which +// you should have received as part of this distribution. The terms +// are also available at +// http://www.cecill.info/licences/Licence_CeCILL_V2-en.txt +// Author: Tess Zacharias, Shubham Lohakare +// Organization: FOSSEE, IIT Bombay +// Email: toolbox@scilab.in +// +function [compMat] = imcomplement(srcImg) +//Computes the complement of the image +// +//Calling Sequence +//compMat = imcomplement(srcImg) +// +//Parameters +//srcImg : Input image +// +//Description +//In the complement of a binary image, zeros become ones and ones become zeros; black and white are reversed. In the complement of an intensity or RGB image, each pixel value is subtracted from the maximum pixel value supported by the class (or 1.0 for double-precision images) and the difference is used as the pixel value in the output image. In the output image, dark areas become lighter and light areas become darker. +// +//Examples +//a = imread("lena.jpeg"); +//k = imcomplement(a); +//imshow(k) +// +//Examples +//a = imread("photo1.jpg"); +//k = imcomplement(a); +//imshow(k) +// +//Authors +//Tess Zacharias +//Shubham Lohakare + srcMat = mattolist(srcImg) + + out = raw_imcomplement(srcMat) + + ch = size(out) + + for i=1:ch + compMat(:,:,i) = out(i) + end + +endfunction diff --git a/macros/imcontour.sci b/macros/imcontour.sci new file mode 100644 index 0000000..ad26ff7 --- /dev/null +++ b/macros/imcontour.sci @@ -0,0 +1,53 @@ +// Copyright (C) 2015 - IIT Bombay - FOSSEE +// +// This file must be used under the terms of the CeCILL. +// This source file is licensed as described in the file COPYING, which +// you should have received as part of this distribution. The terms +// are also available at +// http://www.cecill.info/licences/Licence_CeCILL_V2-en.txt +// Author: Shubham Lohakare, Tess Zacharias +// Organization: FOSSEE, IIT Bombay +// Email: toolbox@scilab.in +// +function [contourMat] = imcontour(matA) +//Draws a contour plot for the input image +// +//Calling Sequence +//contourMat = imcontour(srcImg) +// +//Parameters +//srcImg : THe input image +// +//Description +//The function draws contour outlines in the image. +// +//Examples +//a = imread("lena.jpeg"); +//k = imcontour(a); +//imshow(k) +// +//Examples +//a = imread("photo1.jpg"); +//k = imcontour(a); +//imshow(k) +// +//Examples +//a = imread("bryan.jpg"); +//k = imcontour(a); +//imshow(k) +// +//Authors +//Tess zacharias +//Shubham Lohakare + srcMat = mattolist(matA) + + out = raw_imcontour(srcMat) + + ch = size(out) + + for i=1:ch + contourMat(:,:,i) = out(i) + end + + +endfunction diff --git a/macros/imcrop.sci~ b/macros/imcrop.sci~ new file mode 100644 index 0000000..7af043f --- /dev/null +++ b/macros/imcrop.sci~ @@ -0,0 +1,5 @@ +function[cropImg] = imcrop(srcImg, xcoor, ycoor, width, height) + srcMat = mattolist(srcImg) + disp(srcMat) + cropImg = opencv_imcrop(srcMat, xcoor, ycoor, width, height) +endfunction diff --git a/macros/imdecolor.sci b/macros/imdecolor.sci new file mode 100644 index 0000000..73c0a99 --- /dev/null +++ b/macros/imdecolor.sci @@ -0,0 +1,60 @@ +// Copyright (C) 2015 - IIT Bombay - FOSSEE +// +// This file must be used under the terms of the CeCILL. +// This source file is licensed as described in the file COPYING, which +// you should have received as part of this distribution. The terms +// are also available at +// http://www.cecill.info/licences/Licence_CeCILL_V2-en.txt +// Author: Shubham Lohakare, Ashish Manatosh Barik +// Organization: FOSSEE, IIT Bombay +// Email: toolbox@scilab.in +// +function [outImg1, outImg2] = imdecolor(srcImg1) +//Decolors and color boosts an image giving 2 outputs for the same respectively. +// +//Calling Sequence +//[outImg1, outImg2] = imdecolor(srcImg1) +// +//Parameters +//srcImg1 : It is a 3-channel input image. +//outImg1 : It is a grayscale image of the image passed as input. +//outImg2 : It is a color boosted image of the image passed as input. +// +//Description +//This function is used to decolor an image and also add a boost to it's color +//The output are 2 images, one is a grayscale and the other is a color boosted image +// +//Examples +//var=imread("ImageName"); +//[decoloredImage,colorBoostedImage] = imdecolor(var); +//PRESS ENTER +//imshow(decoloredImage); shows the decolored Image +//imshow(colorBoostedImage); shows the color boosted image +// +//Examples +//a = imread("images.jpeg"); +//[b, c] = imdecolor(a); +//PRESS ENTER +//imshow(b); shows the decolored Image +//imshow(c); shows the color boosted image +// +//Authors +//Shubham Lohakare, NITK Surathkal +//Ashish Mantosh, NIT Rourkela + srcMat1 = mattolist(srcImg1) + + + [out1, out2] = raw_imdecolor(srcMat1) + + channels1 = size(out1) + channels2 = size(out2) + + for i = 1:channels1 + outImg1(:, :, i) = (out1(i)) + end + + for j = 1:channels2 + outImg2(:, :, j) = (out2(j)) + end + +endfunction diff --git a/macros/imdivide.sci b/macros/imdivide.sci new file mode 100644 index 0000000..091df7a --- /dev/null +++ b/macros/imdivide.sci @@ -0,0 +1,54 @@ +// Copyright (C) 2015 - IIT Bombay - FOSSEE +// +// This file must be used under the terms of the CeCILL. +// This source file is licensed as described in the file COPYING, which +// you should have received as part of this distribution. The terms +// are also available at +// http://www.cecill.info/licences/Licence_CeCILL_V2-en.txt +// Author: Tess Zacharias, Shubham Lohakare +// Organization: FOSSEE, IIT Bombay +// Email: toolbox@scilab.in +// +function [out] = imdivide(srcImg1, srcImg2) +// Divides one image with another or divide image by constant. +// +//Calling Sequence +//outputMat = imdivide(input1, input2) +// +//Parameters +//input1 : Image or an array +//input2 : Image or an array of same size or a scalar +// +//Description +//imdivide takes 2 inputs, either both images which should be of the same size or one image and another scalar which is used as the divisor. Also the inputs can be two arrays of the same size or one array and one scalar. The output is the quotient of the two. +// +//Examples +//k = imread("lena.jpeg"); +//p = imdivide(k,2); +//imshow(p); +// +//Examples +//k = imread("photo.jpg"); +//p = imdivide(k,0.8); +//imshow(p); +// +//Examples +//a = [10 20;50 10]; +//b = 5; +//p = imdivide(a,b); +// +//Authors +//Tess Zacharias +//Shubham Lohakare + srcMat1=mattolist(srcImg1) + srcMat2=mattolist(srcImg2) + + output=raw_imdivide(srcMat1, srcMat2) + + channels = size(output) + + for i = 1: channels + out(:,:,i)=(output(i)) + end + out = double(out) +endfunction; diff --git a/macros/imfill.sci b/macros/imfill.sci new file mode 100644 index 0000000..2b11f48 --- /dev/null +++ b/macros/imfill.sci @@ -0,0 +1,61 @@ +// Copyright (C) 2015 - IIT Bombay - FOSSEE +// +// This file must be used under the terms of the CeCILL. +// This source file is licensed as described in the file COPYING, which +// you should have received as part of this distribution. The terms +// are also available at +// http://www.cecill.info/licences/Licence_CeCILL_V2-en.txt +// Author: Vinay Bhat, Shubham Lohakare +// Organization: FOSSEE, IIT Bombay +// Email: toolbox@scilab.in +// +function [dstMat] = imfill(srcImg, varargin) +//Fills in the regions and holes in an image. +// +//Calling Sequence +//[outputImage] = imfill(srcImg) +//[outputImage] = imfill(srcImg,locations) +// +//Parameters +//srcImg : It is the input image +//locations : If locations is a P-by-1 vector, it contains the linear indices of starting locations. If locations is P-by-ndims(BW) matrix, each row contains the array indices of one of the starting locations. +// +//Description +//The function performs a flood-fill operation on the pixels of the input image. +// +//Examples +//k = imread("lena.jpeg"); +//im = imfill(k, [1 1; 10 10; 11 12]); +//imshow(im); +// +//Examples +//k = imread("lena1.jpeg"); +//im = imfill(k, [1 1; 20 20; 11 12;50 50;]); +//imshow(im); +// +//Examples +//k = imread("penguin.jpg"); +//p = imfill(k); +//imshow(p); +// +//Authors +//Vinay Bhat +//Shubham Lohakare + [lhs, rhs] = argn(0) + + srcMat = mattolist(srcImg) + + select rhs + case 1 then + out = raw_imfill(srcMat) + case 2 then + out = raw_imfill(srcMat, varargin(1)) + end + + channel = size(out) + + for i = 1: channel + dstMat(:,:,i) = out(i) + end + +endfunction diff --git a/macros/imhmin.sci~ b/macros/imhmin.sci~ new file mode 100644 index 0000000..d57e774 --- /dev/null +++ b/macros/imhmin.sci~ @@ -0,0 +1,15 @@ +unction[dstMat] = imfill(srcImg, H-min) + + [lhs, rhs] = argn(0) + + srcMat = mattolist(srcImg) + + out = opencv_imfill(srcMat, H-min) + + channel = size(out) + + for i = 1: channel + dstMat(:,:,i) = out(i) + end + +endfunction diff --git a/macros/iminpaint.sci b/macros/iminpaint.sci new file mode 100644 index 0000000..c98e96b --- /dev/null +++ b/macros/iminpaint.sci @@ -0,0 +1,54 @@ +// Copyright (C) 2015 - IIT Bombay - FOSSEE +// +// This file must be used under the terms of the CeCILL. +// This source file is licensed as described in the file COPYING, which +// you should have received as part of this distribution. The terms +// are also available at +// http://www.cecill.info/licences/Licence_CeCILL_V2-en.txt +// Author: Shubham Lohakare, Ashish Manatosh Barik +// Organization: FOSSEE, IIT Bombay +// Email: toolbox@scilab.in +// +function [pImg] = iminpaint(srcImg1,mask,radius,methodNum) +//Inpaints the unwanted area in an image using the neighboring pixel points +// +//Calling Sequence +//pImg = iminpaint(srcImg1,maskedRectangle,radius,methodNum) +// +//Parameters +//srcImg : It is the input image +//maskedRectangle: It is a vector of double used which contains the co-ordinates of the masking rectangle +//radius : Radius of a circular neighborhood of each point inpainted that is considered by the algorithm. +//methodNum : Inpainting method that could be one of the following,INPAINT_NS Navier-Stokes based method or INPAINT_TELEA Method by Alexandru Telea +// +//Description +//The function reconstructs the selected image area from the pixel near the area boundary. The function may be used to remove dust and scratches from a scanned photo, or to remove undesirable objects from still images. +// +//Examples +//a = imread("p1.jpeg"); +//b = [210,40,100,200]; +//typeOfMethod = 2; +//radius = 50; +//c = iminpaint(a,b,radius,typeOfMethod); +// +//Examples +//a = imread("orig.jpg"); +//b = [100,157,120,150]; +//typeOfMethod = 1; +//radius = 5; +//c = iminpaint(a,b,radius,typeOfMethod); +// +//Authors +//Shubham Lohakare, NITK Surathkal +//Ashish Mantosh, NIT Rourkela + srcMat1 = mattolist(srcImg1) + srcMat2 = mattolist(mask) + out=raw_iminpaint(srcMat1,srcMat2,radius,methodNum) + + channels = size(out) + + for i = 1 : channels + pImg(:,:,i) = (out(i)) + end + pImg = double(pImg) +endfunction diff --git a/macros/immultiply.sci b/macros/immultiply.sci new file mode 100644 index 0000000..a64f97e --- /dev/null +++ b/macros/immultiply.sci @@ -0,0 +1,53 @@ +// Copyright (C) 2015 - IIT Bombay - FOSSEE +// +// This file must be used under the terms of the CeCILL. +// This source file is licensed as described in the file COPYING, which +// you should have received as part of this distribution. The terms +// are also available at +// http://www.cecill.info/licences/Licence_CeCILL_V2-en.txt +// Author: Tess Zacharias, Shubham Lohakare +// Organization: FOSSEE, IIT Bombay +// Email: toolbox@scilab.in +// +function [multiplyMat] = immultiply(srcImg1, srcImg2) +//Multiply the contents of 2 matrices and store it in another +// +//Calling Sequence +//multiplyMat = immultiply(input1, input2) +// +//Parameters +//input1 : First input matrix or an image +//input2 : Second input matrix or image +// +//Description +//p=immultiply(a,b) multiplies each of the element in the first argument's array with the corrresponding element in the second argument's array and the answer is stored in p. +// +//Examples +//a = imread("lena.jpeg"); +//k = immultiply(a,2); +//imshow(k) +// +//Examples +//a = imread("photo.jpg"); +//k = immultiply(a,0.5); +//imshow(k) +// +//Examples +//a = [1 2 3; 4 5 6]; +//b = [10 20 30;10 20 30]; +//k = immultiply(a,b); +//disp(k) +// +//Authors +//Tess Zacharias +//Shubham Lohakare + srcMat1=mattolist(srcImg1) + srcMat2=mattolist(srcImg2) + out = raw_immultiply(srcMat1, srcMat2) + + channel = size(out) + + for i = 1: channel + multiplyMat(:,:,i) = out(i) + end +endfunction diff --git a/macros/imread.bin b/macros/imread.bin new file mode 100644 index 0000000000000000000000000000000000000000..d344d4d01f63abe8e7e806b71f88ba7843156883 GIT binary patch literal 8756 zcmeI&OOF*r6bJC}JzijdQ5f*f$nemNfQl%ZD2XnNOBcokuHCpZeg@ZmDwlo;6CW|r z#Ncyf#Pb{akCmG4JAjN5u#=OnuJit%Q&l~EXZ7fOWp-d|$8}(7Y3YHY1M3^#&o*|j zw;n9s(b>lDJ2_ihCuZ~6{Lt!J&--L~Y3X3;ohW*}XshV!YuBzFuKQ}y`Y=c4>7uow z{Y4u^_{WOO(QD<&(p@PMH$ENm#^06?yjc*b|#r@V^;ydaB0q=R0^A$7e95-{*6&<}xoQ zdcotl8h=qf!Z#lr&eZt$APZ+PlRaDab4Brey2fH1vvH?=zfykGL|lEpz(8z?tA;nm z`)Vx4?*_c#AXiwygDrRS?8L^qHJ-|C44?CZJlm-s+w8)pt?gz#XHDq;^n|e-$AWv_qZY^%|X8*^k zRWRTueaV+TAhQUoV3xJiV=xsDyJE-Z%X7Q;WR5*D`0$aNIK{*_8>fn3K_+WCm<2y; zpPkL3G2iwXI{c*<=MXam zw|2|#gtp0$#FhM(*e^jbgcZWf81Z9c>j-|SAUljP^l zF1_WV9@nuxeRz;RKitRipQ=S-r4wA*+NTcq=H*~*c@B1RMP&6yyVjC>`ic*_?S7cG zDEBr${Y7?pxVQPW`zM*U4xZId?XvdGdFEf7Z5{C1cswWGU=bYB7rj6HE*sASuglVykyuFKb+)#tNSSZ^a;EZXV$ytF|5od zX77JlJLyTb)EriLu?^1)MfRW;@AvDOP5j4(@m}KnZ|vdnxf`%eFK6!;*Ir_qzPMj{ z*?vCO%kWO0?IqsvVXZCNC;rL%$bZ$#J+|p(?>GH9D*wD2wC9DrR{T@@*#Ge5q(D|i&vdyQs0d6Qi|&W-kik~&uHev)AFl^;>Upy6YT%s} zj(PWladh)HME{MI4Z7~IAA9e`PmhpMr^uW44f3msLtm(Adxq(Yyg#0;aoZ#0*s*V+ z-M*zJK0U*xxb#+X^o=!f^?6(@-jsg6p~@@0X)M+!ieM^_v2Uj}eZ#-C!T%V>@h#?H zLbk=$yxh!9{T+~8?=*I8efJ7Gf5*Gd7M&}S3(~L7r(E{Z`e9@OuA~#`bfumX0joC7$Jy`@9^n?@|}G7wMAwJBO=pitlm}J@LL%#ExD| z&hq9XeQR&iL+PW`!MZwCq+jszeMVnqoL^OTNy&{dDw+H^f&5quZbt;8C9m)`2}{b;b0zJhJ=RR{Ro48GPWylw|u z{hgYftZ~+SY9R);^SrOd>Z4|OY6}lzd%$kBB*#bAuG+p-#K*l+=j-d}jUgZX^j?vE zdA_J$N6*%rzOy&N6+UF(4HIV*KFnZkj*L5bYlo7V>0pE^dIHFM7Q5(7BYu{p99IjW3ICGr3O literal 0 HcmV?d00001 diff --git a/macros/imread.sci b/macros/imread.sci new file mode 100644 index 0000000..3aaf9b0 --- /dev/null +++ b/macros/imread.sci @@ -0,0 +1,72 @@ +// Copyright (C) 2015 - IIT Bombay - FOSSEE +// +// This file must be used under the terms of the CeCILL. +// This source file is licensed as described in the file COPYING, which +// you should have received as part of this distribution. The terms +// are also available at +// http://www.cecill.info/licences/Licence_CeCILL_V2-en.txt +// Author: Sukul Bagai & Nihar Rao +// Organization: FOSSEE, IIT Bombay +// Email: toolbox@scilab.in + +function[dstMat] = imread(matA,varargin) +// This function is used to Read/Load an image from the disk +// +// +// +// Calling Sequence +// image=imread("image_path"); +// image=imread("image_path",options) +// +// Parameters +// image_path: a String which contains the path of the image that is to be read. +// options: an Integer, containing the option for user to specify. See below for details. +// 0 : convert image to the single channel grayscale image. +// 1 : convert image to the 3 channel BGR color image. +// 2 : load 16-bit/32-bit image when the input image has the corresponding depth, otherwise convert it to 8-bit. +// 4 : the image is read in any possible color format. +// 8 : use the gdal driver for loading the image. +// 16 : convert image to the single channel grayscale image and the image size reduced 1/2. +// 17 : convert image to the 3 channel BGR color image and the image size reduced 1/2. +// 32 : convert image to the single channel grayscale image and the image size reduced 1/4. +// 33 : convert image to the 3 channel BGR color image and the image size reduced 1/4. +// 64 : convert image to the single channel grayscale image and the image size reduced 1/8. +// 65 : convert image to the 3 channel BGR color image and the image size reduced 1/8. +// 128 : do not rotate the image according to EXIF's orientation flag. +// +// Description +// This function is used to Read/Load an image from the disk +// +// +// Examples +// Read a image as it is(Unchanged). +// //Calling imread +// image=imread("test.jpg"); +// +// Read image as grayscale +// //Calling imread +// image=imread("test.jpg",0); + + [lhs rhs]=argn(0); + + if lhs>1 + error(msprintf(" Too many output arguments")); + elseif rhs>2 + error(msprintf(" Too many input arguments,maximum number of arguments is 2\n")); + elseif rhs<1 + error(msprintf("the function needs atleast 1 arguments")); + end + if rhs==1 + out = raw_imread(matA); + else + out=raw_imread(matA,varargin(1)); + end + + + channel = size(out) + + for i = 1: channel + dstMat(:,:,i) = (out(i)) + end + +endfunction diff --git a/macros/imread.sci~ b/macros/imread.sci~ new file mode 100644 index 0000000..bfc3aae --- /dev/null +++ b/macros/imread.sci~ @@ -0,0 +1,11 @@ +function[dstMat] = imread(matA) + + out = opencv_imread(matA) + + channel = size(out) + + for i = 1: channel + dstMat(:,:,i) = double(out(i)) + end + +endfunction diff --git a/macros/imresize.bin b/macros/imresize.bin new file mode 100644 index 0000000000000000000000000000000000000000..3506f9ba7aea5f1b9b1e3e11dd51d65642ea67cf GIT binary patch literal 2700 zcmdUx&2H2{5QM!XfN+ROjMlqh*TESYs%j#epZ3Yl?Q~CjZC4-d1ZumUo*dVisDq}@ zEw64KRMj)#y_B8HRS3Q4{24D~ z?BPS)S(w|8{OlXI)3}x$g>`e*bjzO@{C|r-zSCgf!;x6_ziJ=s7czJVs7 z$ebH&=PTueD?I#eCpTj-_hb*lc%r*LLpwR>O>(#v@cirz8XFHx_`!|3z$$$o|EMNy zZ+yDC@8{EYnSN#e$_GyHgC}^*=|S%3u)&|~erUC|%Om3#^C*3@W1rIZJN8-B!|OKl zPeDD_oBO^jttb0)pz_jsN`5hq+&>LUjp=%=WQT3n%$DtZmPl(Jk2Rn-AF;5xethD5 z?ux^Wv*g|8v;3%Wo8<7+eMB!^5ugjbcz$wgxRkK8wYj!^=_JWL)~}@Tn11x-UH^>K Ng?98YV+_r?{{vsr((M2M literal 0 HcmV?d00001 diff --git a/macros/imresize.sci b/macros/imresize.sci new file mode 100644 index 0000000..0ae3438 --- /dev/null +++ b/macros/imresize.sci @@ -0,0 +1,41 @@ +// Copyright (C) 2015 - IIT Bombay - FOSSEE +// +// This file must be used under the terms of the CeCILL. +// This source file is licensed as described in the file COPYING, which +// you should have received as part of this distribution. The terms +// are also available at +// http://www.cecill.info/licences/Licence_CeCILL_V2-en.txt +// Author: Nihar Rao +// Organization: FOSSEE, IIT Bombay +// Email: toolbox@scilab.in + +function [out]=imresize(image,alpha,beta) +// This function is used to resize the image +// +// Calling Sequence +// +// newImage=imresize(inputImage,alpha,beta); +// +// Parameters +// +// newImage: the new resized image +// inputImage: the image which should be resized. +// alpha: new number of rows. +// beta: new number of columns. +// +// Description +// +// This function is used to resize the image +// +// Examples +// +// z=imread("lena.jpeg",0); +// zz=imresize(z,35,12); +// imshow(zz) + image1=mattolist(image); + a=raw_imresize(image1,alpha,beta); + dimension=size(a) + for i = 1:dimension + out(:,:,i)=a(i); + end +endfunction; diff --git a/macros/imrotate.sci b/macros/imrotate.sci new file mode 100644 index 0000000..e0893d7 --- /dev/null +++ b/macros/imrotate.sci @@ -0,0 +1,70 @@ +// Copyright (C) 2015 - IIT Bombay - FOSSEE +// +// This file must be used under the terms of the CeCILL. +// This source file is licensed as described in the file COPYING, which +// you should have received as part of this distribution. The terms +// are also available at +// http://www.cecill.info/licences/Licence_CeCILL_V2-en.txt +// Author: Shubham Lohakare, Priyanka Hiranandani +// Organization: FOSSEE, IIT Bombay +// Email: toolbox@scilab.in +// +function [out] = imrotate(srcImg, angle, varargin) +//Rotates an image by the specified angle +// +//Calling Sequence +//outputImage = imrotate(srcImg, angle) +//outputImage = imrotate(srcImg, angle, BoundingBoxType) +// +//Parameters +//srcImg : The input image which is to be rotated +//angle : The angle by which the image is to be rotated +//BoundingBoxType : The type of the bounding box for the image displayed, whether a cropped one or one displaying full image. +// +//Description +//The function rotates the input image in the anticlockwise direction by the angle specified around the centre point of the image. The bounding box determines whether the complete image or a cropped image will be displayed based on the BoundingBoxType i.e. 'loose' will display the complete image and 'crop' will display the cropped image. +// +//Examples +//k = imread("lena.jpeg'); +//p = imrotate(k, 45); +//imshow(p) +// +//Examples +//k = imread("lena.jpeg'); +//p = imrotate(k, 30, 'loose'); +//imshow(p) +// +//Examples +//k = imread("photo.jpg"); +//p = imrotate(k, 60, 'crop'); +//imshow(p) +// +//Authors +//Shubham Lohakare, NITK Surathkal +//Priyanka Hiranandani, NIT Surat +srcMat = mattolist(srcImg) + + [lhs, rhs] = argn(0) + + if rhs > 3 then + error(msprintf("Too many input arguments")) + end + if lhs > 1 then + error(msprintf("Too many output arguments")) + end + + + select rhs + case 2 then + output = raw_imrotate(srcMat,angle) + case 3 then + output = raw_imrotate(srcMat, angle,varargin(1)) + end + + channels = size(output) + for i = 1: channels + out(:,:,i) = (output(i)) + end + out = double(out) + +endfunction diff --git a/macros/imsharpen.sci~ b/macros/imsharpen.sci~ new file mode 100644 index 0000000..4c4a4be --- /dev/null +++ b/macros/imsharpen.sci~ @@ -0,0 +1,18 @@ +function[dstMat] = imsharpen(SrcImg) + + srcMat = mattolist(SrcImg) +// [rows cols channels]=size(SrcImg); +// imgList=list(); +// for i=1:channels +// imgList(i)=SrcImg(:,:,i); +// end +// disp(imgList(i)) +// out = opencv_imsharpen(imgList) + out = opencv_imsharpen(srcMat) + [rows cols channel] = size(out) + + for i = 1: channel + dstMat(:,:,i) = out(i) + end + +endfunction diff --git a/macros/imsubtract.sci b/macros/imsubtract.sci new file mode 100644 index 0000000..abd79a3 --- /dev/null +++ b/macros/imsubtract.sci @@ -0,0 +1,56 @@ +// Copyright (C) 2015 - IIT Bombay - FOSSEE +// +// This file must be used under the terms of the CeCILL. +// This source file is licensed as described in the file COPYING, which +// you should have received as part of this distribution. The terms +// are also available at +// http://www.cecill.info/licences/Licence_CeCILL_V2-en.txt +// Author: Tess Zacharias, Shubham Lohakare +// Organization: FOSSEE, IIT Bombay +// Email: toolbox@scilab.in +// +function [out] = imsubtract(srcImg1, srcImg2) +//Subtract the contents of 2 matrices or images and store it inn another +// +//Calling Sequence +//outputMat = imsubtract(input1, input2) +// +//Parameters +//input1 : First input matrix or an image +//input2 : Second input matrix or image +// +//Description +//p=imsubtract(a,b) subtracts each of the element in the first argument's array with the corrresponding element in the second argument's array and the answer is stored in p. +// +//Examples +//a = imread("lena.jpeg"); +//k = imsubtract(a,50); +//imshow(k) +// +//Examples +//a = imread("lena.jpeg"); +//b = imread("lena1.jpeg"): +//k = imsubtract(a,b); +//imshow(k) +// +//Examples +//a = [19 20 21;23 54 11]; +//b = [9 10 11;3 34 -9]; +//c = imsubtract(a,b); +//disp(c) +// +//Authors +//Tess Zacharias +//Shubham Lohakare + srcMat1=mattolist(srcImg1) + srcMat2=mattolist(srcImg2) + + output = raw_imsubtract(srcMat1, srcMat2) + channels = size(output) + + for i = 1: channels + out(:,:,i)= (output(i)) + end + out=double(out) + +endfunction diff --git a/macros/ind2gray.sci b/macros/ind2gray.sci new file mode 100644 index 0000000..8869d81 --- /dev/null +++ b/macros/ind2gray.sci @@ -0,0 +1,11 @@ +function [output] = ind2gray(srcImg,choice) + srcMat = mattolist(srcImg) + + out = raw_ind2gray(srcMat,choice) + + channel = size(out) + + for i = 1: channel + output(:,:,i) = out(i) + end +endfunction diff --git a/macros/ind2rgb.sci b/macros/ind2rgb.sci new file mode 100644 index 0000000..c7208a2 --- /dev/null +++ b/macros/ind2rgb.sci @@ -0,0 +1,11 @@ +function [output] = ind2rgb(srcImg,choice) + srcMat = mattolist(srcImg) + + out = raw_ind2rgb(srcMat,choice) + + channel = size(out) + + for i = 1: channel + output(:,:,i) = out(i) + end +endfunction diff --git a/macros/indexImages.bin b/macros/indexImages.bin new file mode 100644 index 0000000000000000000000000000000000000000..a129b2391cf2e3371cff3eb72be7674f008fd895 GIT binary patch literal 7548 zcmdVfTW^$A6b9hIV=c6lN)I>`3V~QTh*pJ|NN7UTTW`Jgio`2_k5~Q#|Av3T3zZr* zBm@<`QgJ=)_qKb+nbIl6geEKBp1n@*de_=}hL8EBnb~vq7pCWCPp`FqGreB#NXh(S zsqQb9QL9~Bdu~fNw>i5qxbM^1>Hc(oZhmQ4bNl69?|Av0EqSA4t>o^bM~_a_bH3zs zx5ws8$x_L&l9dwrCy{B(T8S38??CBa+E zoptOV7IyI$I*Gr0;%$~*oYzX!W1X6;6Z>|p*$2Zg?)w#I7#G|1#%Ea1XE=`9@g8pA z3`YFDTO#h!lJNF(#ewtJu9k4Ep71Yje19oBHgc;m``>r_xC$5V)H)*XrIO1f;iZ;4 zYna&l)Wwmz&6EDyhbJ*^)|wv~SND}pub*Zt{e*wq{IQdxjSEj^4Fv3=CpuoDA*c5sT%)*k)!60>-!p2NJf`Epj+!NQjRpXDny{Pr`SxMXvqB(?rl zw)VrTT7tv;i36Wl)^xBExzrgx;NUOT`4W2h_**-F`kgpp$({NAvexWkD~|h<-Ck$% zUd5GT+$;s_|H-Q!s3ZM_FWjn2-Sq17nJ#yQeVnohzr(fBWjzfqFe`@GgL5ZpU6>~YLCXDzvWUj|pcSJ=a*SGoU2`N`pY zNpMLWVZfB7U+l#Aaw)#Vl51fUc=-9$yAJ*`iI!B#x zwa~X5$PrxOQ;uM>9*v^IG2S&jU|1-nZnmrH^_ zzcpL@*GnHh;S)oD@*Gtc`*363)^ejhi@)AIaVaj0Y{ktpXG#6`aX*|7W*Ggs^QTJW z7_RMN?X`7Tn=iS=Y%#U_`~Ce6Bi!oP4^PARu5}n%jHx*oacU3$&VbM6vc*11KW^qH z#hm$Q`5CUG;Oxwk-ooZLEL`}>ci4V@i$3l*ry|(3XMw};`c3h)*Y9}x z*dD3c_Tql3;{u27fN-Dtvc2>07v6p-d*{r|nX{Y?ajY}ntF>n19t{8Pq{R8L?B&w$ z^q$ULkUPnKd|M1`N{pFMSV5_Himcu?@T(iZCxq)Tz^r`;*(#rAhk>@B*;pQ{j z?=Sab*gVJi$j4V7rkBR|0T226^yD^nb%r0g=NCu6Yx}FX;=65A@9H*ZR_-p{J8`;s zFSj3j+wlkelqhy);p@M*=gr=^5`B|*+#Chl?mYB1*e@>6oLN|I2<(<{(r2E{1pXTT zE!}$Uv7@_C3%&N9BYX{>p$E6vj(aCLjvGElr{^|T`e%+IbiN^UoKM^D@*VI=wH0;? zr#XFC1*pwhzQ>&__2Fcfj|aCd)@SvV^3c?|=7G-|lt*Pl|IKm;0?nt-~|b_G+?PrZztAYH_Y7spT-{axljBc{<2!_xI?% z-i5ChYVDjIoUgf!Ps(5Kua->0m%cr&_lLp9V2r7)JL<4G#bY@2d@@c?ZrrIDIK5Uf z38#a#9_(%$jB&6T9E@==&Ie=6J(a%cRr==MeX_nSZ+uZP^zH4EN&5CIorS~b%V3O? pPo=l|ncmiaO-|g~a@qQOtHA21f4}Q#{=V&g%lS8t{m5tC`d^7a_09kQ literal 0 HcmV?d00001 diff --git a/macros/indexImages.sci b/macros/indexImages.sci new file mode 100644 index 0000000..928ad28 --- /dev/null +++ b/macros/indexImages.sci @@ -0,0 +1,66 @@ +// Copyright (C) 2015 - IIT Bombay - FOSSEE +// +// This file must be used under the terms of the CeCILL. +// This source file is licensed as described in the file COPYING, which +// you should have received as part of this distribution. The terms +// are also available at +// http://www.cecill.info/licences/Licence_CeCILL_V2-en.txt +// Author: Rohit Suri ,Umang Agarwal & Sridhar Reddy +// Organization: FOSSEE, IIT Bombay +// Email: toolbox@scilab.in + + +function [imageIndex]=indexImages(imgSet,varargin) +// This function creates image search index +// +// Calling Sequence +// imageIndex = indexImages(imgSet, bagOfFeatures, Name, Value... ); +// +// Parameters +// imgSet: Collection of images with their location and labels +// bagOfFeatures: Bag of Visual Words +// Verbose [Optional Input Argument]: Enable Progress display to Screen +// SaveFeatureLocations [Optional Input Argument]: A boolean value indicating whether feature locations has to be saved or not. Values: [True(default)|False] +// imageIndex: Search Index Object containing the mapping of visual vocabulary to each image in the image set +// +// Description +// Creates a search Index Object that has been mapped to visual words that can be used for retrieve Images +// +// Examples +// imgSet = imageSet(directory,'recursive'); +// [trainingSet testSet] = partition(imgSet,[0.8]); +// bag = bagOfFeatures(trainingSet); +// imageindex = indexImages(trainingSet, bag); +// +// With Optional Arguments: +// imageindex = indexImages(trainingSet, bag, "Verbose", 1); +// +// Authors +// Umang Agrawal +// Rohit Suri +// Sridhar Reddy + + [lhs rhs]=argn(0); + if rhs>6 + error(msprintf(" Too many input arguments")); + end + imgSetList=imageSetToList(imgSet); + if modulo(lhs,2)==0 + bagList=bagStructToList(varargin(1)); + select rhs + case 1 then + [imageIndexList]=raw_indexImages(imgSetList); + case 2 then + [imageIndexList]=raw_indexImages(imgSetList,bagList); + case 3 then + [imageIndexList]=raw_indexImages(imgSetList,varargin(1),varargin(2)); + case 4 then + [imageIndexList]=raw_indexImages(imgSetList,bagList,varargin(2),varargin(3)); + case 5 then + [imageIndexList]=raw_indexImages(imgSetList,varargin(1),varargin(2),varargin(3),varargin(4)); + case 6 then + [imageIndexList]=raw_indexImages(imgSetList,bagList,varargin(2),varargin(3),varargin(4),varargin(5)); + end + end + +endfunction diff --git a/macros/indexImages.sci~ b/macros/indexImages.sci~ new file mode 100644 index 0000000..567a90d --- /dev/null +++ b/macros/indexImages.sci~ @@ -0,0 +1,53 @@ +function [imageIndex]=indexImages(imgSet,varargin) +// This function creates image search index +// +// Calling Sequence +// imageIndex = indexImages(imgSet, bagOfFeatures, Name, Value... ); +// +// Parameters +// imgSet: Collection of images with their location and labels +// bagOfFeatures: Bag of Visual Words +// Verbose [Optional Input Argument]: Enable Progress display to Screen +// SaveFeatureLocations [Optional Input Argument]: A boolean value indicating whether feature locations has to be saved or not. Values: [True(default)|False] +// imageIndex: Search Index Object containing the mapping of visual vocabulary to each image in the image set +// +// Description +// Creates a search Index Object that has been mapped to visual words that can be used for retrieve Images +// +// Examples +// imgSet = imageSet(directory,'recursive'); +// [trainingSet testSet] = partition(imgSet,[0.8]); +// bag = bagOfFeatures(trainingSet); +// imageindex = indexImages(trainingSet, bag); +// +// With Optional Arguments: +// imageindex = indexImages(trainingSet, bag, "Verbose", 1); +// +// Authors +// Umang Agrawal +// Rohit Suri +// Sridhar Reddy + + [lhs rhs]=argn(0); + if rhs>6 + error(msprintf(" Too many input arguments")); + end + imageSetList=imageSetStructToList(imageSet); + if modulo(lhs,2)==0 + bagList=bagStructToList(varargin(1)); + select rhs + case 1 then + [imageIndexList]=opencv_indexImages(imgSetList); + case 2 then + [imageIndexList]=opencv_indexImages(imgSetList,bagList); + case 3 then + [imageIndexList]=opencv_indexImages(imgSetList,varargin(1),varargin(2)); + case 4 then + [imageIndexList]=opencv_indexImages(imgSetList,bagList,varargin(2),varargin(3)); + case 5 then + [imageIndexList]=opencv_indexImages(imgSetList,varargin(1),varargin(2),varargin(3),varargin(4)); + case 6 then + [imageIndexList]=opencv_indexImages(imgSetList,bagList,varargin(2),varargin(3),varargin(4),varargin(5)); + end + +endfunction diff --git a/macros/integralImage.bin b/macros/integralImage.bin new file mode 100644 index 0000000000000000000000000000000000000000..38b5e6ccf91c89d849194e086d2103bc6a486236 GIT binary patch literal 1380 zcma)6!A^uQ5Jio;HY~DD3K*z+P!kWH^<>u1@a{kOAO5C?&3=Fp--8a+N|7d$nRYtu zo7V@rv{_y&vo|Ww?#HoClH>@sZtSPBgu-6P!)*iPXT2Li`TnU5x4H`a`;_B{w6dhut0KIc(+fE5cJ@o2mgk5f4YJPFGBSu*7v15B~7y>;>EyY zw=-{N-p=f9lc>|~rg(;2UIa7P)B6`6=gt{HMZH7z@wy z`TR&@EM(pWCl`)|eZdL%Qvn<6@Wby3Xu<{$4s+HSpM3C!0v!C2ANzie9Y1-_1URfm z3-dSWywS)y#*To!oD&_aK^y)=An%<(9CYy6oP87HL$QeqAE1GK9t!whjvJc!H^w0dcV}ID}exMKS=(Rgm*Tbp&#Iat%Cl)sN)X&awH69%N z@Tm_y!3K|<%+X}||H~a`U)&$=Rp=f3QeEXPIQ_`EG>Nn7Q~E6qZ|RP(?YaDB|BT$d zP<*+H`u;}8FdAJXHE(_s9qTXs;_0vI2=U7G$l~+LKh7dn6CK^Pf1FhvdlJN(x{I*l zdw(e2zYXi4(F5)*Txx$W#DO)|e`^280)4FE{MOl^gks56eAdShuUx-Sjhoaj^q^LPw|zT%?Q_mg?acQd-q=36xY)XRIQ}lqX0w-rqsQ-!)2sf` zqxJK2o~&OwoG^9x=iE9t4NMesDF|3ibkXWNrkz!CL_t>(>HvWF8$K9~+A!V@*syo<*4Y=A^~xHL_V^Rq7`Js}aa6bVZY|fuVU9kZV(q@@ zvT2QsF`I0Wk(=75C-%n2uCdtZuwB`8u{8G)Tk%l)@=1ri+LY@n0h_;OosYKzap;#H z{o1xp{$3y+HjVY)4DJUX2V=e-#&-91wDi*);^6(@N#;LI`#A00v>ycZneM7DXZ*o$ zk>#H)EuUg-otRfEwbQzx%b)i5wDMb7y5`wx%;)9flh~;5+GX1wwavLbsSo)cIewP@ zzl&`?N6x19E*8GUJf6Mk%kjvc+&4!(Q)I^)sC>_iILiBn>6iD9(zjNA#3G06;SX2u z1Y$5(8*JX;VAmnzF->T#P*OG1ev-xw;+5ZTCT@G1o_H z=liVDlNV=9|E$`15%_D3KTrP3@p-wp0-5TkhdeIW+9@Q$cq>r-_thxX7t z(QSP9(--5In@zqa#NvCxeR($+_uhOrc5fDr%pU~&Pu-#ASDqX1={Y{l$;InIe{|-H zE4!I#Ri1$ZM1a;6pk;_BX@@wA(z+4dQ0Vu1_6PjSS)9}d|*OPAcRhcCqU zc|cFRKLqTk)$ZB8`S>!B%U`lL`2^!~sV;6W=ce*a9+&L%qn_yFioX0fcet+ITj}G| zxbp0f?-)mHuxpKf@wZQoZME6{rm>LYUtIcf1v`7!7hAjgm!C5CPj4Ofa!cpZVsUM8 zS|Q^p9Wm2YFZ12$da>8?e^y;Z>`eZ@UE1OIH2i_@% literal 0 HcmV?d00001 diff --git a/macros/matMulDeriv.sci b/macros/matMulDeriv.sci new file mode 100644 index 0000000..02793e5 --- /dev/null +++ b/macros/matMulDeriv.sci @@ -0,0 +1,48 @@ +// Copyright (C) 2015 - IIT Bombay - FOSSEE +// +// This file must be used under the terms of the CeCILL. +// This source file is licensed as described in the file COPYING, which +// you should have received as part of this distribution. The terms +// are also available at +// http://www.cecill.info/licences/Licence_CeCILL_V2-en.txt +// Author: Nihar Rao +// Organization: FOSSEE, IIT Bombay +// Email: toolbox@scilab.in +function [DA,DB]= matMulDeriv(A,B) +// this function Computes partial derivatives of the matrix product for each multiplied matrix +// +// Calling Sequence +// [da db]=matMulDeriv(A,B); +// +// Parameters +// A First multiplied matrix. +// B Second multiplied matrix. +// da First output derivative matrix d(A*B)/dA of size (A.rows * B.cols)x(A.rows * A.cols) and same type as A. +// db Second output derivative matrix d(A*B)/dB of size (A.rows * B.cols)x(B.rows * B.cols) and same type as A. +// +// Description +// this function Computes partial derivatives of the matrix product for each multiplied matrix +// Examples +// +// Declare mattrices +//a=[1 2 ;3 4]; +//b=[1 2 ;3 4]; +// //call function +//[da db]=matMulDeriv(a,b); +// //view output +//da +//db + [lhs rhs]=argn(0); + + if lhs>2 + error(msprintf(" Too many output arguments,maximum number of output arguments is 2")); + elseif rhs>2 + error(msprintf(" Too many input arguments,maximum number of arguments is 2`")); + elseif rhs<2 + error(msprintf("the function needs atleast 2 arguments")); + end + + [DA,DB]=raw_matMulDeriv(A,B); + + +endfunction diff --git a/macros/mattolist.sci~ b/macros/mattolist.sci~ new file mode 100644 index 0000000..77a6b2c --- /dev/null +++ b/macros/mattolist.sci~ @@ -0,0 +1,9 @@ +function [imgList]=mattolist(imgMat) + [rows cols channels]=size(imgMat); + imgList=list(); + for i=1:channels + imgList($+1)=imgMat(:,:,i); + disp(imgList(i)) + end + +endfunction diff --git a/macros/multiDenoise.sci b/macros/multiDenoise.sci new file mode 100644 index 0000000..c50dfd4 --- /dev/null +++ b/macros/multiDenoise.sci @@ -0,0 +1,104 @@ +// Copyright (C) 2015 - IIT Bombay - FOSSEE +// +// This file must be used under the terms of the CeCILL. +// This source file is licensed as described in the file COPYING, which +// you should have received as part of this distribution. The terms +// are also available at +// http://www.cecill.info/licences/Licence_CeCILL_V2-en.txt +// Author: Shubham Lohakare, Ashish Manatosh Barik +// Organization: FOSSEE, IIT Bombay +// Email: toolbox@scilab.in +// +function [denoise] = multiDenoise(imgToDenoiseIndex, temporalWindowSize, filterStrength, templateWindowSize, searchWindowSize, n,choice, varargin) +// Removes gaussian white noise from an image taking reference images of the same captured in small intervals +// +// Calling Sequence +// out = multiDenoise(imgToDenoiseIndex, temporalWindowSize, filterStrength, templateWindowSize, searchWindowSize, n, choice, srcImg1, srcImg2, srcImg3) +// out = multiDenoise(imgToDenoiseIndex, temporalWindowSize, filterStrength, templateWindowSize, searchWindowSize, n, choice, srcImg1, srcImg2, srcImg3, srcImg4) +// out = multiDenoise(imgToDenoiseIndex, temporalWindowSize, filterStrength, templateWindowSize, searchWindowSize, n, choice, srcImg1, srcImg2, srcImg3, srcImg4, srcImg5) +// +// Parameters +// imgToDenoiseIndex : Target image to denoise index in srcImgs sequence +// temporalWindowSize : Number of surrounding images to use for target image denoising. Should be odd. +// filterStrength : Parameter regulating filter strength. Bigger h value perfectly removes noise but also removes image details, smaller h value preserves details but also preserves some noise. +// templateWindowSize : Size in pixels of the template patch that is used to compute weights. Should be odd. +// searchWindowSize : Size in pixels of the window that is used to compute weighted average for given pixel. Should be odd. +// n : number of images passed. +// choice : chooses which type of method to use +// srcImgs : The input images which are passed. They are variable arguments. +// +// Description +// Modification of fastNlMeansDenoising function for images sequence where consequtive images have been captured in small period of time. It removes gaussian white noise.The output is a denoised image +// +// Examples +// a= imread("img1.jpg"); +// b= imread("img2.jpg"); +// c= imread("img3.jpg"); +// imgToDenoiseIndex=1; +// temporalWindowSize =1; +// templateWindowSize =7; +// searchWindowSize =21; +// filterStrength = 10; +// n = 3; +// choice = 1; +// k=multiDenoise(imgToDenoiseIndex,temporalWindowSize,filterStrength,templateWindowSize,searchWindowSize,n,choice,a,b,c); +// +// Examples +// a= imread("img1.jpg"); +// b= imread("img2.jpg"); +// c= imread("img3.jpg"); +// d= imread("img4.jpg"); +// imgToDenoiseIndex=1; +// temporalWindowSize =1; +// templateWindowSize =7; +// searchWindowSize =21; +// filterStrength = 100; +// n = 4; +// choice = 1; +// k=multiDenoise(imgToDenoiseIndex,temporalWindowSize,filterStrength,templateWindowSize,searchWindowSize,n,choice,a,b,c,d); +// +// Examples +// a= imread("pic.jpeg"); +// b= imread("pic1.jpeg"); +// c= imread("pic2.jpeg"); +// d= imread("pic3.jpeg"); +// e= imread("pic4.jpeg"); +// imgToDenoiseIndex=3; +// temporalWindowSize =3; +// templateWindowSize =7; +// searchWindowSize =21; +// filterStrength = 75; +// n = 5; +// choice = 2; +// k=multiDenoise(imgToDenoiseIndex,temporalWindowSize,filterStrength,templateWindowSize,searchWindowSize,n,choice,a,b,c,d,e); +// +// Authors +// Shubham Lohakare, NITK Surathkal +// Ashish Mantosh, NIT Rourkela + [lhs, rhs] = argn(0) + + select rhs + case 10 then + for i = 1:n + varargin(i) = mattolist(varargin(i)) + end + out = raw_multiDenoise(imgToDenoiseIndex, temporalWindowSize, filterStrength, templateWindowSize, searchWindowSize, n, choice, varargin(1), varargin(2), varargin(3)) + case 11 then + for i = 1:n + varargin(i) = mattolist(varargin(i)) + end + out = raw_multiDenoise(imgToDenoiseIndex, temporalWindowSize, filterStrength, templateWindowSize, searchWindowSize, n, choice, varargin(1), varargin(2), varargin(3), varargin(4)) + case 12 then + for i = 1:n + varargin(i) = mattolist(varargin(i)) + end + out = raw_multiDenoise(imgToDenoiseIndex, temporalWindowSize, filterStrength, templateWindowSize, searchWindowSize, n, choice, varargin(1), varargin(2), varargin(3), varargin(4), varargin(5)) + end + + channel = size(out) + + for i= 1: channel + denoise(:,:,i) = (out(i)) + end + +endfunction diff --git a/macros/multiDenoiseColor.sci b/macros/multiDenoiseColor.sci new file mode 100644 index 0000000..34b04ba --- /dev/null +++ b/macros/multiDenoiseColor.sci @@ -0,0 +1,106 @@ +// Copyright (C) 2015 - IIT Bombay - FOSSEE +// +// This file must be used under the terms of the CeCILL. +// This source file is licensed as described in the file COPYING, which +// you should have received as part of this distribution. The terms +// are also available at +// http://www.cecill.info/licences/Licence_CeCILL_V2-en.txt +// Author: Shubham Lohakare, Ashish Manatosh Barik +// Organization: FOSSEE, IIT Bombay +// Email: toolbox@scilab.in +// +function [denoise] = multiDenoiseColor(imgToDenoiseIndex, temporalWindowSize, filterStrength, filterStrengthColor, templateWindowSize, searchWindowSize, n,varargin) +// Removes colored noise from an image taking reference images of the same captured in small intervals +// +// Calling Sequence +// out = multiDenoiseColor(imgToDenoiseIndex, temporalWindowSize, filterStrength, filterStrengthColor,templateWindowSize, searchWindowSize, n, srcImg1, srcImg2, srcImg3) +// out = multiDenoiseColor(imgToDenoiseIndex, temporalWindowSize, filterStrength,filterStrengthColor, templateWindowSize, searchWindowSize, n, srcImg1, srcImg2, srcImg3,srcImg4) +// out = multiDenoiseColor(imgToDenoiseIndex, temporalWindowSize, filterStrength,filterStrengthColor, templateWindowSize, searchWindowSize, n,srcImg1, srcImg2, srcImg3,srcImg4,srcImg5) +// +// Parameters +// imgToDenoiseIndex : Target image to denoise index in srcImgs sequence +// temporalWindowSize : Number of surrounding images to use for target image denoising. Should be odd. +// filterStrength : Parameter regulating filter strength. Bigger h value perfectly removes noise but also removes image details, smaller h value preserves details but also preserves some noise. +// filterStrengthColor : same as filterStrength but for color components of noise. +// templateWindowSize : Size in pixels of the template patch that is used to compute weights. Should be odd. +// searchWindowSize : Size in pixels of the window that is used to compute weighted average for given pixel. Should be odd. +// n : number of images passed. +// srcImgs : The input images which are passed. They are variable arguments. +// +// Description +// Modification of denoiseColor function for images sequence where consequtive images have been captured in small period of time. It removes colored noise.The output is a denoised image +// +// Examples +// a= imread("img1.jpg"); +// b= imread("img2.jpg"); +// c= imread("img3.jpg"); +// imgToDenoiseIndex=1; +// temporalWindowSize =1; +// templateWindowSize =7; +// searchWindowSize =21; +// filterStrength = 10; +// filterStrengthColor = 10; +// n = 3; +// k=multiDenoiseColor(imgToDenoiseIndex,temporalWindowSize,filterStrength,filterStrengthColor,templateWindowSize,searchWindowSize,n,a,b,c); +// +// Examples +// a= imread("img1.jpg"); +// b= imread("img2.jpg"); +// c= imread("img3.jpg"); +// d= imread("img4.jpg"); +// imgToDenoiseIndex=1; +// temporalWindowSize =1; +// templateWindowSize =7; +// searchWindowSize =21; +// filterStrength = 100; +//filterStrengthColor=30; +// n = 4; +// choice = 1; +// k=multiDenoiseColor(imgToDenoiseIndex,temporalWindowSize,filterStrength,filterStrengthColor,templateWindowSize,searchWindowSize,n,a,b,c,d); +// +// Examples +// a= imread("pic.jpeg"); +// b= imread("pic1.jpeg"); +// c= imread("pic2.jpeg"); +// d= imread("pic3.jpeg"); +// e= imread("pic4.jpeg"); +// imgToDenoiseIndex=3; +// temporalWindowSize =3; +// templateWindowSize =7; +// searchWindowSize =21; +// filterStrength = 75; +//filterStrengthColor = 50; +// n = 5; +// choice = 2; +// k=multiDenoiseColor(imgToDenoiseIndex,temporalWindowSize,filterStrength,filterStrengthColor,templateWindowSize,searchWindowSize,n,a,b,c,d,e); +// +// Authors +// Shubham Lohakare, NITK Surathkal +// Ashish Mantosh, NIT Rourkela + [lhs, rhs] = argn(0) + + select rhs + case 10 then + for i = 1:n + varargin(i) = mattolist(varargin(i)) + end + out = raw_multiDenoiseColor(imgToDenoiseIndex, temporalWindowSize, filterStrength, templateWindowSize, searchWindowSize, n,varargin(1), varargin(2), varargin(3)) + case 11 then + for i = 1:n + varargin(i) = mattolist(varargin(i)) + end + out = raw_multiDenoiseColor(imgToDenoiseIndex, temporalWindowSize, filterStrength, templateWindowSize, searchWindowSize, n, varargin(1), varargin(2), varargin(3), varargin(4)) + case 12 then + for i = 1:n + varargin(i) = mattolist(varargin(i)) + end + out = raw_multiDenoiseColor(imgToDenoiseIndex, temporalWindowSize, filterStrength, templateWindowSize, searchWindowSize, n,varargin(1), varargin(2), varargin(3), varargin(4), varargin(5)) + end + + channel = size(out) + + for i= 1: channel + denoise(:,:,i) = (out(i)) + end + +endfunction diff --git a/macros/pcread.bin b/macros/pcread.bin new file mode 100644 index 0000000000000000000000000000000000000000..e62e48f824a6243cde17df26dde8a8e8489d8e31 GIT binary patch literal 2956 zcmds(!HU#C5Qd|o?q)ODNg$KNPKMp=A_IF8_NL&?2k;fV_@1791a-l~vIy$Iqd5NG zn8MIWXNNtB14XC1s{XG2tGa9I#HI0KGx{x}D7q)9tGsMS+RX-CUe@dO`moJB{rme- zbSynmNFGV-Csh=?W$C%>roXn^Ew~RQ4W^@+Mf$ZLCBk=hx zCG0Whi{0Nde1A!NFC_R8?<)y7tlOD6H+wvh5Zq^-ttIx68y1mB*e37YNw1H`y@?qOYHch&Q;EL&^+YBe)y7)xD4k5E{xx~yvb~q z-?u%^V~sw)F#}#rR>7N_)3y+2n2KsnIQ@NxgNZ=+26Kl}|Jzblr^ZbVlcvM-#jK*)L1; 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+ + + + + + + +endfunction diff --git a/macros/pyrMeanShiftFiltering.sci~ b/macros/pyrMeanShiftFiltering.sci~ new file mode 100644 index 0000000..02d6e7e --- /dev/null +++ b/macros/pyrMeanShiftFiltering.sci~ @@ -0,0 +1,8 @@ +function [outputImg]=pyrMeanShiftFiltering(inputImage,sp,sr) + inputList=mattolist(inputImage); + outputList=opencv_pyrMeanShiftFiltering(inputList,sp,sr); + end + for i=1:size(outputList) + outputImg(:,:,i)=outputList(i) + end +endfunction diff --git a/macros/rectifyStereoImages.sci~ b/macros/rectifyStereoImages.sci~ new file mode 100644 index 0000000..2cd9c54 --- /dev/null +++ b/macros/rectifyStereoImages.sci~ @@ -0,0 +1,59 @@ +function [out]=rectifyStereoImages(input_image1,cameramatrix1,Distortion_coff1,input_image2,cameramatrix2,Distortioncoff2,Translationvector,Rotationvector) +// Rectify the pair of image taken by stereo camera +// +// Calling Sequence +// [left_image,right_image] = rectifyStereoImages (input_image1,cameramatrix1,Distortion_coff1,input_image2,cameramatrix2,Distortioncoff2,Translationvector,Rotationvector) +// left_image = rectified input_image1 +// right_image = rectified input_image2 +// +// Parameters +// +// input_image1 : First Stereo image on which rectification has to be performed +// Cameramatrix1 : An input matrix of 3*3 +// Distortion_coff1 : A vector of size 4 ,5 or 8 +// input_image2 : Second Stereo image on which rectification has to be performed +// Cameramatrix2 : An input matrix of 3*3 +// Distortion_coff2 : A vector of size 4 ,5 or 8 +// Translationvector : A vector of size 3 +// Rotationvector : An input matrix of 3*3 +// left_image : rectified input_image1 +// right_image : rectfied input_image2 +// +// Description +// This function first undistorted and then rectified the both image1 and image2.It uses camera parameters,respective rotation,translation of both camera. +// +// Examples +// a = imread('lena.jpeg') +// cameramatrix1 = [1 0 1;0 1 1;0 0 1]; +// Distortion_coff1 = [200 200 400 300]; +// b = imread('lena.jpeg') +// cameramatrix2 = [2 0 1;0 1 1;0 0 1]; +// Distortion_coff2 = [205 240 410 370]; +// Translationvector = [1 2 3]; +// Rotationvector = [0 0 2;1 4 5;6 7 8]; +// [left_image,right_image] = rectifyStereoImages(a,cameramatrix1,Distortion_coff1,b,cameramatrix2,Distortioncoff2,Translationvector,Rotationvector); +// imshow(left_image); +// imshow(right_image); +// +// Authors. +// +//Diwakar Bhardwaj + + input_image3=mattolist(input_image1); + input_image4=mattolist(input_image2); + [left_image right_image]=rectifyStereoImages(input_image3,cameramatrix1,Distortion_coff1,input_image4,cameramatrix2,Distortioncoff2,Translationvector,Rotationvector); + + dimension1=size(left_image) + for i = 1:dimension1 + left_out(:,:,i)=left_image(i); + end + + dimension2=size(right_image) + for j = 1:dimension2 + right_out(:,:,j)=right_image(j); + end + + + out=struct("left_rectifyimage",left_out,"right_rectifyimage",right_out); + +endfunction;* diff --git a/macros/stereoCalibrate.bin b/macros/stereoCalibrate.bin new file mode 100644 index 0000000000000000000000000000000000000000..11db6eb8815b2d27f7cb9872057d5a7ef9250560 GIT binary patch literal 14424 zcmeI(-ELh+6$fy)e7R2QxXzcuvD+lH5Yi}ZU1%>rBE3Y2R(uJSUUE~Zx4q;QxZweK z3!Z|fs6ayEqC!w{1(@}-_y2g#&fYucm^cl!EiLWYGi%nY_5ZImGdn%q-P@dP?tJ## z)$I$jjlIn~`FnnCZS9$o8ymBYYrE+^etx;eb}n4rytsE`XZ!lzg2wi>jjhe2?q`l? z+_}^AKil@dRBOz(wy(E++Mkvamuj7tO5Q2CQ?gg`LdkZ?ZizlRFP2;{xmZHS_)dvF zI)6DhIM}S`tc1QX?Q12m<7sa6Jn5Ow?ncSg61Fdtn6GbWy>^Y(Z#Ls|Vi1r1+uhSR zzpRZ1W7d7MBzRPF-ZtNy&nm|F7(d0o)s6qT!{F=n4lj0tnf8$F2i4E^7&iM8W34|! zm|64NCE|qVj2aQV2}XB7+h zr3T;*@8thqyS&4XKHS_Y3GQ-OUvfxZ;FS&75@XR{bsb#sZ`pN*xUK1Pp5-E*?HTeb zaVG9|kKlLmW51i1ID?U=c<*)NY_hK&gPD3v-W$_4CwXrU487->x;CcXiMecMPl+u$ z@jvkx8;Y@w>5bB%$Cp)Vv>z)QaL19hHQ>V6*oUJwUxNi)5?}O&{4h3F|Lwl{TItb+ z;VSz_Kc4Kb;X1x0hE?n@Ggoc=uW`Wt^NxcLZ5;ROUHteS%F(I4C9#anWj7qB&hTPy z>SK;KV``)2bj)@e!@HfmW%nOk#`pdlb;bw&@+W&hF!HW$_#2=3NLPRM3o$&77}-sY zvT0x8gSu1$sb@85eQUZKzE&d6_#h^2ea7gt80s@VhWA(=v^hOCm)&LaK#byGE7&K- zG5c*C@6|l(^?4mT^IHG=bF6<_xp2}rpHx0n=<{> zyTM=D?^K%|y7Jguw)D}F)9Q!qzCAi$OgQeQ!Q~1Xzu6$pp6e? zyY-rh-ZIH!JIFP}+Uf9@^v7oW-Bq4lQrX!F!Fd~%Lvp9+3$owEfn+>tO8ulpH;+{7-G;FSTgR^ZVXWPM>5?8N<|Bnmy!R$3IP>28H*g=R)zi#Ng>d-yy8;Tf@0Gxfte3p`?}G#N=5O^{J>qb`=7z&x zb#{JIPiw%}*w}AH|5f{F4Ik<>zYksb-ROwU!f!}ho!Q3Cmv;w#*J?k*YtAFTL2wS> z+|z#c(8k&Ahc&cz{Oj0eldPt(=NG%?Z^kap-xeFjE-ZG<-;8a{-xeFjV7oeBTZc8* z^7T^w4OigP@NbI-HI`IUz_|4m^acYaawdDQ6R;C#`> z+Jn=`8@ZCakuzs2Z+0Hao8J}&^5&N%XE|>cb8r1ra!;-$_uT!?R_+~r1GMMV?+XLD z_kPKF?iC1!e<#bm#r)kmmHd^n$zS)(|L6QY!g_7(llq4-Iru?|9Bc)q?v}noi0_7c ztNRA@p8t;M-M5|Z$b5s3-Su*>W!txmZy0m)t>U|qJ$G3B-s!FS??v%r>^|E1!G}l1 z$e%V&=QA0*3%B-9GtT%ic3*G($oD%;#e>5>&f#<@-m&k6b`9UN{_P?;B6i%$r=j&e zDP4Z$dpG=xYwX)4>(SZWo4t5(Z}EG=o4YlesaYJ$32}M)HX8eX0c&Vp3%~B#{{?wa B*PQ?W literal 0 HcmV?d00001 diff --git a/macros/stereoCalibrate.sci b/macros/stereoCalibrate.sci new file mode 100644 index 0000000..502cc10 --- /dev/null +++ b/macros/stereoCalibrate.sci @@ -0,0 +1,107 @@ +// Copyright (C) 2015 - IIT Bombay - FOSSEE +// +// This file must be used under the terms of the CeCILL. +// This source file is licensed as described in the file COPYING, which +// you should have received as part of this distribution. The terms +// are also available at +// http://www.cecill.info/licences/Licence_CeCILL_V2-en.txt +// Author: Nihar Rao +// Organization: FOSSEE, IIT Bombay +// Email: toolbox@scilab.in + +function [params]=stereoCalibrate(objectpoints,imagepoints1,imagepoints2,varargin) +// this function Performs stereo calibration for the fisheye model. +// +// Calling Sequence +// +// stereo=stereoCalibrate(objectpoints,imagepoints1,imagepoints2); +// stereo=stereoCalibrate(objectpoints,imagepoints1,imagepoints2,cameraMatrix1,distCoeffs1,cameraMatrix2,distCoeffs2); +// +// Parameters +// stereo: a Struct containing all the camera Params +// objectpoints: a 2d set of actual object points. +// imagepoints1: a list of imagepoints of image1. +// imagepoints2: a list of imagepoints of image2. +// cameraMatrix1: camera matrix of first camera. +// distCoeffs1: distortion coefficients of first camera.it should be 4*1 or 1*4. +// cameraMatrix2: camera matrix of second camera. +// distCoeffs2: distortion coefficients of second camera.it should be 4*1 or 1*4. +// +// Description +// +// this function Performs stereo calibration for the fisheye model. +// +// Examples +// // A example to show calibration, using the traditional chessboard/checkerboard example. +// +// //generate checkerboardpoints for calibration +// yo=genCheckerboardPoints([7 10],8); +// //read first image +// z=imread("left1.jpg",0); +// //read second image +// image=imread("right1.jpg",0); +// //detect checkerboardpoints for image 1 +// ii=detectCheckerboardCorner(z,[7 10]); +// //detect checkerboardpoints for image 2 +// ii2=detectCheckerboardCorner(image,[7 10]); +// //convert imagepoints to list +// ii=list(ii); +// ii2=list(ii2); +// // call function +// final=stereoCalibrate(yo,ii,ii2); +// // show the struct +// final +// // use the above calibration further +// uu = undistortImage(image,final.cameraMatrix2); +// imshow(uu); +// +// +// //generate checkerboardpoints for calibration +// yo=genCheckerboardPoints([7 10],8); +// //read first image +// z=imread("left1.jpg",0); +// //read second image +// image=imread("right1.jpg",0); +// //detect checkerboardpoints for image 1 +// ii=detectCheckerboardCorner(z,[7 10]); +// //detect checkerboardpoints for image 2 +// ii2=detectCheckerboardCorner(image,[7 10]); +// //convert imagepoints to list +// ii=list(ii); +// ii2=list(ii2); +// // call function +// final=stereoCalibrate(yo,ii,ii2); +// // show the struct +// final +// // use the above calibration further +// uu = undistortImage(image,final.cameraMatrix2,'distCoeffs',final.distortionCoefficients2); +// imshow(uu); + + + + [lhs rhs]=argn(0); + + if lhs>1 + error(msprintf(" Too many [a b c d e f]put arguments\n")); + elseif rhs>7 + error(msprintf(" Too many input arguments,maximum number of arguments is 7\n")); + elseif rhs<3 + error(msprintf("the function needs atleast 3 arguments\n")); + end + + if rhs==3 + [a b c d e f] =raw_stereoCalibrate(objectpoints,imagepoints1,imagepoints2); + elseif rhs==4 + [a b c d e f]=raw_stereoCalibrate(objectpoints,imagepoints1,imagepoints2,varargin(1)); + elseif rhs==5 + [a b c d e f]=raw_stereoCalibrate(objectpoints,imagepoints1,imagepoints2,varargin(1),varargin(2)); + elseif rhs==6 + [a b c d e f]=raw_stereoCalibrate(objectpoints,imagepoints1,imagepoints2,varargin(1),varargin(2),varargin(3)); + elseif rhs==7 + [a b c d e f]=raw_stereoCalibrate(objectpoints,imagepoints1,imagepoints2,varargin(1),varargin(2),varargin(3),varargin(4)); + end + + + + params=struct('cameraMarix1',a,'distortionCoefficients1',b,'cameraMatrix2',c,'distortionCoefficients2',d,'rotationMatrix',e,'TranslationVector',f); +endfunction diff --git a/macros/trainSVMClassifier.bin b/macros/trainSVMClassifier.bin new file mode 100644 index 0000000000000000000000000000000000000000..5f159078e13f02ae9b089fa0c2d7146b1a6741db GIT binary patch literal 20296 zcmeI(-ELf083ten3M6joIBsGm*lwK=N}2+#+?J{kiHZZ%f>5KXM1aa)IY8nTxCM?l z=LR_77C7OIBklmyNDv|+e##Mu@IB*s<2BoR#xo|<#&|~hwD(@?`+dK6t-WX4v%R^z zwsGh8ci+FTytTDXw>i$J@ zw(sline~k>#@9=Xt(Ne`R{V=4#>F6X<>*L{ zZ@S4NG5AS*HOA+is`(Eke=d2p#$B_$JQR8JsRs6R*#?Wuo8v=n=7OV|=*#s+N%Yvk z$DEp8EJ;7=^uaklY~COGrc1hY$(yfFmdM|^*m7|m-^qbJjNua7)VNz?Vn#I&yTK9^xT;dUAZOBsqVq&gEk+cstL$n%jK;*P8n3?&cJ% z97d<0MN_~IMRZEj*4 zV?zf|^fl`M*QW6~DPMW$ySObD-8#NF)H!Z-gwwEtqqP+Ncd^4&b%(DfvF4jq|8eB& ztbL|${j~l5$_c9-2G+B^+M2+7(qi&PU7sXAjKjouo&)UpxktjS#p}%lUIPwI!pj^C zmrLx&d4_Cp{BDgec(-?N9>=?JI2ylDl4puM+q&QR?%-L^bF+E6cWcZuPK*Ed>w1Cz z2aCU6{IPRS`thO*^{rV zP5$$|`Fx$vvgSTJ)c;Gx$sTH7fkXobP`Q>rY(shkduYS2mMk@SD01%ZDys;yQ;z`%d9XUBiu^=;k{ZeA>C-K^MO5 zdw>^)_W!8d&FLwO_=1nUR_qq5whq481=H^L&E$qx{Lteo`?~uB9pikZ->JoQI2gMe z^`@=GIbY`0Z@zt(ptj(TcXCjloW*Hv<-=ZWtq(eM^(N=t{4(D53#RbrR~|&3>5Vw4 zxy#A)sQr$cI`Te^y|}H;wC@DiP2yVcoP-G+<8uCX_!2RO?QF0u)pe57}MJmrsFe0MpT@peu0^(ffBHS~pJ{EBUER-C)`GqapVq1=iv=qbsOii5A#PI({EPZ>dl(4U#L}`WL9j)`4QtJ;(M#=Ry$mA z3crbS*iO4Q?4Bx~m7Fvj+vl=(3NQ7KTa(@ICh+Z!jl-|IzmAK+{!v}iu(IdNPoC56 z-Cro(&zBUv2Jb@r4eOPX7W>6S&*O-ac_s?rnV-+Y@HpcV8@gFE212 z?5+5d`;dEei*erRStIQ`z~Ft<{lc?=xbB_y_dF}*S*rUi_W!tt*gx`lsZMh3e?+?b z2|bwkE|=#?`^zlv4`Tmr*|8Tz`_Eeod2$^+Zo>ws@q+uEQZ~$sD~KCC`;4&(u8*$M$`XdeqD|81SoCFil)z zZLiqS*H^W-KBs+$1dl!}yY;+UdSay>dBH-C?6VGy=lkVOowI?3T+>gzHO`h@_9N%U z=&O}Z>(90N=>+@Oy5}7B&LA=QaQ@rkMZ1<=r+--o{KK}d-q!Xg{}-c2&Z`?ho<(mB_9G%MTBu)5mi?=&PCS;(oTb*5Rh_ zj_||{m_7>kv$rb`xrG<y`2(v{8;CGwzx+pdtmlaYeC$^ z7bE<0G@kX&FI~2BaGgCVcEoACvO&)vxw+`ge=J9bC!w+og$1(?gDh%Pal%~seY*61Q-R>>V{hSmk}bXc8vgoaeX+N((~qx~@bgAVIDiLYeAc%vZ?0`@pBqJ|A6vPzS=rpY zH2m4rh*@7hx;$Lo7~c;LHZ`Fcqg-!Ih|e5S!Sd*e~Cb+1d$ zuGBeSuG0%S=tZvGOY+Q--pYO2Uee3n;vDYj*YWT1=|PY6E^FwmI@jZGlyrOiOpW1q z`@N42tYJRx-fvD1i01@rB>3}Zjhb`s&mL~xx{cm(TyvHF;Pdk;0;X@4!0U9$WBFSPfaardxRXWVZtTb<42oom}YzXP>@>1FPt z-sgAsukDrf%OjiK@S;=)^~{dZ>VVrVMz5DIesKK5zzEOV`X+o=d;= zIQ{-aozK7DTL=36(~7I#-zr)3yFeIxj@Iu{&aBRbGk6ltcy5?KXLb&7=4TZbXTDRi z;7oxq_@`RzpA*n`@NC{cMF8UXTjZ3{%_5N|2QB1d;c|m{_njjY`<&&y5i#h4@wsN zFAxTw1^*ug|3`i7%w-K(H(5j8YtFic_WHfF^t)&G*1@|qkagf)*jmZ7e e!5;??zMX{SVc+TZ-FKsUwA11 literal 0 HcmV?d00001 diff --git a/macros/trainSVMClassifier.sci b/macros/trainSVMClassifier.sci new file mode 100644 index 0000000..a288163 --- /dev/null +++ b/macros/trainSVMClassifier.sci @@ -0,0 +1,111 @@ +// Copyright (C) 2015 - IIT Bombay - FOSSEE +// +// This file must be used under the terms of the CeCILL. +// This source file is licensed as described in the file COPYING, which +// you should have received as part of this distribution. The terms +// are also available at +// http://www.cecill.info/licences/Licence_CeCILL_V2-en.txt +// Author: Nihar Rao +// Organization: FOSSEE, IIT Bombay +// Email: toolbox@scilab.in +function [classifier]=trainSVMClassifier(imgSet,bag,classifierName,varargin) +// This function is used to train an image classifier using the SVM(Support Vector Machines) Model. +// +// Calling Sequence +// imgSet = imageSet(directory,'recursive'); +// 'or' +// imgSet = imageSet(image); +// bag = bagOfFeatures(imgSet); +// classifier = trainSVMClassifier(imgSets, bag); +// classifier = trainSVMClassifier(imgSets, bag,'nameclass') +// classifier = trainSVMClassifier(imgSets, bag,'nameclass') +// classifier = trainSVMClassifier(imgSets, bag,'nameclass',C) +// classifier = trainSVMClassifier(imgSets, bag,'nameclass',C,coeff) +// classifier = trainSVMClassifier(imgSets, bag,'nameclass',C,coeff,degree) +// classifier = trainSVMClassifier(imgSets, bag,'nameclass',C,coeff,degree,gamma) +// classifier = trainSVMClassifier(imgSets, bag,'nameclass',C,coeff,degree,gamma,kernelType,Nu) +// classifier = trainSVMClassifier(imgSets, bag,'nameclass',C,coeff,degree,gamma,kernelType,Nu,P) +// classifier = trainSVMClassifier(imgSets, bag,'nameclass',C,coeff,degree,gamma,kernelType,Nu,P,setType) +// +// Parameters +// classifier: Image category classifier location +// BagofFeaturesLocation : location of the xml or yml file. +// Description : features obtained after training. +// imgSets: Input imageSet to train the classifier on +// bag: The bagOfFeatures of the imageSet provided +// image: The set of images used for creating the imageset used for training +// nameclass: Name of the classifier one wants for their trained model .xml or .yml file +// C: Parameter C of a SVM optimization problem that should be used to train the model +// coef: Parameter coef0 of a kernel function that should be used to train the model +// degree: Parameter degree of a kernel function that should be used to train the model +// gamma:Parameter γ of a kernel function that should be used to train the model. +// kernelType:Type of a SVM kernel that should be used to train the model.it should be [-1,5]. +// Nu:Parameter ν of a SVM optimization problem that should be used to train the model. +// P: Parameter ϵ of a SVM optimization problem that should be used to train the model. +// type: Type of a SVM formulation that should be used to train the model.it should be [100,104]. +// +// Description +// this function is used to train an image classifier using the SVM(Support Vector Machines) Model. +// +// +// Examples +// //get imageset from 'images2' folder +// image=imageSet('images2','recursive'); +// //get bag of features +// x=bagOfFeatures(image); +// //train thew model and name the saved .yml file as "SVM" +// d=trainSVMClassifier(image,x,"SVM"); +// //read image to get prediction from mthe above trained data +// z=imread("fish.jpg"); +// //finally predict the class using SVM's prediction function for the input image +// resp=predict(d,z,"SVM"); +// +// //get imageset from 'images2' folder +// image=imageSet('images2','recursive'); +// //get bag of features +// x=bagOfFeatures(image); +// //train the model with the given parameters and name the saved .yml file as "SVM" +// d=trainSVMClassifier(image,x,"SVM",1.1,0.2); +// //read image to get prediction from mthe above trained data +// z=imread("fish.jpg"); +// //finally predict the class for the input image +// resp=predict(d,z,"SVM"); + + + + + + //convert to list + bag_list = bagStructToList(bag); + imgSets_list = imageSetToList(imgSet); + [lhs rhs]=argn(0); + + if lhs>1 + error(msprintf(" Too many output arguments")); + elseif rhs>11 + error(msprintf(" Too many input arguments,maximum number of arguments is 11")); + elseif rhs<3 + error(msprintf("the function needs atleast 3 arguments")); + end + if rhs==3 + temp=raw_trainSVMClassifier(imgSets_list, bag_list,classifierName); + elseif rhs==4 + temp=raw_trainSVMClassifier(imgSets_list,bag_list,classifierName,varargin(1)); + elseif rhs==5 + temp=raw_trainSVMClassifier(imgSets_list,bag_list,classifierName,varargin(1),varargin(2)); + elseif rhs==6 + temp=raw_trainSVMClassifier(imgSets_list,bag_list,classifierName,varargin(1),varargin(2),varargin(3)); + elseif rhs==7 + temp=raw_trainSVMClassifier(imgSets_list,bag_list,classifierName,varargin(1),varargin(2),varargin(3),varargin(4)); + elseif rhs==8 + temp=raw_trainSVMClassifier(imgSets_list,bag_list,classifierName,varargin(1),varargin(2),varargin(3),varargin(4),varargin(5)); + elseif rhs==9 + temp=raw_trainSVMClassifier(imgSets_list,bag_list,classifierName,varargin(1),varargin(2),varargin(3),varargin(4),varargin(5),varargin(6)); + elseif rhs==10 + temp=raw_trainSVMClassifier(imgSets_list,bag_list,classifierName,varargin(1),varargin(2),varargin(3),varargin(4),varargin(5),varargin(6),varargin(7)); + elseif rhs==11 + temp=raw_trainSVMClassifier(imgSets_list,bag_list,classifierName,varargin(1),varargin(2),varargin(3),varargin(4),varargin(5),varargin(6),varargin(7),varargin(8)); + end + classifier = struct("ClassifierLocation", temp(2), "BagofFeaturesLocation", temp(3), "Description", temp(4)); + +endfunction diff --git a/macros/trainSVMSGDClassifier.bin b/macros/trainSVMSGDClassifier.bin new file mode 100644 index 0000000000000000000000000000000000000000..1a5a9abed226aae34f027a20bb41a86503ba93ef GIT binary patch literal 19188 zcmeI(O>Z4n83%BOmy$TC^1u9emN`(+Apb7yh6dwmc)bj4l>E+e^i?y;R z>-MRQl|7PYmp7L;SJy7=txRTbtt~B`Ej`cH_)(3kHEzB8?z`veT3bt7-5Q!_YFwys zrp9&+`xk3i!`ITI#k*32pZ4*f&wR7y%Qf&thWpH|Z`821T7xXS^sm>jPKSY(jjrg( zMjJb#gPiE+V`T1>&ws4(*Ba(`YrIqAg`#mE+v&y^-NC^+x%lE2zhe)d(4rxiUUuU% zZ}(eUuGJnMcEOHJ^!)#Hjl`~|_vh@x^Uva8Ct9PA0X<}Wqz0T~M{J7h*nnR=U>M%` zbiLN-3=O@BSxXDg-~uN)=?lKruGIKUjhAb*G;DOAc*|M*=-BvTjoAFbnzP3q-0+!a zpUov$E zBY4tB7TNG>ZKK;79yIc`%~SK#jJ%si{w&+sBnQ~g;u4?U?(mTVU+Cx_XTOr~aD}lt zOKtSAl*e#LE{?zv*`LU zLF+k9jMB?eU;5dfD~5Voo{5BYPs1{$<&Zv3|HpQPtQSmr!(O-;dWp63JnslQq0+bp^VRpSpjFCx#oL;8pu z@?P4vxy_;4zW>baokXu0>Pzx3ISf0wnrHP-)%-9$>XRM)-zvWo54O?~Ibs@p_VT{# z%nOZ}qhm{IXXt$o9e%YEx$?)FT8kgA)ST>pb$vN{?H}~cdZ(+^F&*T_?}O|?%Qkw= z;n059d9Lo^MowtO#2h~DUhqH*-}d{;OLdPY{RoEaCksC9xfQI?#}Bf}45t0}_}C_| z_<%0;i%)K%u})Uv9bep=w|wCjo7R_n2e8k7`|URxzQt~NC+_@XGd=7GFMasg*vdeI z78aTJ?aO)_FPOrg+=Fs8IKx9NCr0h}g7~4XTRkn!yx&^bJ1f`b!32(QAcxI(#5OUG zFJG-S`i5kV`2;U=5~J4EAvx&j5ZCY~&)9)K`6VvqC6gbPeTHFudLMuh8OeaihD0H~9Cl zZgr9wc|$mmotW`~&g4^io_e3v2kjr!3xn~`ik2_I-<4gie53QAZx67a=iGd+dit?s zpEdRked`Z>+sk3fH{VV0$JfLbPg~RaO3n|w_7l(WTN8VEMUEQ4lQ@!*oEfSQ^6*7= zzc#Yo=Iu~!hmsg`JW5P| z-QhBZfB#wcLB+K%S8NvXn&jwM9m;og4Xb&3gB}sS)OyZ}+S-)`_pF_$d0X?ZH8lO6 zr>69zp&Dmja>bk-Y&TD=$K=_!mpXTaNo2UPH?lk<#TGrne)i;f>))BWPfv|qdKaB- zZ^(WAy~_PqTvAKF=;V;gS9b6t?*nwR+d6yErFZJ1aAfP{8u2k04q=QYdJ?|}shiJ> znw;duL9zcqVFfSv&-2Y7as7A2Tn&kT^0cj2ddU^%_WN`{Hf`>jw|R?K&dWLT*qJ)W zx%w!cE#m88Y?AlkJ4#P0_WRE??L7XoB{eIasarbRo+Vy-N9zB_HOFh@T@nu&*3iKk z51C?NKXTBt^l0(&H@4wHkJen>iz~kLG548UmqXU%7+HAfmv`3bFwnBm6 zqCfb%AIrhV@&Cu1>U_LcwdB1BPH+@|xWNZziT%fF4uhAv5v)^hLvcuKLqitK#W!{T za?Qth-&cF~>BWnWZE_{?i+!J{HFQI=u8*vXCpqjB!+C7+-4q=^@X9m!<32g2KiWfg zt;UNrVrTpw!?FD)!yi854F=?j6`P~iS{tj>kGS%^l{xQsp7#Hx(3g1k{duGI*cN}- z1q(c4kvg@WTDn|wJg{JE; 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literal 0 HcmV?d00001 diff --git a/macros/trainSVMSGDClassifier.sci b/macros/trainSVMSGDClassifier.sci new file mode 100644 index 0000000..bb01b27 --- /dev/null +++ b/macros/trainSVMSGDClassifier.sci @@ -0,0 +1,101 @@ +// Copyright (C) 2015 - IIT Bombay - FOSSEE +// +// This file must be used under the terms of the CeCILL. +// This source file is licensed as described in the file COPYING, which +// you should have received as part of this distribution. The terms +// are also available at +// http://www.cecill.info/licences/Licence_CeCILL_V2-en.txt +// Author: Nihar Rao +// Organization: FOSSEE, IIT Bombay +// Email: toolbox@scilab.in + +function [classifier]=trainSVMSGDSGDClassifier(imgSet,bag,classifierName,varargin) +// This function is used to train an image classifier using the SVMSGD(Stochastic Gradient Descent SVM) Model. +// +// Calling Sequence +// imgSet = imageSet(directory,'recursive'); +// 'or' +// imgSet = imageSet(image); +// bag = bagOfFeatures(imgSet); +// classifier = trainSVMSGDClassifier(imgSets, bag);` +// classifier = trainSVMSGDClassifier(imgSets, bag,'nameclass') +// classifier = trainSVMSGDClassifier(imgSets, bag,'nameclass') +// classifier = trainSVMSGDClassifier(imgSets, bag,'nameclass',initialStepSize) +// classifier = trainSVMSGDClassifier(imgSets, bag,'nameclass',initialStepSize,marginReg) +// classifier = trainSVMSGDClassifier(imgSets, bag,'nameclass',initialStepSize,marginReg,marginType) +// classifier = trainSVMSGDClassifier(imgSets, bag,'nameclass',initialStepSize,marginReg,marginType,optimalParams) +// classifier = trainSVMSGDClassifier(imgSets, bag,'nameclass',initialStepSize,marginReg,marginType,optimalParams,stepDecreasingPower) +//classifier = trainSVMSGDClassifier(imgSets, bag,'nameclass',initialStepSize,marginReg,marginType,optimalParams,stepDecreasingPower,svmsgdType) +// +// Parameters +// classifier: Image category classifier location +// BagofFeaturesLocation : location of the xml or yml file. +// Description : features obtained after training. +// imgSets: Input imageSet to train the classifier on +// bag: The bagOfFeatures of the imageSet provided +// image: The set of images used for creating the imageset used for training +// nameclass: Name of the classifier one wants for their trained model .xml or .yml file +// initialStepSize:Parameter initialStepSize of a SVMSGD optimization problem that should be used to train the model. +// marginReg: Parameter marginRegularization of a SVMSGD optimization problem that should be used to train the model +// marginType: Parameter marginType of a SVMSGD optimization problem that should be used to train the model.it should be either 0 or 1. +// optimalParams: sets optimal parameters values for chosen SVM SGD model. +// stepDecreasingPower: Parameter stepDecreasingPower of a SVMSGD optimization problem that should be used to train the model. +// svmsgdType: Algorithm type of SVMSGD that should be used to train the model.it should be either 0 or 1. +// +// +// Description +// This function is used to train an image classifier using the SVMSGD(Stochastic Gradient Descent SVM) Model. +// +// Examples +// //get imageset from 'images2' folder +// image=imageSet('images2','recursive'); +// //get bag of features +// x=bagOfFeatures(image); +// //train thew model and name the saved .yml file as "pbrr" using the given parameters +// r=trainSVMSGDClassifier(image,x,"pbrr",0,0,0,1,0,1); +// //read image to get prediction from the above trained data +// z=imread("fish.jpg"); +// //finally predict the class using SVMSGD's prediction function for the input image +// resp=predict(r,z,"SVMSGD"); +// +// //get imageset from 'images2' folder +// image=imageSet('images2','recursive'); +// //get bag of features +// x=bagOfFeatures(image); +// //train the model and name the saved .yml file as "pbrr" +// r=trainSVMSGDClassifier(image,x,"pbrr"); +// //read image to get prediction from the above trained data +// z=imread("fish.jpg"); +// //finally predict the class using SVMSGD's prediction function for the input image +// resp=predict(r,z,"SVMSGD"); + + //convert to list + bag_list = bagStructToList(bag); + imgSets_list = imageSetToList(imgSet); + [lhs rhs]=argn(0); + + if lhs>1 + error(msprintf(" Too many output arguments")); + elseif rhs>9 + error(msprintf(" Too many input arguments,maximum number of arguments is 9")); + elseif rhs<3 + error(msprintf("the function needs atleast 3 arguments")); + end + if rhs==3 + temp=raw_trainSVMSGDSGDClassifier(imgSets_list, bag_list,classifierName); + elseif rhs==4 + temp=raw_trainSVMSGDSGDClassifier(imgSets_list,bag_list,classifierName,varargin(1)); + elseif rhs==5 + temp=raw_trainSVMSGDSGDClassifier(imgSets_list,bag_list,classifierName,varargin(1),varargin(2)); + elseif rhs==6 + temp=raw_trainSVMSGDSGDClassifier(imgSets_list,bag_list,classifierName,varargin(1),varargin(2),varargin(3)); + elseif rhs==7 + temp=raw_trainSVMSGDSGDClassifier(imgSets_list,bag_list,classifierName,varargin(1),varargin(2),varargin(3),varargin(4)); + elseif rhs==8 + temp=raw_trainSVMSGDSGDClassifier(imgSets_list,bag_list,classifierName,varargin(1),varargin(2),varargin(3),varargin(4),varargin(5)); + elseif rhs==9 + temp=raw_trainSVMSGDSGDClassifier(imgSets_list,bag_list,classifierName,varargin(1),varargin(2),varargin(3),varargin(4),varargin(5),varargin(6)); + end + classifier = struct("ClassifierLocation", temp(2), "BagofFeaturesLocation", temp(3), "Description", temp(4)); + +endfunction diff --git a/macros/undistortPoints.bin b/macros/undistortPoints.bin new file mode 100644 index 0000000000000000000000000000000000000000..1cf81d428cb13beb5bf63547a04d4e09be883081 GIT binary patch literal 6108 zcmd7W!EPKy5C&ie0wj*T0YkD5>vfh8pJZvg^D7zqjR z5n<|E&2L)cncc=m8cn_z$dk6FV+5FjbZ#qACkiXrnt*t91d%KhE zTfH?lFV))qjf2VT?qs*Wyt94#WP2W@f1VZTbboU5!rE-IGe5b0(P27SoEFrDl_wSa zX2ri-@>$7)lAq4b&L;JommHSNN~R?TCD!R*D`8{4SE5Gq?UGw1^mj`3ORV$fN54}- zPhj(n4S#m95>I~Y*xxQ0%E8)=5f-a<%So07zg`{8pDe`uJI7Z&k9f7iGw%wAD8fb)IG%#Cp@!Z8~%;Qu-@(LR&hJ# z`*HcoLw$I$cPAZ3VrIR~3y1OwA4B%`);e4`LpJJVvna{F^y44ZS~#!a`B<&;R+qfR zOa3s$^rXjSFg~p@zjeJh#@EBn-(B%m$wq$rhh-&%TD^zV2z| zDVF?k@TBH+H9Q}~TeTkldjmeLuElJ}co#P{e^+xgZ`#A*;Mc;iNA5`H69;hmyyT2# zZ^Z4#;~P6;_klTlwm31zD}Ta<-jkj!U;WI7=$SW4@Tu;c*XZ<2bn58aMaRw^7Tfsi z!6E(C0bB3LzQ3M4?nE!jS)Jji#cBP+75i(Q9}b)qPxnNh6MfF!z6Bp&dX%lTReOi$ zaO({JQ1VMBA9NVv;tZ}{OuhX$Z`Ycb&Wl>aCT$P$Nu9>eqbJ-gIiup4tBL60@FtJ; 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The terms +// are also available at +// http://www.cecill.info/licences/Licence_CeCILL_V2-en.txt +// Author: Deepshika & Nihar Rao +// Organization: FOSSEE, IIT Bombay +// Email: toolbox@scilab.in + +function [idealPoints] = undistortPoints(observedPoints, camMat, disCoefMat, rectMat, newCamMat) +// Returns the ideal point coordinates from the observed point coordinates +// +// Calling Sequence +// [idealPoints] = undistortPoints(observedPoints, camMat, disCoefMat, rectMat, newCamMat) +// +// Parameters +// observedPoints: 1xN or Nx1 2-channel (CV_32FC2 or CV_64FC2). +// camMat: \vecthreethree{f_x}{0}{c_x}{0}{f_y}{c_y}{0}{0}{1} +// disCoefMat: Input vector of distortion coefficients (k_1, k_2, p_1, p_2[, k_3[, k_4, k_5, k_6]]) of 4, 5, or 8 elements. If the vector is NULL/empty, the zero distortion coefficients are assumed. +// rectMat: Rectification transformation in the object space (3x3 matrix). If the matrix is empty, the identity transformation is used. +//newCamMat: New camera matrix (3x3) or new projection matrix (3x4. If the matrix is empty, the identity new camera matrix is used. +// idealPoints: ideal point coordinates matrix. If matrix newCamMat is identity or omitted, idealPoints will contain normalized point coordinates. +// +// Description +// Returns the ideal points coordinates from the observed point coordinates after undistortion and reverse perpective transformation. +// +// Examples +// [observedPoints] = [1 2 3 4; 4 3 2 1] +// [camMat] = [450 0 231; 0 876.3 87.1; 0 0 1] +// [disCoefMat] = [3 2 0 9] +// [rectMat] = [1 0 0; 0 1 0; 0 0 1] +// [newCamMat] = [] +// [idealPoints] = undistortPoints(observedPoints, camMat, disCoefMat, rectMat, newCamMat) + + + + output = raw_undistortPoints(observedPoints, camMat, disCoefMat, rectMat, newCamMat) + + idealPoints=output; + + + +endfunction diff --git a/macros/xyz2rgb.bin b/macros/xyz2rgb.bin new file mode 100644 index 0000000000000000000000000000000000000000..980d866a3ffaa3f0b863bc082a966b43c7a0d589 GIT binary patch literal 844 zcma)4K@Ng25JZfcpkUJkgh(-nhbDUW=r_FkPXFWsj5yPvA+<#|nY46g+39raeG_iQ zQri&+K`;UGN)?r|vsyDJGx3|i$sM^hkOJWV@7cC3(uR{oO6936?N%>v*lPw%J1)N! z!1V~oEE0)B2~w60H?OZFFOtn_cc^V!#^{I~8hB*u@bUUOO4+!sq{rxp|L9mikO1Zs zX5w+-I}O#5#y2yvH-yv&Xw!T%!%h;tYv)X$;0dW=ks`sf4-UL P{PAA&jvjJP+`9D*$A)B) literal 0 HcmV?d00001 diff --git a/macros/xyz2rgb.sci b/macros/xyz2rgb.sci new file mode 100644 index 0000000..d557939 --- /dev/null +++ b/macros/xyz2rgb.sci @@ -0,0 +1,8 @@ +function [output] = xyz2rgb(img) + image = mattolist(img); + a = opencv_xyz2rgb(image); + d = size(a); + for i=1:d + output(:,:,i) = a(i); + end +endfunction diff --git a/sci_gateway/builder_gateway.sce b/sci_gateway/builder_gateway.sce new file mode 100644 index 0000000..654d1e4 --- /dev/null +++ b/sci_gateway/builder_gateway.sce @@ -0,0 +1,13 @@ +function builder_gateway() + + sci_gateway_dir = get_absolute_file_path("builder_gateway.sce"); + languages = ["cpp"]; + + tbx_builder_gateway_lang(languages,sci_gateway_dir); + tbx_build_gateway_loader(languages,sci_gateway_dir); + tbx_build_gateway_clean(languages,sci_gateway_dir); + + endfunction + + builder_gateway() + clear builder_gateway; // remove builder_gateway on stack diff --git a/sci_gateway/cleaner_gateway.sce b/sci_gateway/cleaner_gateway.sce new file mode 100644 index 0000000..03aedaf --- /dev/null +++ b/sci_gateway/cleaner_gateway.sce @@ -0,0 +1,15 @@ +// This file is released under the 3-clause BSD license. See COPYING-BSD. +// Generated by builder_gateway.sce: Please, do not edit this file + +sci_gateway_dir = get_absolute_file_path("cleaner_gateway.sce"); +current_dir = pwd(); + +chdir(sci_gateway_dir); +if ( isdir("cpp") ) then + chdir("cpp"); + exec("cleaner.sce"); + mdelete("cleaner.sce"); +end + +chdir(current_dir); +clear sci_gateway_dir current_dir; diff --git a/sci_gateway/cpp/PCL_pcread.cpp b/sci_gateway/cpp/PCL_pcread.cpp new file mode 100644 index 0000000..6c7d5e7 --- /dev/null +++ b/sci_gateway/cpp/PCL_pcread.cpp @@ -0,0 +1,365 @@ +/*Authors-Nihar Rao + Shreyash Sharma + +*/ + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + + +using namespace std; +extern "C" +{ + #include "api_scilab.h" + #include "Scierror.h" + #include "BOOL.h" + #include + #include "sciprint.h" + + + +bool files_exist_check( char *name) { + struct stat buffer; + return (stat (name, &buffer) == 0); + } + + int PCL_pcread(char *fname, unsigned long fname_len) + { + SciErr sciErr; + int iLen = 0; + //variable info + int iRows = 0; + int iCols = 0; + int piRows = 0; + int piCols = 0; + int *piAddr = NULL; + int *piLen = NULL; + char **pstData = NULL; + int **pstData1 = NULL; + int i,j,k=0; + int intErr; + double val; + double *points; + double *rgbValues,*intensityValues; + int n; + int width,height; + int il,z; + double num; + double *xLimit; + double *yLimit; + double *zLimit; + double *normalVectors; + bool isDense; + pcl::PointXYZRGB minLimit,maxLimit; + + + + //Checking number of input and output arguments (enviromnet variable, min arguments, max arguments) + CheckInputArgument(pvApiCtx, 1, 1); + CheckOutputArgument(pvApiCtx, 11, 11); + + + + // get Address of inputs + sciErr = getVarAddressFromPosition(pvApiCtx, 1, &piAddr); + + if (sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + + + //Now, we will retrieve the string from the input parameter. For this, we will require 3 calls + //first call to retrieve dimensions + sciErr = getMatrixOfString(pvApiCtx, piAddr, &iRows, &iCols, NULL, NULL); + if(sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + piLen = (int*)malloc(sizeof(int) * iRows * iCols); + //second call to retrieve length of each string + sciErr = getMatrixOfString(pvApiCtx, piAddr, &iRows, &iCols, piLen, NULL); + if(sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + + pstData = (char**)malloc(sizeof(char*) * iRows * iCols); + for(i = 0 ; i < iRows * iCols ; i++) + { + pstData[i] = (char*)malloc(sizeof(char) * (piLen[i] + 1));//+ 1 for null termination + } + //third call to retrieve data + sciErr = getMatrixOfString(pvApiCtx, piAddr, &iRows, &iCols, piLen, pstData); + if(sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + //check if file exists + if(!files_exist_check(pstData[0])) + { + + Scierror(999, "Error: the input file not found!.Please enter correct path!\n"); + return 0; + } + + //get string version of file + + string inputFile(pstData[0]); + + /*Processing*/ + + + n=inputFile.length(); + + + + pcl::PointCloud::Ptr cloud (new pcl::PointCloud ()); + //checking ending + if(inputFile.substr(n-3,n-1)=="pcd") + { + + + + if (pcl::io::loadPCDFile (pstData[0], *cloud) == -1) // load the file + { + cout<<"\n ERROR: couldn't load file\n"< (pstData[0], *cloud) < 0) + { + cout<<"\n ERROR: couldn't load file\n"<height; + width=cloud->width; + num=cloud->points.size(); + isDense=cloud->is_dense; + + //Allocate memory for cloud processing + points=(double *)malloc(sizeof(double)*height*width*3); + normalVectors=(double *)malloc(sizeof(double)*height*width*3); + rgbValues=(double *)malloc(sizeof(double)*height*width*3); + intensityValues=(double *)malloc(sizeof(double)*height*width); + xLimit=(double *)malloc(sizeof(double)*1*2); + yLimit=(double *)malloc(sizeof(double)*1*2); + zLimit=(double *)malloc(sizeof(double)*1*2); + + + il=0; + + pcl::PointCloud::iterator it; + + + + //storing values + for ( it = cloud->points.begin(); it!=cloud->points.end(); ++it) { + points[il]=(*it).x; + points[(height * width) + il]=(*it).y; + points[(2 * height * width) + il]=(*it).z; + + //RGB + rgbValues[il]=(*it).r; + rgbValues[(height * width) + il]=(*it).g; + rgbValues[(2 * height * width) + il]=(*it).b; + //intensity + intensityValues[il]=0.2989 *(*it).r + 0.5870 * (*it).g + 0.1140 * (*it).b; + + il++; + + + + } + + + + //////get Limits + getMinMax3D(*cloud,minLimit,maxLimit); + + //Allocate limits for returning to scilab + + xLimit[0]=minLimit.x; + xLimit[1]=maxLimit.x; + + yLimit[0]=minLimit.y; + yLimit[1]=maxLimit.y; + + zLimit[0]=minLimit.z; + zLimit[1]=maxLimit.z; + + ///Normal computation + + + pcl::PointCloud::Ptr normals (new pcl::PointCloud); + pcl::IntegralImageNormalEstimation ne; + ne.setNormalEstimationMethod (ne.AVERAGE_3D_GRADIENT); + ne.setMaxDepthChangeFactor(0.02f); + ne.setNormalSmoothingSize(10.0f); + ne.setInputCloud(cloud); + //ne.setRadiusSearch (0.03); + ne.compute(*normals); + + + //convert cloud to double * + + + pcl::PointCloud::iterator ir; + il=0; + for ( ir = normals->points.begin(); ir!=normals->points.end(); ++ir) { + normalVectors[il]=(*ir).x; + normalVectors[(height * width) + il]=(*ir).y; + normalVectors[(2 * height * width) + il]=(*ir).z; + + il++; + + + } + + } + catch(exception& e) + { + Scierror(999,e.what()); + return 0; + + + } + + + + + + + //Write Output to Scilab + + + + sciErr = createMatrixOfDouble(pvApiCtx, nbInputArgument(pvApiCtx) + 1,height*width, 3, points); + if(sciErr.iErr){ + printError(&sciErr, 0); + return 0; + } + sciErr = createMatrixOfDouble(pvApiCtx, nbInputArgument(pvApiCtx) + 2, 1, 1,&num ); + if(sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + intErr = createScalarInteger32(pvApiCtx, nbInputArgument(pvApiCtx) + 3,width); + if(intErr) + { + Scierror(999,"Error creating matrix"); + return 0; + } + intErr = createScalarInteger32(pvApiCtx, nbInputArgument(pvApiCtx) + 4,height); + if(intErr) + { + Scierror(999,"Error creating matrix"); + return 0; + } + sciErr = createMatrixOfDouble(pvApiCtx, nbInputArgument(pvApiCtx) + 5,height*width, 3, rgbValues); + if(sciErr.iErr){ + printError(&sciErr, 0); + return 0; + } + sciErr = createMatrixOfDouble(pvApiCtx, nbInputArgument(pvApiCtx) + 6,1,2,xLimit); + if(sciErr.iErr){ + printError(&sciErr, 0); + return 0; + } + sciErr = createMatrixOfDouble(pvApiCtx, nbInputArgument(pvApiCtx) + 7,1,2,yLimit); + if(sciErr.iErr){ + printError(&sciErr, 0); + return 0; + } + sciErr = createMatrixOfDouble(pvApiCtx, nbInputArgument(pvApiCtx) + 8,1,2,zLimit); + if(sciErr.iErr){ + printError(&sciErr, 0); + return 0; + } + + //processing bool for output(is_dense) + int final; + if(isDense) + final=1; + else + final=0; + + intErr=createScalarBoolean(pvApiCtx, nbInputArgument(pvApiCtx) + 9,final ); + if(intErr) + { + Scierror(999,"error creating booleean output "); + return 0; + + + } + sciErr = createMatrixOfDouble(pvApiCtx, nbInputArgument(pvApiCtx) + 10,width,height,intensityValues); + if(sciErr.iErr){ + printError(&sciErr, 0); + return 0; + } + sciErr = createMatrixOfDouble(pvApiCtx, nbInputArgument(pvApiCtx) + 11,height*width, 3, normalVectors); + if(sciErr.iErr){ + printError(&sciErr, 0); + return 0; + } + + + for(int i=1;i<=11;i++) + AssignOutputVariable(pvApiCtx, i) = nbInputArgument(pvApiCtx) + i; + + + //Returning the Output Variables as arguments to the Scilab environment + ReturnArguments(pvApiCtx); + + return 0; + } + + + + +} + + diff --git a/sci_gateway/cpp/builder_gateway_cpp.sce b/sci_gateway/cpp/builder_gateway_cpp.sce new file mode 100644 index 0000000..318bf1a --- /dev/null +++ b/sci_gateway/cpp/builder_gateway_cpp.sce @@ -0,0 +1,458 @@ +// This file is released under the 3-clause BSD license. See COPYING-BSD. + + +mode(-1) +lines(0) + +toolbox_title = "FOSSEE_Image_Processing_Toolbox"; + +Build_64Bits = %t; + + +path_builder = get_absolute_file_path('builder_gateway_cpp.sce'); +Names = [ +// "raw_dctmtx", "dctmtx"; +// "raw_multithresh", "multithresh"; +// "raw_applycform", "opencv_applycform"; + "raw_arrowedline", "opencv_arrowedline"; + "raw_blur", "opencv_blur"; + "raw_boundingRect", "opencv_boundingRect"; +//// "raw_bwconvhull", "opencv_bwconvhull"; +//// "raw_bwdistgeodesic", "opencv_bwdistgeodesic"; +//// "raw_bwlookup", "opencv_bwlookup"; +//// "raw_canny", "opencv_canny"; +// "raw_circle", "opencv_circle"; +//// "raw_clipline", "opencv_clipline"; +//// "raw_convexhull", "opencv_convexhull"; +//// "raw_convmtx2", "opencv_convmtx2"; +//// "raw_copymakeborder", "opencv_copymakeborder"; +//// "raw_corner", "opencv_corner"; +//// "raw_cornerEigenValsAndVecs", "opencv_cornerEigenValsAndVecs"; +//// "raw_cornerHarris", "opencv_cornerHarris"; +//// "raw_cornerMinEigenVal", "opencv_cornerMinEigenVal"; +// "raw_cvtColor", "opencv_cvtColor"; +//// "raw_demosaic", "opencv_demosaic"; +// "raw_dilate", "opencv_dilate"; +//// "raw_ellipse", "opencv_ellipse"; +//// "raw_ellipse2poly", "opencv_ellipse2poly"; +// +//// "raw_fftshift", "opencv_fftshift"; +//// "raw_fillconvexpoly", "opencv_fillconvexpoly"; +//// "raw_filter2D", "opencv_filter2D"; +//// "raw_findContours", "opencv_findContours"; +//// "raw_fsamp2", "opencv_fsamp2"; + +//// "raw_gabor", "opencv_gabor"; +//// "raw_gaussianblur", "opencv_gaussianblur"; +//// "raw_getStructuringElement", "opencv_getStructuringElement"; +//// "getTextSize", "opencv_getTextSize"; +//// "raw_getgaussiankernel", "opencv_getgaussiankernel"; +//// "raw_getrectsubpix", "opencv_getrectsubpix"; +//// "raw_getrotationmatrix2D", "opencv_getrotationmatrix2D"; +//// "raw_goodfeaturestotrack", "opencv_goodfeaturestotrack"; + +//// "raw_houghcircles", "opencv_houghcircles"; +//// "raw_houghlines", "opencv_houghlines"; +//// "raw_houghlinesp", "opencv_houghlinesp"; +//// "raw_ifftshift", "opencv_ifftshift"; +//// "raw_im2double", "opencv_im2double"; +//// "raw_imabsdiff", "opencv_imabsdiff"; +//// "raw_imadd", "opencv_imadd"; +//// "raw_imattributes", "opencv_imattributes"; +//// "raw_imboxfilt3", "opencv_imboxfilt3"; +//// "raw_imcomplement", "opencv_imcomplement"; +//// "raw_imcontour", "opencv_imcontour"; +//// "raw_imcontrast", "opencv_imcontrast"; +// "raw_imcrop", "opencv_imcrop"; +//// "raw_imdivide", "opencv_imdivide"; +//// "raw_imextendedmax", "opencv_imextendedmax"; +//// "raw_imextendedmin", "opencv_imextendedmin"; +//// "raw_imfill", "opencv_imfill"; +//// "raw_imfindcircles", "opencv_imfindcircles"; +//// "raw_imfuse", "opencv_imfuse"; +//// "raw_imgaborfilt", "opencv_imgaborfilt"; +//// "raw_imgaussfilt3", "opencv_imgaussfilt3"; +//// "raw_imguidedfilter", "opencv_imguidedfilter"; +//// "raw_imhmax", "opencv_imhmax"; +//// "raw_imhmin", "opencv_imhmin"; +//// "raw_imimposemin", "opencv_imimposemin"; +//// "raw_imlincomb", "opencv_imlincomb"; +//// "raw_immultiply", "opencv_immultiply"; +// "raw_impixel", "opencv_impixel"; +//// "raw_impyramid", "opencv_impyramid"; + "raw_imread", "opencv_imread"; +//// "raw_imrect", "opencv_imrect"; +// "raw_imresize", "opencv_imresize"; +// "raw_imsharpen", "opencv_imsharpen"; +//// "raw_imshowpair", "opencv_imshowpair"; +//// "raw_imsubtract", "opencv_imsubtract"; +//// "raw_imwarp", "opencv_imwarp"; +// "raw_imwrite", "opencv_imwrite"; +//// "raw_ind2gray", "opencv_ind2gray"; +//// "raw_ind2rgb", "opencv_ind2rgb"; +//// "raw_lab2double", "opencv_lab2double"; +//// "raw_lab2rgb", "opencv_lab2rgb"; +//// "raw_lab2uint16", "opencv_lab2uint16"; +//// "raw_lab2uint8", "opencv_lab2uint8"; +//// "raw_lab2xyz", "opencv_lab2xyz"; +//// "raw_laplacian", "opencv_laplacian"; +//// "raw_line", "opencv_line"; +// + +// "raw_medianblur", "opencv_medianblur"; +//// "raw_montage", "opencv_montage"; +//// "raw_morphologyEx", "opencv_morphologyEx"; +//// "raw_ntsc2rgb", "opencv_ntsc2rgb"; +//// "raw_puttext", "opencv_puttext"; +//// "raw_pyrDown", "opencv_pyrDown"; +//// "raw_pyrUp", "opencv_pyrUp"; +//// "raw_rectangle", "opencv_rectangle"; +//// "raw_regionfill", "opencv_regionfill"; +//// "raw_rgb2lab", "opencv_rgb2lab"; +//// "raw_rgb2ntsc", "opencv_rgb2ntsc"; + "raw_rgb2xyz", "opencv_rgb2xyz"; +//// "raw_roifill", "opencv_roifill"; +//// "raw_roipoly", "opencv_roipoly"; +//// "raw_scharr", "opencv_scharr"; +//// "raw_sepFilter2D", "opencv_sepFilter2D"; +//// "raw_sobel", "opencv_sobel"; +//// "raw_ssim", "opencv_ssim"; +//// "raw_threshold", "opencv_threshold"; +//// "raw_undistort", "opencv_undistort"; +//// "raw_viscircles", "opencv_viscircles"; +//// "raw_watershed", "opencv_watershed"; +//// "raw_whitepoint", "opencv_whitepoint"; +//// "raw_wiener2", "opencv_wiener2"; +//// "raw_xyz2double", "opencv_xyz2double"; +//// "raw_xyz2lab", "opencv_xyz2lab"; +//// "raw_xyz2rgb", "opencv_xyz2rgb"; +//// "raw_xyz2uint16", "opencv_xyz2uint16"; +// "raw_iminpaint.cpp", "opencv_iminpaint"; +// "raw_roiFreeHand.cpp","opencv_roiFreeHand.cpp" + +// "raw_deconvlucy", "opencv_deconvlucy"; +//// "imhistmatch", "opencv_imhistmatch"; +//// "graycoprops", "opencv_graycoprops"; +//// "graydiffweight", "opencv_graydiffweight"; +//// "decorrstretch", "opencv_decorrstretch"; +//// "adaptf", "opencv_adapthisteq"; +//// "affine2d", "opencv_affine2d"; + + +//// "approxpolyDP","approxpolyDP"; +//// "arclenght","arclenght"; +//// "bilateralfilter","bilateralfilter"; +//// "borderInterpolate","borderInterpolate"; +//// "boxfilter","boxfilter"; +//// "contourarea","contourarea"; +//// "boxfilter","boxfilter"; +// "raw_fitellipse","opencv_fitellipse"; +//// "getkerneltype","getkerneltype"; +//// "histeq","histeq"; +// "raw_imrotate","opencv_imrotate"; +//// "mean1","mean1"; +//// "minAreaRect","minAreaRect"; +//// "minimumenclosingcirlce","minimumenclosingcirlce"; +//// "pyrMeanShiftFiltering","pyrMeanShiftFiltering"; +// "raw_rgb2gray","opencv_rgb2gray"; +//// "warpaffine","warpaffine"; +// "raw_detectMinEigenFeatures","opencv_detectMinEigenFeatures"; +// "raw_correctMatches","opencv_correctMatches"; +// "raw_findHomography","opencv_findHomography"; +// "raw_matMulDeriv","opencv_matMulDeriv"; +// "raw_imageSet","opencv_imageSet"; +// "raw_bagOfFeatures","opencv_bagOfFeatures"; +// "raw_trainImageCategoryClassifier","opencv_trainImageCategoryClassifier"; +// "raw_trainSVMClassifier","opencv_trainSVMClassifier"; +// "raw_predictSVM","opencv_predictSVM"; +// "raw_trainSVMSGDClassifier","opencv_trainSVMSGDClassifier"; +// "raw_predictSVMSGD","opencv_predictSVMSGD"; +// "raw_getParamsSVM","opencv_getParamsSVM"; +// "raw_getParamsSVMSGD","opencv_getParamsSVMSGD"; +// "raw_trainBoostClassifier","opencv_trainBoostClassifier"; +// "raw_predictBoost","opencv_predictBoost"; +// "raw_trainEMClassifier","opencv_trainEMClassifier"; +// "raw_CascadeObjectDetector","opencv_CascadeObjectDetector"; +// "ocv_detectBRISKFeatures","opencv_detectBRISKFeatures"; +// "raw_detectMSERFeatures","opencv_detectMSERFeatures"; +// "raw_extractFeatures","opencv_extractFeatures"; +// "raw_detectSURFFeatures","opencv_detectSURFFeatures" +// "raw_drawMatch","opencv_drawMatch"; +// "raw_matchFeatures","opencv_matchFeatures"; +// "ocv_detectFASTFeatures","opencv_detectFASTFeatures"; +// "ocv_detectHarrisFeatures","opencv_detectHarrisFeatures"; +// "raw_peopleDetector","opencv_peopleDetector"; +// "raw_rectangle","opencv_rectangle"; +// "raw_detectKAZEFeatures","opencv_detectKAZEFeatures"; +// "raw_detectGFTTFeatures","opencv_detectGFTTFeatures"; +// "raw_estimateFundamentalMat","opencv_estimateFundamentalMat"; +// "raw_undistortPoints","opencv_undistortPoints"; +// "raw_rectifyStereoImages","opencv_rectifyStereoImages"; +// "raw_estimateNewCameraMatrix", "opencv_estimateNewCameraMatrix"; +// "raw_stereoCalibrate","opencv_stereoCalibrate"; +// "raw_detectCheckerboardCorner","opencv_detectCheckerboardCorner"; +// "raw_genCheckerboardPoints","opencv_genCheckerboardPoints"; +// "raw_undistortImage","opencv_undistortImage"; +// "raw_disparity","opencv_disparity"; +// "raw_indexImages","opencv_indexImages"; +// "raw_lab2double","opencv_lab2double"; +// "raw_fitellipse","opencv_fitellipse"; +// "raw_graycoprops","opencv_graycoprops"; +// "raw_integralKernel","opencv_integralKernel"; +// "raw_pcread","PCL_pcread"; + + + + ]; + +Files = [ +// "dctmtx.cpp", + +// "multithresh.cpp", +// "opencv_applycform.cpp", +// "opencv_arrowedline.cpp", +// "opencv_blur.cpp", +//// "opencv_boundingRect.cpp", +//// "opencv_bwconvhull.cpp", +//// "opencv_bwdistgeodesic.cpp", +//// "opencv_bwlookup.cpp", +//// "opencv_canny.cpp", +// "opencv_circle.cpp", +//// "opencv_clipline.cpp", +//// "opencv_convexhull.cpp", +//// "opencv_convmtx2.cpp", +//// "opencv_copymakeborder.cpp", +//// "opencv_corner.cpp", +//// "opencv_cornerEigenValsAndVecs.cpp", +//// "opencv_cornerHarris.cpp", +//// "opencv_cornerMinEigenVal.cpp", +// "opencv_cvtColor.cpp", +//// "opencv_demosaic.cpp", +// "opencv_dilate.cpp", +// "opencv_ellipse.cpp", +//// "opencv_ellipse2poly.cpp", +/// "opencv_erode.cpp", +//// "opencv_fftshift.cpp", +//// "opencv_fillconvexpoly.cpp", +//// "opencv_filter2D.cpp", +//// "opencv_findContours.cpp", +//// "opencv_fsamp2.cpp", + +//// "opencv_gabor.cpp", +//// "opencv_gaussianblur.cpp", +//// "opencv_getStructuringElement.cpp", +//// "opencv_getTextSize.cpp", +//// "opencv_getgaussiankernel.cpp", +//// "opencv_getrectsubpix.cpp", +//// "opencv_getrotationmatrix2D.cpp", +//// "opencv_goodfeaturestotrack.cpp", + +//// "opencv_houghcircles.cpp", +//// "opencv_houghlines.cpp", +//// "opencv_houghlinesp.cpp", +//// "opencv_ifftshift.cpp", +//// "opencv_im2double.cpp", +//// "opencv_imabsdiff.cpp", +//// "opencv_imadd.cpp", +//// "opencv_imattributes.cpp", +//// "opencv_imboxfilt3.cpp", +//// "opencv_imcomplement.cpp", +//// "opencv_imcontour.cpp", +//// "opencv_imcontrast.cpp", +// "opencv_imcrop.cpp", +//// "opencv_imdivide.cpp", +//// "opencv_imextendedmax.cpp", +//// "opencv_imextendedmin.cpp", +//// "opencv_imfill.cpp", +//// "opencv_imfindcircles.cpp", +//// "opencv_imfuse.cpp", +//// "opencv_imgaborfilt.cpp", +//// "opencv_imgaussfilt3.cpp", +//// "opencv_imguidedfilter.cpp", +//// "opencv_imhmax.cpp", +//// "opencv_imhmin.cpp", +//// "opencv_imimposemin.cpp", +//// "opencv_imlincomb.cpp", +//// "opencv_immultiply.cpp", +// "opencv_impixel.cpp", +//// "opencv_impyramid.cpp", + "opencv_imread.cpp", +//// "opencv_imrect.cpp", +// "opencv_imresize.cpp", +// "opencv_imsharpen.cpp", +//// "opencv_imshowpair.cpp", +//// "opencv_imsubtract.cpp", +//// "opencv_imwarp.cpp", +// "opencv_imwrite.cpp", +//// "opencv_ind2gray.cpp", +//// "opencv_ind2rgb.cpp", +//// "opencv_lab2double.cpp", +//// "opencv_lab2rgb.cpp", +//// "opencv_lab2uint16.cpp", +//// "opencv_lab2uint8.cpp", +//// "opencv_lab2xyz.cpp", +//// "opencv_laplacian.cpp", +//// "opencv_line.cpp", +// "opencv_roiFreeHand.cpp", + +// "opencv_medianblur.cpp", +//// "opencv_montage.cpp", +//// "opencv_morphologyEx.cpp", +//// "opencv_ntsc2rgb.cpp", +//// "opencv_puttext.cpp", +//// "opencv_pyrDown.cpp", +//// "opencv_pyrUp.cpp", +//// "opencv_rectangle.cpp", +//// "opencv_regionfill.cpp", +//// "opencv_rgb2lab.cpp", +//// "opencv_rgb2ntsc.cpp", + "opencv_rgb2xyz.cpp", +//// "opencv_roifill.cpp", +//// "opencv_roipoly.cpp", +//// "opencv_scharr.cpp", +//// "opencv_sepFilter2D.cpp", +//// "opencv_sobel.cpp", +//// "opencv_ssim.cpp", +//// "opencv_threshold.cpp", +//// "opencv_undistort.cpp", +//// "opencv_viscircles.cpp", +//// "opencv_watershed.cpp", +//// "opencv_whitepoint.cpp", +//// "opencv_wiener2.cpp", +//// "opencv_xyz2double.cpp", +//// "opencv_xyz2lab.cpp", +//// "opencv_xyz2rgb.cpp", +//// "opencv_xyz2uint16.cpp", + + +// "opencv_deconvlucy.cpp", +//// "opencv_integralImage.cpp", +//// "opencv_imhistmatch.cpp", +//// "opencv_graycoprops.cpp", +//// "opencv_graydiffweight.cpp", +//// "opencv_decorrstretch.cpp", +//// "opencv_adapthisteq.cpp", +//// "opencv_affine2d.cpp", + +// "rgb2gray.cpp", +//// "warpaffine.cpp", +//// "opencv_pyrMeanShiftFiltering.cpp", +//// "opencv_minimumenclosingcirlce.cpp", +//// "opencv_minAreaRect.cpp", +//// "opencv_mean1.cpp", +// "opencv_imrotate.cpp", +//// "opencv_getkerneltype.cpp", +// "opencv_fitellipse.cpp", +//// "opencv_contourarea.cpp", +//// "opencv_boxfilter.cpp", +//// "opencv_borderInterpolate.cpp", +//// "opencv_bilateralfilter.cpp", +//// "opencv_arclength.cpp", +//// "opencv_approxpolyDP.cpp", +//// "opencv_histeq.cpp", +// "opencv_detectMinEigenFeatures.cpp", + "opencv_correctMatches.cpp", + "opencv_findHomography.cpp", + "opencv_matMulDeriv.cpp", + "opencv_imageSet.cpp", + "opencv_bagOfFeatures.cpp", + "opencv_trainImageCategoryClassifier.cpp", + "opencv_trainSVMClassifier.cpp", + "opencv_predictSVM.cpp", + "opencv_trainSVMSGDClassifier.cpp", + "opencv_predictSVMSGD.cpp", + "opencv_getParamsSVM.cpp", + "opencv_getParamsSVMSGD.cpp", + "opencv_trainBoostClassifier.cpp", + "opencv_predictBoost.cpp", + "opencv_trainEMClassifier.cpp", + "opencv_CascadeObjectDetector.cpp", + "opencv_detectBRISKFeatures.cpp", + "opencv_detectMSERFeatures.cpp", + "opencv_extractFeatures.cpp", + "opencv_detectSURFFeatures.cpp", + "opencv_drawMatch.cpp", + "opencv_matchFeatures.cpp", + "opencv_detectFASTFeatures.cpp", + "opencv_detectHarrisFeatures.cpp", + "opencv_peopleDetector.cpp", + "opencv_rectangle.cpp", + "opencv_detectKAZEFeatures.cpp", + "opencv_detectGFTTFeatures.cpp", + "opencv_estimateFundamentalMatrix.cpp", + "opencv_undistortPoints.cpp", + "opencv_rectifyStereoImages.cpp", +// "opencv_estimateNewCameraMatrix.cpp", + "opencv_stereoCalibrate.cpp", + "opencv_detectCheckerboardCorner.cpp", + "opencv_genCheckerboardPoints.cpp", + "opencv_undistortImage.cpp", + "opencv_disparity.cpp", + "opencv_indexImages.cpp", + "opencv_lab2double.cpp", + "opencv_fitellipse.cpp", + "opencv_graycoprops.cpp", + "opencv_integralKernel.cpp", + "PCL_pcread.cpp" + "opencv_bundleAdjustment.cpp" + "opencv_iminpaint.cpp" + + + + ]; + + //copyfile("/home/fossee/Desktop/FOSSEE_Image_Processing_Toolbox/sci_gateway/cpp/common.h",TMPDIR); + //copyfile("/home/fossee/Desktop/FOSSEE_Image_Processing_Toolbox/sci_gateway/cpp/common.cpp",TMPDIR); + + //[a, opt] = getversion(); + //Version = opt(2); + + //if getos()=="Windows" then +// third_dir = path_builder+filesep()+'..'+filesep()+'..'+filesep()+'thirdparty'; +// lib_base_dir = third_dir + filesep() + 'windows' + filesep() + 'lib' + filesep() + Version + filesep(); +// inc_base_dir = third_dir + filesep() + 'windows' + filesep() + 'include' + filesep() + 'coin'; +// C_Flags=['-D__USE_DEPRECATED_STACK_FUNCTIONS__ -w -I '+path_builder+' '+ '-I '+inc_base_dir+' '] +// Linker_Flag = [lib_base_dir+"libClp.lib "+lib_base_dir+"libCgl.lib "+lib_base_dir+"libOsi.lib "+lib_base_dir+"libOsiClp.lib "+lib_base_dir+"libCoinUtils.lib "+lib_base_dir+"libSymphony.lib "+lib_base_dir+"IpOptFSS.lib "+lib_base_dir+"IpOpt-vc10.lib "] + +//else + //third_dir = path_builder+'..'+filesep()+'..'+filesep()+'thirdparty'; + //lib_base_dir = third_dir + filesep() + 'linux' + filesep() + 'lib' + filesep() + Version + filesep(); + //inc_base_dir = third_dir + filesep() + 'linux' + filesep() + 'include' + filesep() + 'opencv'; + //incl_base_dir = third_dir + filesep() + 'linux' + filesep() + 'include' + filesep() + 'opencv2'; + +// C_Flags=["-D__USE_DEPRECATED_STACK_FUNCTIONS__ -w -fpermissive -I"+path_builder+"-I"+inc_base_dir+" "+"-I"+incl_base_dir+" -Wl,-rpath= "+lib_base_dir+" "+"-L"+lib_base_dir+"libopencv_core"+" "+"-L"+lib_base_dir+"libopencv_highgui"+" "+"-L"+lib_base_dir+"libopencv_imgproc" ] + +// export LD_LIBRARY_PATH="$LD_LIBRARY_PATH:"+lib_base_dir +// unix_s("export LD_LIBRARY_PATH="+lib_base_dir); + +// C_Flags=["-I"+inc_base_dir+" "+"-I"+incl_base_dir]; +// Linker_Flag = ["-L"+lib_base_dir+"libopencv_core"+" "+"-L"+lib_base_dir+"libopencv_highgui"+" "+"-L"+lib_base_dir+"libopencv_imgproc" ]; + +// Linker_Flag = ["-L/home/fossee/Desktop/FOSSEE_Image_Processing_Toolbox/thirdparty/linux/lib/x64 -lopencv_core -L/home/fossee/Desktop/FOSSEE_Image_Processing_Toolbox/thirdparty/linux/lib/x64 -lopencv_imgproc -L/home/fossee/Desktop/FOSSEE_Image_Processing_Toolbox/thirdparty/linux/lib/x64 -lopencv_highgui" ] + + +//tools_path = path_builder + "../../thirdparty/linux/"; +//unix_s("export LD_LIBRARY_PATH="+tools_path+"lib/"+Version+filesep()+" "); +//C_Flags=["-w -fpermissive -I"+tools_path+"include/opencv -I"+tools_path+"include/opencv2 -Wl,-rpath="+tools_path+"lib/"+Version+filesep()+" "] + +//Linker_Flag = ["-L"+tools_path+"lib/"+Version+"-lopencv_shape -lopencv_stitching -lopencv_objdetect -lopencv_superres -lopencv_videostab -lopencv_calib3d -lopencv_features2d -lopencv_highgui -lopencv_video -lopencv_photo -lopencv_ml -lopencv_imgproc -lopencv_flann -lopencv_core "] + +//end + +//tbx_build_gateway(toolbox_title,Names,Files,get_absolute_file_path("builder_gateway_cpp.sce"), [], Linker_Flag, C_Flags,"g++"); + +//clear toolbox_title Names Files Linker_Flag C_Flags; + +function builder_gw_cpp() + WITHOUT_AUTO_PUTLHSVAR = %t; + copyfile(path_builder+"/common.h",TMPDIR); + copyfile(path_builder+"/common.cpp",TMPDIR); + tbx_build_gateway("skeleton_imageprocessing", .. + Names, .. + Files, .. + get_absolute_file_path("builder_gateway_cpp.sce"),[],["-L/usr/local/lib -lopencv_stitching -lopencv_superres -lopencv_videostab -lopencv_aruco -lopencv_bgsegm -lopencv_bioinspired -lopencv_ccalib -lopencv_cvv -lopencv_dpm -lopencv_fuzzy -lopencv_hdf -lopencv_line_descriptor -lopencv_optflow -lopencv_reg -lopencv_saliency -lopencv_stereo -lopencv_structured_light -lopencv_phase_unwrapping -lopencv_rgbd -lopencv_viz -lopencv_surface_matching -lopencv_tracking -lopencv_datasets -lopencv_text -lopencv_face -lopencv_plot -lopencv_dnn -lopencv_xfeatures2d -lopencv_shape -lopencv_video -lopencv_ximgproc -lopencv_calib3d -lopencv_features2d -lopencv_flann -lopencv_xobjdetect -lopencv_objdetect -lopencv_ml -lopencv_xphoto -lopencv_highgui -lopencv_videoio -lopencv_imgcodecs -lopencv_photo -lopencv_imgproc -lopencv_core -lpcl_common -lpcl_features -lpcl_filters -lpcl_io -lpcl_kdtree -lpcl_keypoints -lpcl_octree -lpcl_outofcore -lpcl_people -lpcl_recognition -lpcl_registration -lpcl_sample_consensus -lpcl_search -lpcl_segmentation -lpcl_surface -lpcl_tracking"],["-I/usr/include/scilab -I/usr/local/include/opencv -I/usr/local/include/opencv2 -I/usr/local/include/pcl-1.8 -I/usr/include/eigen3 "],"g++"); +endfunction + +builder_gw_cpp(); +clear builder_gw_cpp; // remove builder_gw_cpp on stack + diff --git a/sci_gateway/cpp/builder_gateway_cpp.sce~ b/sci_gateway/cpp/builder_gateway_cpp.sce~ new file mode 100644 index 0000000..c736288 --- /dev/null +++ b/sci_gateway/cpp/builder_gateway_cpp.sce~ @@ -0,0 +1,364 @@ +// This file is released under the 3-clause BSD license. See COPYING-BSD. + + +mode(-1) +lines(0) + +toolbox_title = "FOSSEE_Image_Processing_Toolbox"; + +Build_64Bits = %t; + + +path_builder = get_absolute_file_path('builder_gateway_cpp.sce'); +Names = [ +// "raw_dctmtx", "dctmtx"; +// "raw_multithresh", "multithresh"; +// "raw_applycform", "opencv_applycform"; + //"raw_arrowedline", "opencv_arrowedline"; + "raw_blur", "opencv_blur"; +// "raw_boundingRect", "opencv_boundingRect"; +// "raw_bwconvhull", "opencv_bwconvhull"; +// "raw_bwdistgeodesic", "opencv_bwdistgeodesic"; +// "raw_bwlookup", "opencv_bwlookup"; +// "raw_canny", "opencv_canny"; + "raw_circle", "opencv_circle"; +// "raw_clipline", "opencv_clipline"; +// "raw_convexhull", "opencv_convexhull"; +// "raw_convmtx2", "opencv_convmtx2"; +// "raw_copymakeborder", "opencv_copymakeborder"; +// "raw_corner", "opencv_corner"; +// "raw_cornerEigenValsAndVecs", "opencv_cornerEigenValsAndVecs"; +// "raw_cornerHarris", "opencv_cornerHarris"; +// "raw_cornerMinEigenVal", "opencv_cornerMinEigenVal"; +// "raw_cvtColor", "opencv_cvtColor"; +// "raw_demosaic", "opencv_demosaic"; + "raw_dilate", "opencv_dilate"; +// "raw_ellipse", "opencv_ellipse"; +// "raw_ellipse2poly", "opencv_ellipse2poly"; + "raw_erode", "opencv_erode"; +// "raw_fftshift", "opencv_fftshift"; +// "raw_fillconvexpoly", "opencv_fillconvexpoly"; +// "raw_filter2D", "opencv_filter2D"; +// "raw_findContours", "opencv_findContours"; +// "raw_fsamp2", "opencv_fsamp2"; + +// "raw_gabor", "opencv_gabor"; +// "raw_gaussianblur", "opencv_gaussianblur"; +// "raw_getStructuringElement", "opencv_getStructuringElement"; +// "getTextSize", "opencv_getTextSize"; +// "raw_getgaussiankernel", "opencv_getgaussiankernel"; +// "raw_getrectsubpix", "opencv_getrectsubpix"; +// "raw_getrotationmatrix2D", "opencv_getrotationmatrix2D"; +// "raw_goodfeaturestotrack", "opencv_goodfeaturestotrack"; + +// "raw_houghcircles", "opencv_houghcircles"; +// "raw_houghlines", "opencv_houghlines"; +// "raw_houghlinesp", "opencv_houghlinesp"; +// "raw_ifftshift", "opencv_ifftshift"; +// "raw_im2double", "opencv_im2double"; +// "raw_imabsdiff", "opencv_imabsdiff"; +// "raw_imadd", "opencv_imadd"; +// "raw_imattributes", "opencv_imattributes"; +// "raw_imboxfilt3", "opencv_imboxfilt3"; +// "raw_imcomplement", "opencv_imcomplement"; +// "raw_imcontour", "opencv_imcontour"; +// "raw_imcontrast", "opencv_imcontrast"; + "raw_imcrop", "opencv_imcrop"; +// "raw_imdivide", "opencv_imdivide"; +// "raw_imextendedmax", "opencv_imextendedmax"; +// "raw_imextendedmin", "opencv_imextendedmin"; +// "raw_imfill", "opencv_imfill"; +// "raw_imfindcircles", "opencv_imfindcircles"; +// "raw_imfuse", "opencv_imfuse"; +// "raw_imgaborfilt", "opencv_imgaborfilt"; +// "raw_imgaussfilt3", "opencv_imgaussfilt3"; +// "raw_imguidedfilter", "opencv_imguidedfilter"; +// "raw_imhmax", "opencv_imhmax"; +// "raw_imhmin", "opencv_imhmin"; +// "raw_imimposemin", "opencv_imimposemin"; +// "raw_imlincomb", "opencv_imlincomb"; +// "raw_immultiply", "opencv_immultiply"; + "raw_impixel", "opencv_impixel"; +// "raw_impyramid", "opencv_impyramid"; + "raw_imread", "opencv_imread"; +// "raw_imrect", "opencv_imrect"; + "raw_imresize", "opencv_imresize"; + "raw_imsharpen", "opencv_imsharpen"; +// "raw_imshowpair", "opencv_imshowpair"; +// "raw_imsubtract", "opencv_imsubtract"; +// "raw_imwarp", "opencv_imwarp"; + "raw_imwrite", "opencv_imwrite"; +// "raw_ind2gray", "opencv_ind2gray"; +// "raw_ind2rgb", "opencv_ind2rgb"; +// "raw_lab2double", "opencv_lab2double"; +// "raw_lab2rgb", "opencv_lab2rgb"; +// "raw_lab2uint16", "opencv_lab2uint16"; +// "raw_lab2uint8", "opencv_lab2uint8"; +// "raw_lab2xyz", "opencv_lab2xyz"; +// "raw_laplacian", "opencv_laplacian"; +// "raw_line", "opencv_line"; + +// "raw_medianblur", "opencv_medianblur"; +// "raw_montage", "opencv_montage"; +// "raw_morphologyEx", "opencv_morphologyEx"; +// "raw_ntsc2rgb", "opencv_ntsc2rgb"; +// "raw_puttext", "opencv_puttext"; +// "raw_pyrDown", "opencv_pyrDown"; +// "raw_pyrUp", "opencv_pyrUp"; +// "raw_rectangle", "opencv_rectangle"; +// "raw_regionfill", "opencv_regionfill"; +// "raw_rgb2lab", "opencv_rgb2lab"; +// "raw_rgb2ntsc", "opencv_rgb2ntsc"; +// "raw_rgb2xyz", "opencv_rgb2xyz"; +// "raw_roifill", "opencv_roifill"; +// "raw_roipoly", "opencv_roipoly"; +// "raw_scharr", "opencv_scharr"; +// "raw_sepFilter2D", "opencv_sepFilter2D"; +// "raw_sobel", "opencv_sobel"; +// "raw_ssim", "opencv_ssim"; +// "raw_threshold", "opencv_threshold"; +// "raw_undistort", "opencv_undistort"; +// "raw_viscircles", "opencv_viscircles"; +// "raw_watershed", "opencv_watershed"; +// "raw_whitepoint", "opencv_whitepoint"; +// "raw_wiener2", "opencv_wiener2"; +// "raw_xyz2double", "opencv_xyz2double"; +// "raw_xyz2lab", "opencv_xyz2lab"; +// "raw_xyz2rgb", "opencv_xyz2rgb"; +// "raw_xyz2uint16", "opencv_xyz2uint16"; + +// "deconvlucy", "opencv_deconvlucy"; +// "imhistmatch", "opencv_imhistmatch"; +// "graycoprops", "opencv_graycoprops"; +// "graydiffweight", "opencv_graydiffweight"; +// "decorrstretch", "opencv_decorrstretch"; +// "adaptf", "opencv_adapthisteq"; +// "affine2d", "opencv_affine2d"; + + +// "approxpolyDP","approxpolyDP"; +// "arclenght","arclenght"; +// "bilateralfilter","bilateralfilter"; +// "borderInterpolate","borderInterpolate"; +// "boxfilter","boxfilter"; +// "contourarea","contourarea"; +// "boxfilter","boxfilter"; +// "fitellipse","fitellipse"; +// "getkerneltype","getkerneltype"; +// "histeq","histeq"; + "raw_imrotate","opencv_imrotate"; +// "mean1","mean1"; +// "minAreaRect","minAreaRect"; +// "minimumenclosingcirlce","minimumenclosingcirlce"; +// "pyrMeanShiftFiltering","pyrMeanShiftFiltering"; + "raw_rgb2gray","opencv_rgb2gray"; +// "warpaffine","warpaffine"; + + + + ]; + +Files = [ +// "dctmtx.cpp", + +// "multithresh.cpp", +// "opencv_applycform.cpp", + //"opencv_arrowedline.cpp", + "opencv_blur.cpp", +// "opencv_boundingRect.cpp", +// "opencv_bwconvhull.cpp", +// "opencv_bwdistgeodesic.cpp", +// "opencv_bwlookup.cpp", +// "opencv_canny.cpp", + "opencv_circle.cpp", +// "opencv_clipline.cpp", +// "opencv_convexhull.cpp", +// "opencv_convmtx2.cpp", +// "opencv_copymakeborder.cpp", +// "opencv_corner.cpp", +// "opencv_cornerEigenValsAndVecs.cpp", +// "opencv_cornerHarris.cpp", +// "opencv_cornerMinEigenVal.cpp", +// "opencv_cvtColor.cpp", +// "opencv_demosaic.cpp", + "opencv_dilate.cpp", + "opencv_ellipse.cpp", +// "opencv_ellipse2poly.cpp", + "opencv_erode.cpp", +// "opencv_fftshift.cpp", +// "opencv_fillconvexpoly.cpp", +// "opencv_filter2D.cpp", +// "opencv_findContours.cpp", +// "opencv_fsamp2.cpp", + +// "opencv_gabor.cpp", +// "opencv_gaussianblur.cpp", +// "opencv_getStructuringElement.cpp", +// "opencv_getTextSize.cpp", +// "opencv_getgaussiankernel.cpp", +// "opencv_getrectsubpix.cpp", +// "opencv_getrotationmatrix2D.cpp", +// "opencv_goodfeaturestotrack.cpp", + +// "opencv_houghcircles.cpp", +// "opencv_houghlines.cpp", +// "opencv_houghlinesp.cpp", +// "opencv_ifftshift.cpp", +// "opencv_im2double.cpp", +// "opencv_imabsdiff.cpp", +// "opencv_imadd.cpp", +// "opencv_imattributes.cpp", +// "opencv_imboxfilt3.cpp", +// "opencv_imcomplement.cpp", +// "opencv_imcontour.cpp", +// "opencv_imcontrast.cpp", + "opencv_imcrop.cpp", +// "opencv_imdivide.cpp", +// "opencv_imextendedmax.cpp", +// "opencv_imextendedmin.cpp", +// "opencv_imfill.cpp", +// "opencv_imfindcircles.cpp", +// "opencv_imfuse.cpp", +// "opencv_imgaborfilt.cpp", +// "opencv_imgaussfilt3.cpp", +// "opencv_imguidedfilter.cpp", +// "opencv_imhmax.cpp", +// "opencv_imhmin.cpp", +// "opencv_imimposemin.cpp", +// "opencv_imlincomb.cpp", +// "opencv_immultiply.cpp", + "opencv_impixel.cpp", +// "opencv_impyramid.cpp", + "opencv_imread.cpp", +// "opencv_imrect.cpp", + "opencv_imresize.cpp", + "opencv_imsharpen.cpp", +// "opencv_imshowpair.cpp", +// "opencv_imsubtract.cpp", +// "opencv_imwarp.cpp", + "opencv_imwrite.cpp", +// "opencv_ind2gray.cpp", +// "opencv_ind2rgb.cpp", +// "opencv_lab2double.cpp", +// "opencv_lab2rgb.cpp", +// "opencv_lab2uint16.cpp", +// "opencv_lab2uint8.cpp", +// "opencv_lab2xyz.cpp", +// "opencv_laplacian.cpp", +// "opencv_line.cpp", + +// "opencv_medianblur.cpp", +// "opencv_montage.cpp", +// "opencv_morphologyEx.cpp", +// "opencv_ntsc2rgb.cpp", +// "opencv_puttext.cpp", +// "opencv_pyrDown.cpp", +// "opencv_pyrUp.cpp", +// "opencv_rectangle.cpp", +// "opencv_regionfill.cpp", +// "opencv_rgb2lab.cpp", +// "opencv_rgb2ntsc.cpp", +// "opencv_rgb2xyz.cpp", +// "opencv_roifill.cpp", +// "opencv_roipoly.cpp", +// "opencv_scharr.cpp", +// "opencv_sepFilter2D.cpp", +// "opencv_sobel.cpp", +// "opencv_ssim.cpp", +// "opencv_threshold.cpp", +// "opencv_undistort.cpp", +// "opencv_viscircles.cpp", +// "opencv_watershed.cpp", +// "opencv_whitepoint.cpp", +// "opencv_wiener2.cpp", +// "opencv_xyz2double.cpp", +// "opencv_xyz2lab.cpp", +// "opencv_xyz2rgb.cpp", +// "opencv_xyz2uint16.cpp", + + +// "opencv_deconvlucy.cpp", +// "opencv_integralImage.cpp", +// "opencv_imhistmatch.cpp", +// "opencv_graycoprops.cpp", +// "opencv_graydiffweight.cpp", +// "opencv_decorrstretch.cpp", +// "opencv_adapthisteq.cpp", +// "opencv_affine2d.cpp", + + "rgb2gray.cpp", +// "warpaffine.cpp", +// "opencv_pyrMeanShiftFiltering.cpp", +// "opencv_minimumenclosingcirlce.cpp", +// "opencv_minAreaRect.cpp", +// "opencv_mean1.cpp", + "opencv_imrotate.cpp", +// "opencv_getkerneltype.cpp", +// "opencv_fitellipse.cpp", +// "opencv_contourarea.cpp", +// "opencv_boxfilter.cpp", +// "opencv_borderInterpolate.cpp", +// "opencv_bilateralfilter.cpp", +// "opencv_arclength.cpp", +// "opencv_approxpolyDP.cpp", +// "opencv_histeq.cpp", + + + + ]; + + copyfile("/home/fossee/Desktop/FOSSEE_Image_Processing_Toolbox/sci_gateway/cpp/common.h",TMPDIR); + copyfile("/home/fossee/Desktop/FOSSEE_Image_Processing_Toolbox/sci_gateway/cpp/common.cpp",TMPDIR); + + [a, opt] = getversion(); + Version = opt(2); + + if getos()=="Windows" then +// third_dir = path_builder+filesep()+'..'+filesep()+'..'+filesep()+'thirdparty'; +// lib_base_dir = third_dir + filesep() + 'windows' + filesep() + 'lib' + filesep() + Version + filesep(); +// inc_base_dir = third_dir + filesep() + 'windows' + filesep() + 'include' + filesep() + 'coin'; +// C_Flags=['-D__USE_DEPRECATED_STACK_FUNCTIONS__ -w -I '+path_builder+' '+ '-I '+inc_base_dir+' '] +// Linker_Flag = [lib_base_dir+"libClp.lib "+lib_base_dir+"libCgl.lib "+lib_base_dir+"libOsi.lib "+lib_base_dir+"libOsiClp.lib "+lib_base_dir+"libCoinUtils.lib "+lib_base_dir+"libSymphony.lib "+lib_base_dir+"IpOptFSS.lib "+lib_base_dir+"IpOpt-vc10.lib "] + +else + third_dir = path_builder+'..'+filesep()+'..'+filesep()+'thirdparty'; + lib_base_dir = third_dir + filesep() + 'linux' + filesep() + 'lib' + filesep() + Version + filesep(); + inc_base_dir = third_dir + filesep() + 'linux' + filesep() + 'include' + filesep() + 'opencv'; + incl_base_dir = third_dir + filesep() + 'linux' + filesep() + 'include' + filesep() + 'opencv2'; + +// C_Flags=["-D__USE_DEPRECATED_STACK_FUNCTIONS__ -w -fpermissive -I"+path_builder+"-I"+inc_base_dir+" "+"-I"+incl_base_dir+" -Wl,-rpath= "+lib_base_dir+" "+"-L"+lib_base_dir+"libopencv_core"+" "+"-L"+lib_base_dir+"libopencv_highgui"+" "+"-L"+lib_base_dir+"libopencv_imgproc" ] + +// export LD_LIBRARY_PATH="$LD_LIBRARY_PATH:"+lib_base_dir +// unix_s("export LD_LIBRARY_PATH="+lib_base_dir); + +// C_Flags=["-I"+inc_base_dir+" "+"-I"+incl_base_dir]; +// Linker_Flag = ["-L"+lib_base_dir+"libopencv_core"+" "+"-L"+lib_base_dir+"libopencv_highgui"+" "+"-L"+lib_base_dir+"libopencv_imgproc" ]; + +// Linker_Flag = ["-L/home/fossee/Desktop/FOSSEE_Image_Processing_Toolbox/thirdparty/linux/lib/x64 -lopencv_core -L/home/fossee/Desktop/FOSSEE_Image_Processing_Toolbox/thirdparty/linux/lib/x64 -lopencv_imgproc -L/home/fossee/Desktop/FOSSEE_Image_Processing_Toolbox/thirdparty/linux/lib/x64 -lopencv_highgui" ] + +unix_s("export LD_LIBRARY_PATH="+tools_path+"lib/"+Version+filesep()+" "); +tools_path = path_builder + "../../thirdparty/linux/"; + +C_Flags=["-w -fpermissive -I"+tools_path+"include/opencv -I"+tools_path+"include/opencv2 -Wl,-rpath="+tools_path+"lib/"+Version+filesep()+" "] + +Linker_Flag = ["-L"+tools_path+"lib/"+Version+"-lopencv_shape -lopencv_stitching -lopencv_objdetect -lopencv_superres -lopencv_videostab -lopencv_calib3d -lopencv_features2d -lopencv_highgui -lopencv_video -lopencv_photo -lopencv_ml -lopencv_imgproc -lopencv_flann -lopencv_core "] + +end + +tbx_build_gateway(toolbox_title,Names,Files,get_absolute_file_path("builder_gateway_cpp.sce"), [], Linker_Flag, C_Flags,"g++"); + +clear toolbox_title Names Files Linker_Flag C_Flags; + +//function builder_gw_cpp() +// WITHOUT_AUTO_PUTLHSVAR = %t; +// copyfile("/home/fossee/Desktop/FOSSEE_Image_Processing_Toolbox/sci_gateway/cpp/common.h",TMPDIR); +// copyfile("/home/fossee/Desktop/FOSSEE_Image_Processing_Toolbox/sci_gateway/cpp/common.cpp",TMPDIR); +//tbx_build_gateway("skeleton_imageprocessing", .. +// names, .. +// files, .. +// get_absolute_file_path("builder_gateway_cpp.sce"),[],["-L/usr/local/lib -lopencv_core -L/usr/local/lib -lopencv_highgui -L/usr/lib -lopencv_imgproc -L/usr/lib -lopencv_calib3d -L/usr/lib -lopencv_video -L/usr/lib -lopencv_nonfree -L/usr/lib -lopencv_ml -L/usr/lib -lopencv_objdetect"],["-I/usr/include/scilab -I/usr/include/opencv -I/usr/include/opencv2 "],"g++ "); +//endfunction + +//builder_gw_cpp(); +//clear builder_gw_cpp; // remove builder_gw_cpp on stack + diff --git a/sci_gateway/cpp/cleaner.sce b/sci_gateway/cpp/cleaner.sce new file mode 100644 index 0000000..12b9fbb --- /dev/null +++ b/sci_gateway/cpp/cleaner.sce @@ -0,0 +1,22 @@ +// This file is released under the 3-clause BSD license. See COPYING-BSD. +// Generated by builder.sce : Please, do not edit this file +// cleaner.sce +// ------------------------------------------------------ +curdir = pwd(); +cleaner_path = get_file_path('cleaner.sce'); +chdir(cleaner_path); +// ------------------------------------------------------ +if fileinfo('loader.sce') <> [] then + mdelete('loader.sce'); +end +// ------------------------------------------------------ +if fileinfo('libskeleton_imageprocessing.so') <> [] then + mdelete('libskeleton_imageprocessing.so'); +end +// ------------------------------------------------------ +if fileinfo('libskeleton_imageprocessing.c') <> [] then + mdelete('libskeleton_imageprocessing.c'); +end +// ------------------------------------------------------ +chdir(curdir); +// ------------------------------------------------------ diff --git a/sci_gateway/cpp/common.cpp~ b/sci_gateway/cpp/common.cpp~ new file mode 100644 index 0000000..c19f58a --- /dev/null +++ b/sci_gateway/cpp/common.cpp~ @@ -0,0 +1,890 @@ +/*************************************************** +Author : Sukul Bagai +***************************************************/ + +//takes the matrix type as parameter and returns a string of the type +string type2str(int type) +{ + string r; + uchar depth = type & CV_MAT_DEPTH_MASK; + switch ( depth ) + { + case CV_8U: r = "8U"; break; + case CV_8S: r = "8S"; break; + case CV_16U: r = "16U"; break; + case CV_16S: r = "16S"; break; + case CV_32S: r = "32S"; break; + case CV_32F: r = "32F"; break; + case CV_64F: r = "64F"; break; + default: r = "User"; break; + } + return r; +} + +//takes matrix type as parameter and returns no. of channels of the image matrix +int no_of_channels(int type) +{ + uchar chans = 1 + (type >> CV_CN_SHIFT); + return chans; +} + +//function used to retrieve image matrix from Scilab environment +/* + We need to retrieve image from the Scilab environment + We do this by getting a List of 2-D matrices. The size of the list, in our case is known(either 3 or 1, + 3 for a coloured image and 1 for a grayscale image), hence we do not require the dynamic capability of a list. + Incase of a 3-channel image, the first matrix will be a matrix with dimensions img.rows X img.cols, and will denote the R(red) + values of the image. Similarly, the second will have the G(green) values, and the third will have B(blue) values. + For a single-channeled image, we will have only a single matrix +*/ +int retrieveImage(Mat &image,int pos) +{ + + SciErr sciErr; + int iRows=0,iCols=0,i,j,k=0; + int *piAddr = NULL; + int *piAddrChild = NULL; + int iPrec = 0,iItem = 0; + + //retrieving number of items in the list and type of data(integer/float) + sciErr = getVarAddressFromPosition(pvApiCtx,pos,&piAddr); + if(sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + sciErr = getListItemAddress(pvApiCtx,piAddr,1,&piAddrChild); + if(sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + sciErr = getListItemNumber(pvApiCtx,piAddr,&iItem); + if(sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + + if(isIntegerType(pvApiCtx, piAddrChild)) + { + //getting precision + sciErr = getMatrixOfIntegerPrecision(pvApiCtx, piAddrChild, &iPrec); + if(sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + switch(iPrec) + { + case SCI_UINT8: //for unsigned integer 8 + { + if(iItem==3) + { + unsigned char *pstDataR = NULL; + unsigned char *pstDataG = NULL; + unsigned char *pstDataB = NULL; + sciErr = getVarAddressFromPosition(pvApiCtx,pos,&piAddr); + if(sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + //retrive the matrix of the R values + sciErr = getMatrixOfUnsignedInteger8InList(pvApiCtx, piAddr, 1, &iRows, &iCols, &pstDataR); + if(sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + //retrive address of the list + sciErr = getVarAddressFromPosition(pvApiCtx,pos,&piAddr); + if(sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + //retrive the matrix of the G values + sciErr = getMatrixOfUnsignedInteger8InList(pvApiCtx, piAddr, 2, &iRows, &iCols, &pstDataG); + if(sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + //retrive address of the list + sciErr = getVarAddressFromPosition(pvApiCtx,pos,&piAddr); + if(sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + //retrive the matrix of the B values + sciErr = getMatrixOfUnsignedInteger8InList(pvApiCtx, piAddr, 3, &iRows, &iCols, &pstDataB); + if(sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + + //creating an image matrix with the no. of rows and columns we retrieved, and assigning it to be of the form 8-bit unsinged integers + image = Mat(iRows,iCols,CV_8UC3); + + /*Now that we have the 3 matrices(R,G,B), we need to assign those values to the pixels. The following code does this*/ + k=0; + for(i=0;i(i,j)[2]=pstDataR[i+iRows*j]; + image.at(i,j)[1]=pstDataG[i+iRows*j]; + image.at(i,j)[0]=pstDataB[i+iRows*j]; + } + } + } + else + { + unsigned char *pstDataR = NULL; + sciErr = getVarAddressFromPosition(pvApiCtx,pos,&piAddr); + if(sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + //retrive the matrix of the R values + sciErr = getMatrixOfUnsignedInteger8InList(pvApiCtx, piAddr, 1, &iRows, &iCols, &pstDataR); + if(sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + + //creating an image matrix with the no. of rows and columns we retrieved, and assigning it to be of the form 8-bit unsinged integers + image = Mat(iRows,iCols,CV_8UC1); + + //Assigning matrix value to pixel + k=0; + for(i=0;i(i,j)=pstDataR[i+iRows*j]; + } + break; + } + case SCI_UINT16: //for unsigned integer 16 + { + if(iItem==3) + { + short unsigned int *pstDataR = NULL; + short unsigned int *pstDataG = NULL; + short unsigned int *pstDataB = NULL; + sciErr = getVarAddressFromPosition(pvApiCtx,pos,&piAddr); + if(sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + //retrive the matrix of the R values + sciErr = getMatrixOfUnsignedInteger16InList(pvApiCtx, piAddr, 1, &iRows, &iCols, &pstDataR); + if(sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + //retrive address of the list + sciErr = getVarAddressFromPosition(pvApiCtx,pos,&piAddr); + if(sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + //retrive the matrix of the G values + sciErr = getMatrixOfUnsignedInteger16InList(pvApiCtx, piAddr, 2, &iRows, &iCols, &pstDataG); + if(sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + //retrive address of the list + sciErr = getVarAddressFromPosition(pvApiCtx,pos,&piAddr); + if(sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + //retrive the matrix of the B values + sciErr = getMatrixOfUnsignedInteger16InList(pvApiCtx, piAddr, 3, &iRows, &iCols, &pstDataB); + if(sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + + //creating an image matrix with the no. of rows and columns we retrieved, and assigning it to be of the form 8-bit unsinged integers + image = Mat(iRows,iCols,CV_16UC3); + + //Now that we have the 3 matrices(R,G,B), we need to assign those values to the pixels. The following code does this + k=0; + for(i=0;i(i,j)[2]=pstDataR[i+iRows*j]; + image.at(i,j)[1]=pstDataG[i+iRows*j]; + image.at(i,j)[0]=pstDataB[i+iRows*j]; + //i+iRows*j + } + } + } + else + { + short unsigned int *pstDataR = NULL; + sciErr = getVarAddressFromPosition(pvApiCtx,pos,&piAddr); + if(sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + //retrive the matrix of the R values + sciErr = getMatrixOfUnsignedInteger16InList(pvApiCtx, piAddr, 1, &iRows, &iCols, &pstDataR); + if(sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + + //creating an image matrix with the no. of rows and columns we retrieved, and assigning it to be of the form 8-bit unsinged integers + image = Mat(iRows,iCols,CV_16UC1); + + //Assigning matrix values to pixels + k=0; + for(i=0;i(i,j)=pstDataR[i+iRows*j]; + } + break; + } + case SCI_INT16: //for signed integer 16 + { + if(iItem==3) + { + short int *pstDataR = NULL; + short int *pstDataG = NULL; + short int *pstDataB = NULL; + sciErr = getVarAddressFromPosition(pvApiCtx,pos,&piAddr); + if(sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + //retrive the matrix of the R values + sciErr = getMatrixOfInteger16InList(pvApiCtx, piAddr, 1, &iRows, &iCols, &pstDataR); + if(sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + //retrive address of the list + sciErr = getVarAddressFromPosition(pvApiCtx,pos,&piAddr); + if(sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + //retrive the matrix of the G values + sciErr = getMatrixOfInteger16InList(pvApiCtx, piAddr, 2, &iRows, &iCols, &pstDataG); + if(sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + //retrive address of the list + sciErr = getVarAddressFromPosition(pvApiCtx,pos,&piAddr); + if(sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + //retrive the matrix of the B values + sciErr = getMatrixOfInteger16InList(pvApiCtx, piAddr, 3, &iRows, &iCols, &pstDataB); + if(sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + + //creating an image matrix with the no. of rows and columns we retrieved, and assigning it to be of the form 8-bit unsinged integers + image = Mat(iRows,iCols,CV_16SC3); + + //Now that we have the 3 matrices(R,G,B), we need to assign those values to the pixels. The following code does this + k=0; + for(i=0;i(i,j)[2]=pstDataR[i+iRows*j]; + image.at(i,j)[1]=pstDataG[i+iRows*j]; + image.at(i,j)[0]=pstDataB[i+iRows*j]; + } + } + } + else + { + short int *pstDataR = NULL; + sciErr = getVarAddressFromPosition(pvApiCtx,pos,&piAddr); + if(sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + //retrive the matrix of the R values + sciErr = getMatrixOfInteger16InList(pvApiCtx, piAddr, 1, &iRows, &iCols, &pstDataR); + if(sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + + //creating an image matrix with the no. of rows and columns we retrieved, and assigning it to be of the form 8-bit unsinged integers + image = Mat(iRows,iCols,CV_16SC1); + + //Assigning image matrix values to pixels + k=0; + for(i=0;i(i,j)=pstDataR[i+iRows*j]; + } + break; + } + } + } + else //for floating point/ double precision values + { + if(iItem==3) + { + double *pstDataR = NULL; + double *pstDataG = NULL; + double *pstDataB = NULL; + sciErr = getVarAddressFromPosition(pvApiCtx,pos,&piAddr); + if(sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + //retrive the matrix of the R values + sciErr = getMatrixOfDoubleInList(pvApiCtx, piAddr, 1, &iRows, &iCols, &pstDataR); + if(sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + //retrive address of the list + sciErr = getVarAddressFromPosition(pvApiCtx,pos,&piAddrChild); + if(sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + //retrive the matrix of the G values + sciErr = getMatrixOfDoubleInList(pvApiCtx, piAddr, 2, &iRows, &iCols, &pstDataG); + if(sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + //retrive address of the list + sciErr = getVarAddressFromPosition(pvApiCtx,pos,&piAddrChild); + if(sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + //retrive the matrix of the B values + sciErr = getMatrixOfDoubleInList(pvApiCtx, piAddr, 3, &iRows, &iCols, &pstDataB); + if(sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + + //creating an image matrix with the no. of rows and columns we retrieved, and assigning it to be of the form 8-bit unsinged integers + image = Mat(iRows,iCols,CV_64FC3); + + //Now that we have the 3 matrices(R,G,B), we need to assign those values to the pixels. The following code does this + k=0; + for(i=0;i(i,j)[2]=pstDataR[i+iRows*j]; + image.at(i,j)[1]=pstDataG[i+iRows*j]; + image.at(i,j)[0]=pstDataB[i+iRows*j]; + } + } + } + else + { + double *pstDataR = NULL; + sciErr = getVarAddressFromPosition(pvApiCtx,pos,&piAddr); + if(sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + //retrive the matrix of the R values + sciErr = getMatrixOfDoubleInList(pvApiCtx, piAddr, 1, &iRows, &iCols, &pstDataR); + if(sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + + //creating an image matrix with the no. of rows and columns we retrieved, and assigning it to be of the form 8-bit unsinged integers + image = Mat(iRows,iCols,CV_64FC1); + + //Assigning image matrix values to pixels + k=0; + for(i=0;i(i,j)=pstDataR[i+iRows*j]; + } + } + return 1; +} + +//function that returns an image matrix to the Scilab environment +/* + What we now need, is to pass the image matrix to the Scilab environment. + We do this by passing a List of 2-D matrices. The size of the list, in our case is known(either 3 or 1, + 3 for a coloured image and 1 for a grayscale image), hence we do not require the dynamic capability of a list. + Incase of a 3-channel image, the first matrix will be a matrix with dimensions img.rows X img.cols, and will denote the R(red) + values of the image. Similarly, the second will have the G(green) values, and the third will have B(blue) values. + For a single-channeled image, we will have only a single matrix +*/ +int returnImage(char *checker,Mat img,int pos) +{ + int i,j,k=0; + int *piAddrNew = NULL; + SciErr sciErr; + int num=no_of_channels(img.type()); //num now contains no. of channels of the image + //creating the list that will be passed to the Scilab enviroment + if(num==3) + sciErr = createList(pvApiCtx, nbInputArgument(pvApiCtx) + pos, 3, &piAddrNew); + else + sciErr = createList(pvApiCtx, nbInputArgument(pvApiCtx) + pos, 1, &piAddrNew); + if(sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + if(strcmp(checker,"8U")==0) //for Unsigned Integer 8 + { + if(num==3) + { + //Since we need to pass a single pointer as an arguement, for a 2-D matrix, we define it in this manner + unsigned char *r = (unsigned char *)malloc(img.rows * img.cols * sizeof(unsigned char)); + unsigned char *g = (unsigned char *)malloc(img.rows * img.cols * sizeof(unsigned char)); + unsigned char *b = (unsigned char *)malloc(img.rows * img.cols * sizeof(unsigned char)); + + //The next block of code retrieves the RGB values at a specified pixel, and assigns it to the matrices + for(i=0;i(i, j); + r [i+img.rows*j]=intensity.val[2]; + g [i+img.rows*j]=intensity.val[1]; + b [i+img.rows*j]=intensity.val[0]; + } + } + + + //Adding the R value matrix to the list + sciErr = createMatrixOfUnsignedInteger8InList(pvApiCtx, nbInputArgument(pvApiCtx)+pos , piAddrNew, 1, img.rows,img.cols, r); + free(r); + if(sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + + //Adding the G value matrix to the list + sciErr = createMatrixOfUnsignedInteger8InList(pvApiCtx, nbInputArgument(pvApiCtx)+pos , piAddrNew, 2, img.rows,img.cols,g); + free(g); + if(sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + + //Adding the B value matrix to the list + sciErr = createMatrixOfUnsignedInteger8InList(pvApiCtx, nbInputArgument(pvApiCtx)+pos , piAddrNew, 3, img.rows,img.cols, b); + free(b); + if(sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + } + else + { + //Since we need to pass a single pointer as an arguement, for a 2-D matrix, we define it in this manner + unsigned char *r = (unsigned char *)malloc(img.rows * img.cols * sizeof(unsigned char)); + + //The next block of code retrieves the image colour values at a specified pixel, and assigns it to the matrices + for(i=0;i(i, j); + + + //Adding the image colour value matrix to the list + sciErr = createMatrixOfUnsignedInteger8InList(pvApiCtx, nbInputArgument(pvApiCtx)+pos , piAddrNew, 1,img.rows,img.cols, r); + free(r); + if(sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + + } + } + else if(strcmp(checker,"16U")==0) //for Unsigned Integer 16 + { + if(num==3) + { + //Since we need to pass a single pointer as an arguement, for a 2-D matrix, we define it in this manner + short unsigned int *r = (short unsigned int *)malloc(img.rows * img.cols * sizeof(short unsigned int)); + short unsigned int *g = (short unsigned int *)malloc(img.rows * img.cols * sizeof(short unsigned int)); + short unsigned int *b = (short unsigned int *)malloc(img.rows * img.cols * sizeof(short unsigned int)); + + //The next block of code retrieves the RGB values at a specified pixel, and assigns it to the matrices + for(i=0;i(i, j); + r[i+img.rows*j]=intensity.val[2]; + g[i+img.rows*j]=intensity.val[1]; + b[i+img.rows*j]=intensity.val[0]; + } + } + + //Adding the R value matrix to the list + sciErr = createMatrixOfUnsignedInteger16InList(pvApiCtx, nbInputArgument(pvApiCtx)+pos , piAddrNew, 1, img.rows,img.cols,r); + free(r); + if(sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + + //Adding the G value matrix to the list + sciErr = createMatrixOfUnsignedInteger16InList(pvApiCtx, nbInputArgument(pvApiCtx)+pos , piAddrNew, 2, img.rows,img.cols,g); + free(g); + if(sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + + //Adding the B value matrix to the list + sciErr = createMatrixOfUnsignedInteger16InList(pvApiCtx, nbInputArgument(pvApiCtx)+pos , piAddrNew, 3, img.rows,img.cols, b); + free(b); + if(sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + } + else + { + //Since we need to pass a single pointer as an arguement, for a 2-D matrix, we define it in this manner + short unsigned int *r = (short unsigned int *)malloc(img.rows * img.cols * sizeof(short unsigned int)); + + //The next block of code retrieves the image colour values at a specified pixel, and assigns it to the matrices + for(i=0;i(i, j); + + //Adding the image colour value matrix to the list + sciErr = createMatrixOfUnsignedInteger16InList(pvApiCtx, nbInputArgument(pvApiCtx)+pos , piAddrNew, 1, img.rows,img.cols,r); + free(r); + if(sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + } + + } + else if(strcmp(checker,"16S")==0) //for Signed Integer 16 + { + if(num==3) + { + //Since we need to pass a single pointer as an arguement, for a 2-D matrix, we define it in this manner + short int *r = (short int *)malloc(img.rows * img.cols * sizeof(short int)); + short int *g = (short int *)malloc(img.rows * img.cols * sizeof(short int)); + short int *b = (short int *)malloc(img.rows * img.cols * sizeof(short int)); + //The next block of code retrieves the RGB values at a specified pixel, and assigns it to the matrices + for(i=0;i(i, j); + r[i+img.rows*j]=intensity.val[2]; + g[i+img.rows*j]=intensity.val[1]; + b[i+img.rows*j]=intensity.val[0]; + } + } + + //Adding the R value matrix to the list + sciErr = createMatrixOfInteger16InList(pvApiCtx, nbInputArgument(pvApiCtx)+pos , piAddrNew, 1, img.rows,img.cols, r); + free(r); + if(sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + + //Adding the G value matrix to the list + sciErr = createMatrixOfInteger16InList(pvApiCtx, nbInputArgument(pvApiCtx)+pos , piAddrNew, 2, img.rows,img.cols, g); + free(g); + if(sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + + //Adding the B value matrix to the list + sciErr = createMatrixOfInteger16InList(pvApiCtx, nbInputArgument(pvApiCtx)+pos , piAddrNew, 3, img.rows,img.cols,b); + free(b); + if(sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + } + + else + { + //Since we need to pass a single pointer as an arguement, for a 2-D matrix, we define it in this manner + short int *r = (short int *)malloc(img.rows * img.cols * sizeof(short int)); + + //The next block of code retrieves the image colour values at a specified pixel, and assigns it to the matrices + for(i=0;i(i, j); + + //Adding the image colour value matrix to the list + sciErr = createMatrixOfInteger16InList(pvApiCtx, nbInputArgument(pvApiCtx)+pos , piAddrNew, 1, img.rows,img.cols,r); + free(r); + if(sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + + } + } + else if(strcmp(checker,"32S")==0) //for Signed Integer 16 + { + if(num==3) + { + //Since we need to pass a single pointer as an arguement, for a 2-D matrix, we define it in this manner + int *r = (int *)malloc(img.rows * img.cols * sizeof(int)); + int *g = (int *)malloc(img.rows * img.cols * sizeof(int)); + int *b = (int *)malloc(img.rows * img.cols * sizeof(int)); + //The next block of code retrieves the RGB values at a specified pixel, and assigns it to the matrices + for(i=0;i(i, j); + r[i+img.rows*j]=intensity.val[2]; + g[i+img.rows*j]=intensity.val[1]; + b[i+img.rows*j]=intensity.val[0]; + } + } + + //Adding the R value matrix to the list + sciErr = createMatrixOfInteger32InList(pvApiCtx, nbInputArgument(pvApiCtx)+pos , piAddrNew, 1, img.rows,img.cols,r); + free(r); + if(sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + + //Adding the G value matrix to the list + sciErr = createMatrixOfInteger32InList(pvApiCtx, nbInputArgument(pvApiCtx)+pos , piAddrNew, 2, img.rows,img.cols,g); + free(g); + if(sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + + //Adding the B value matrix to the list + sciErr = createMatrixOfInteger32InList(pvApiCtx, nbInputArgument(pvApiCtx)+pos , piAddrNew, 3, img.rows,img.cols,b); + free(b); + if(sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + } + else + { + //Since we need to pass a single pointer as an arguement, for a 2-D matrix, we define it in this manner + int *r = (int *)malloc(img.rows * img.cols * sizeof(int)); + + //The next block of code retrieves the image colour values at a specified pixel, and assigns it to the matrices + for(i=0;i(i, j); + + //Adding the image colour value matrix to the list + sciErr = createMatrixOfInteger32InList(pvApiCtx, nbInputArgument(pvApiCtx)+pos , piAddrNew, 1,img.rows,img.cols, r); + free(r); + if(sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + + } + } + + else if(strcmp(checker,"32F")==0) //for Float 32 + { + if(num==3) + { + //Since we need to pass a single pointer as an arguement, for a 2-D matrix, we define it in this manner + double *r = (double *)malloc(img.rows * img.cols * sizeof(double)); + double *g = (double *)malloc(img.rows * img.cols * sizeof(double)); + double *b = (double *)malloc(img.rows * img.cols * sizeof(double)); + //The next block of code retrieves the RGB values at a specified pixel, and assigns it to the matrices + for(i=0;i(i, j); + r[i+img.rows*j]=intensity.val[2]; + g[i+img.rows*j]=intensity.val[1]; + b[i+img.rows*j]=intensity.val[0]; + } + } + + //Adding the R value matrix to the list + sciErr = createMatrixOfDoubleInList(pvApiCtx, nbInputArgument(pvApiCtx)+pos , piAddrNew, 1, img.rows,img.cols,r); + free(r); + if(sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + + //Adding the G value matrix to the list + sciErr = createMatrixOfDoubleInList(pvApiCtx, nbInputArgument(pvApiCtx)+pos , piAddrNew, 2, img.rows,img.cols,g); + free(g); + if(sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + + //Adding the B value matrix to the list + sciErr = createMatrixOfDoubleInList(pvApiCtx, nbInputArgument(pvApiCtx)+pos , piAddrNew, 3, img.rows,img.cols,b); + free(b); + if(sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + } + else + { + //Since we need to pass a single pointer as an arguement, for a 2-D matrix, we define it in this manner + double *r = (double *)malloc(img.rows * img.cols * sizeof(double)); + //The next block of code retrieves the image colour values at a specified pixel, and assigns it to the matrices + for(i=0;i(i, j); + + //Adding the image colour value matrix to the list + sciErr = createMatrixOfDoubleInList(pvApiCtx, nbInputArgument(pvApiCtx)+pos , piAddrNew, 1,img.rows,img.cols,r); + free(r); + if(sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + } + } + else if(strcmp(checker,"64F")==0) //For Float 64 + { + if(num==3) + { + //Since we need to pass a single pointer as an arguement, for a 2-D matrix, we define it in this manner + double *r = (double *)malloc(img.rows * img.cols * sizeof(double)); + double *g = (double *)malloc(img.rows * img.cols * sizeof(double)); + double *b = (double *)malloc(img.rows * img.cols * sizeof(double)); + //The next block of code retrieves the RGB values at a specified pixel, and assigns it to the matrices + for(i=0;i(i, j); + r[i+img.rows*j]=intensity.val[2]; + g[i+img.rows*j]=intensity.val[1]; + b[i+img.rows*j]=intensity.val[0]; + } + } + + //Adding the R value matrix to the list + sciErr = createMatrixOfDoubleInList(pvApiCtx, nbInputArgument(pvApiCtx)+pos , piAddrNew, 1, img.rows,img.cols,r); + free(r); + if(sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + + //Adding the G value matrix to the list + sciErr = createMatrixOfDoubleInList(pvApiCtx, nbInputArgument(pvApiCtx)+pos , piAddrNew, 2, img.rows,img.cols,g); + free(g); + if(sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + + //Adding the B value matrix to the list + sciErr = createMatrixOfDoubleInList(pvApiCtx, nbInputArgument(pvApiCtx)+pos , piAddrNew, 3, img.rows,img.cols, b); + free(b); + if(sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + } + else + { + //Since we need to pass a single pointer as an arguement, for a 2-D matrix, we define it in this manner + double *r = (double *)malloc(img.rows * img.cols * sizeof(double)); + + //The next block of code retrieves the image colour values at a specified pixel, and assigns it to the matrices + for(i=0;i(i, j); + + //Adding the image colour value matrix to the list + sciErr = createMatrixOfDoubleInList(pvApiCtx, nbInputArgument(pvApiCtx)+pos , piAddrNew, 1, img.rows,img.cols, r); + free(r); + if(sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + } + } + +} diff --git a/sci_gateway/cpp/libskeleton_imageprocessing.c b/sci_gateway/cpp/libskeleton_imageprocessing.c new file mode 100644 index 0000000..73a082b --- /dev/null +++ b/sci_gateway/cpp/libskeleton_imageprocessing.c @@ -0,0 +1,36 @@ +#ifdef __cplusplus +extern "C" { +#endif +#include +#include +#include +#include +static int direct_gateway(char *fname,void F(void)) { F();return 0;}; +extern Gatefunc opencv_imread; +extern Gatefunc opencv_rgb2xyz; +extern Gatefunc opencv_CascadeObjectDetector; +extern Gatefunc opencv_detectKAZEFeatures; +static GenericTable Tab[]={ + {(Myinterfun)sci_gateway_without_putlhsvar,opencv_imread,"raw_imread"}, + {(Myinterfun)sci_gateway_without_putlhsvar,opencv_rgb2xyz,"raw_rgb2xyz"}, + {(Myinterfun)sci_gateway_without_putlhsvar,opencv_CascadeObjectDetector,"raw_CascadeObjectDetector"}, + {(Myinterfun)sci_gateway_without_putlhsvar,opencv_detectKAZEFeatures,"raw_detectKAZEFeatures"}, +}; + +int C2F(libskeleton_imageprocessing)() +{ + Rhs = Max(0, Rhs); + if (*(Tab[Fin-1].f) != NULL) + { + if(pvApiCtx == NULL) + { + pvApiCtx = (StrCtx*)MALLOC(sizeof(StrCtx)); + } + pvApiCtx->pstName = (char*)Tab[Fin-1].name; + (*(Tab[Fin-1].f))(Tab[Fin-1].name,Tab[Fin-1].F); + } + return 0; +} +#ifdef __cplusplus +} +#endif diff --git a/sci_gateway/cpp/libskeleton_imageprocessing.so b/sci_gateway/cpp/libskeleton_imageprocessing.so new file 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