Add options for demo scripts to select backend & targets (#43)

* add options for selecting backend & targets

* add eol

demo.py

@@ -23,11 +23,25 @@ def str2bool(v):
     else:
         raise NotImplementedError
 
+backends = [cv.dnn.DNN_BACKEND_OPENCV, cv.dnn.DNN_BACKEND_CUDA]
+targets = [cv.dnn.DNN_TARGET_CPU, cv.dnn.DNN_TARGET_CUDA, cv.dnn.DNN_TARGET_CUDA_FP16]
+help_msg_backends = "Choose one of the computation backends: {:d}: OpenCV implementation (default); {:d}: CUDA"
+help_msg_targets = "Chose one of the target computation devices: {:d}: CPU (default); {:d}: CUDA; {:d}: CUDA fp16"
+try:
+    backends += [cv.dnn.DNN_BACKEND_TIMVX]
+    targets += [cv.dnn.DNN_TARGET_NPU]
+    help_msg_backends += "; {:d}: TIMVX"
+    help_msg_targets += "; {:d}: NPU"
+except:
+    print('This version of OpenCV does not support TIM-VX and NPU. Visit https://gist.github.com/fengyuentau/5a7a5ba36328f2b763aea026c43fa45f for more information.')
+
 parser = argparse.ArgumentParser(
     description="SFace: Sigmoid-Constrained Hypersphere Loss for Robust Face Recognition (https://ieeexplore.ieee.org/document/9318547)")
 parser.add_argument('--input1', '-i1', type=str, help='Path to the input image 1.')
 parser.add_argument('--input2', '-i2', type=str, help='Path to the input image 2.')
 parser.add_argument('--model', '-m', type=str, default='face_recognition_sface_2021dec.onnx', help='Path to the model.')
+parser.add_argument('--backend', '-b', type=int, default=backends[0], help=help_msg_backends.format(*backends))
+parser.add_argument('--target', '-t', type=int, default=targets[0], help=help_msg_targets.format(*targets))
 parser.add_argument('--dis_type', type=int, choices=[0, 1], default=0, help='Distance type. \'0\': cosine, \'1\': norm_l1.')
 parser.add_argument('--save', '-s', type=str, default=False, help='Set true to save results. This flag is invalid when using camera.')
 parser.add_argument('--vis', '-v', type=str2bool, default=True, help='Set true to open a window for result visualization. This flag is invalid when using camera.')
@@ -35,13 +49,15 @@ args = parser.parse_args()
 
 if __name__ == '__main__':
     # Instantiate SFace for face recognition
-    recognizer = SFace(modelPath=args.model, disType=args.dis_type)
+    recognizer = SFace(modelPath=args.model, disType=args.dis_type, backendId=args.backend, targetId=args.target)
     # Instantiate YuNet for face detection
     detector = YuNet(modelPath='../face_detection_yunet/face_detection_yunet_2021dec.onnx',
                      inputSize=[320, 320],
                      confThreshold=0.9,
                      nmsThreshold=0.3,
-                     topK=5000)
+                     topK=5000,
+                     backendId=args.backend,
+                     targetId=args.target)
 
     img1 = cv.imread(args.input1)
     img2 = cv.imread(args.input2)
@@ -56,4 +72,5 @@ if __name__ == '__main__':
 
     # Match
     result = recognizer.match(img1, face1[0][:-1], img2, face2[0][:-1])
-    print('Result: {}.'.format('same identity' if result else 'different identities'))
+    print('Result: {}.'.format('same identity' if result else 'different identities'))
+