Client transpose (#44)

add client option to set transposition direction

Author: dtrawins

example_client/grpc_serving_client.py

@@ -31,10 +31,14 @@
 parser.add_argument('--grpc_address',required=False, default='localhost',  help='Specify url to grpc service. default:localhost')
 parser.add_argument('--grpc_port',required=False, default=9000, help='Specify port to grpc service. default: 9000')
 parser.add_argument('--input_name',required=False, default='input', help='Specify input tensor name. default: input')
-parser.add_argument('--output_name',required=False, default='resnet_v1_50/predictions/Reshape_1', help='Specify output name. default: resnet_v1_50/predictions/Reshape_1')
+parser.add_argument('--output_name',required=False, default='resnet_v1_50/predictions/Reshape_1',
+                    help='Specify output name. default: resnet_v1_50/predictions/Reshape_1')
 parser.add_argument('--transpose_input', choices=["False", "True"], default="True",
-                    help='Set to False to skip NHWC->NCHW input transposing. default: True',
+                    help='Set to False to skip NHWC>NCHW or NCHW>NHWC input transposing. default: True',
                     dest="transpose_input")
+parser.add_argument('--transpose_method', choices=["nchw2nhwc","nhwc2nchw"], default="nhwc2nchw",
+                    help="How the input transposition should be executed: nhwc2nchw or nhwc2nchw",
+                    dest="transpose_method")
 parser.add_argument('--iterations', default=0,
                     help='Number of requests iterations, as default use number of images in numpy memmap. default: 0 (consume all frames)',
                     dest='iterations', type=int)
@@ -78,10 +82,13 @@
 print('\tModel name: {}'.format(args.get('model_name')))
 print('\tIterations: {}'.format(iterations))
 print('\tImages numpy path: {}'.format(args.get('images_numpy_path')))
+if args.get('transpose_input') == "True":
+    if args.get('transpose_method') == "nhwc2nchw":
+        imgs = imgs.transpose((0,3,1,2))
+    if args.get('transpose_method') == "nchw2nhwc":
+        imgs = imgs.transpose((0,2,3,1))
 print('\tImages in shape: {}\n'.format(imgs.shape))
 
-if args.get('transpose_input') == "True":
-    imgs = imgs.transpose((0,3,1,2))
 iteration = 0
 
 while iteration <= iterations: