create face detection in image with gpu

yoloface_gpu.py

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+import argparse
+
+from PIL import Image
+from YOLO import YOLO
+
+
+#####################################################################
+def get_args():
+    parser = argparse.ArgumentParser()
+    parser.add_argument('--model', type=str, default='',
+                        help='path to model weights file')
+    parser.add_argument('--anchors', type=str, default='',
+                        help='path to anchor definitions')
+    parser.add_argument('--classes', type=str, default='',
+                        help='path to class definitions')
+    parser.add_argument('--score', type=float, default='',
+                        help='the score threshold')
+    parser.add_argument('--iou', type=float, default='',
+                        help='the iou threshold')
+    parser.add_argument('--img-size', type=list, action='store',
+                        default=(416, 416), help='input image size')
+    parser.add_argument('--image', default=False, action="store_true",
+                        help='image detection mode')
+    parser.add_argument('--output', type=str,
+                        default='', help='image/video output path')
+    args = parser.parse_args()
+    return args
+
+
+def detect_img(yolo):
+    while True:
+        img = input('[i] ==> Input image filename: ')
+        try:
+            image = Image.open(img)
+        except:
+            print('[!] ==> Open Error! Try again!')
+            continue
+        else:
+            res_image = yolo.detect_image(image)
+            res_image.show()
+
+    yolo.close_session()
+
+
+def _main():
+    # Get the arguments
+    args = get_args()
+
+    if args.image:
+        # Image detection mode
+        print('[i] ==> Image detection mode\n')
+        detect_img(YOLO(args))
+    else:
+        print('[i] ==> Video detection mode\n')
+        # Call the detect_video method here
+
+    print('Well done!!!')
+
+
+if __name__ == "__main__":
+    _main()