Face Recognition

Face Recognition/Facedetect.py

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+import cv2
+
+cap = cv2.VideoCapture(0)
+
+detector = cv2.CascadeClassifier("haarcascade_frontalface_default.xml")
+
+while True:
+
+    ret, frame = cap.read()
+
+    if ret:
+        faces = detector.detectMultiScale(frame)
+
+        for face in faces:
+            x, y, w, h = face
+
+            cut = frame[y:y+h, x:x+w]
+
+            fix = cv2.resize(cut, (100, 100))
+            gray = cv2.cvtColor(fix, cv2.COLOR_BGR2GRAY)
+
+        cv2.imshow("My Screen", frame)
+        cv2.imshow("My Face", gray)
+
+    key = cv2.waitKey(1)
+
+    if key == ord("q"):
+        break
+
+cap.release()
+cv2.destroyAllWindows()

Face Recognition/Facerecog.py

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+import cv2
+import numpy as np
+from sklearn.neighbors import KNeighborsClassifier
+
+data = np.load("face_data.npy")
+
+print(data.shape, data.dtype)
+
+X = data[:, 1:].astype(int)
+y = data[:, 0]
+
+model = KNeighborsClassifier()
+model.fit(X, y)
+
+cap = cv2.VideoCapture(0)
+
+detector = cv2.CascadeClassifier("haarcascade_frontalface_default.xml")
+while True:
+
+    ret, frame = cap.read()
+
+    if ret:
+        faces = detector.detectMultiScale(frame)
+
+        for face in faces:
+            x, y, w, h = face
+
+            cut = frame[y:y+h, x:x+w]
+
+            fix = cv2.resize(cut, (100, 100))
+            gray = cv2.cvtColor(fix, cv2.COLOR_BGR2GRAY)
+
+            out = model.predict([gray.flatten()])
+
+            cv2.rectangle(frame, (x, y), (x+w, y+h), (255, 0, 0), 2)
+
+            cv2.putText(frame, str(out[0]), (x, y - 10), cv2.FONT_HERSHEY_COMPLEX, 2, (255, 0, 0), 2)
+
+            print(out)
+
+            cv2.imshow("My Face", gray)
+
+        cv2.imshow("My Screen", frame)
+
+
+    key = cv2.waitKey(1)
+
+    if key == ord("q"):
+        break
+
+cap.release()
+cv2.destroyAllWindows()

Face Recognition/Facerecog.py~

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+import cv2
+import numpy as np
+from sklearn.neighbors import KNeighborsClassifier
+
+data = np.load("face_data.npy")
+
+print(data.shape, data.dtype)
+
+X = data[:, 1:].astype(int)
+y = data[:, 0]
+
+model = KNeighborsClassifier()
+model.fit(X, y)
+
+cap = cv2.VideoCapture(0)
+
+detector = cv2.CascadeClassifier("../../datasets/haarcascade_frontalface_default.xml")
+while True:
+
+    ret, frame = cap.read()
+
+    if ret:
+        faces = detector.detectMultiScale(frame)
+
+        for face in faces:
+            x, y, w, h = face
+
+            cut = frame[y:y+h, x:x+w]
+
+            fix = cv2.resize(cut, (100, 100))
+            gray = cv2.cvtColor(fix, cv2.COLOR_BGR2GRAY)
+
+            out = model.predict([gray.flatten()])
+
+            cv2.rectangle(frame, (x, y), (x+w, y+h), (255, 0, 0), 2)
+
+            cv2.putText(frame, str(out[0]), (x, y - 10), cv2.FONT_HERSHEY_COMPLEX, 2, (255, 0, 0), 2)
+
+            print(out)
+
+            cv2.imshow("My Face", gray)
+
+        cv2.imshow("My Screen", frame)
+
+
+    key = cv2.waitKey(1)
+
+    if key == ord("q"):
+        break
+
+cap.release()
+cv2.destroyAllWindows()

Face Recognition/face_recog_collector.py

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+import cv2
+import numpy as np
+
+import os
+
+cap = cv2.VideoCapture(0)
+
+detector = cv2.CascadeClassifier("haarcascade_frontalface_default.xml")
+
+name = input("Enter your name : ")
+
+frames = []
+outputs = []
+
+while True:
+
+    ret, frame = cap.read()
+
+    if ret:
+        faces = detector.detectMultiScale(frame)
+
+        for face in faces:
+            x, y, w, h = face
+
+            cut = frame[y:y+h, x:x+w]
+
+            fix = cv2.resize(cut, (100, 100))
+            gray = cv2.cvtColor(fix, cv2.COLOR_BGR2GRAY)
+
+        cv2.imshow("My Screen", frame)
+        cv2.imshow("My Face", gray)
+
+    key = cv2.waitKey(1)
+
+    if key == ord("q"):
+        break
+    if key == ord("c"):
+        #cv2.imwrite(name + ".jpg", frame)
+        frames.append(gray.flatten())
+        outputs.append([name])
+
+X = np.array(frames)
+y = np.array(outputs)
+
+data = np.hstack([y, X])
+
+f_name = "face_data.npy"
+
+if os.path.exists(f_name):
+    old = np.load(f_name)
+    data = np.vstack([old, data])
+
+np.save(f_name, data)
+
+cap.release()
+cv2.destroyAllWindows()