updates
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@ -27,7 +27,7 @@ def detect(
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# Initialize model
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# Initialize model
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if ONNX_EXPORT:
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if ONNX_EXPORT:
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s = (416, 416) # onnx model image size (height, width)
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s = (192, 320) # onnx model image size (height, width)
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model = Darknet(cfg, s)
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model = Darknet(cfg, s)
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else:
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else:
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model = Darknet(cfg, img_size)
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model = Darknet(cfg, img_size)
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@ -121,7 +121,7 @@ if __name__ == '__main__':
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parser = argparse.ArgumentParser()
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parser = argparse.ArgumentParser()
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parser.add_argument('--cfg', type=str, default='cfg/yolov3-spp.cfg', help='cfg file path')
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parser.add_argument('--cfg', type=str, default='cfg/yolov3-spp.cfg', help='cfg file path')
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parser.add_argument('--data-cfg', type=str, default='data/coco.data', help='coco.data file path')
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parser.add_argument('--data-cfg', type=str, default='data/coco.data', help='coco.data file path')
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parser.add_argument('--weights', type=str, default='weights/yolov3-spp.weights', help='path to weights file')
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parser.add_argument('--weights', type=str, default='weights/supermarket2_yolov3-spp-sm2_3000_v0.weights', help='path to weights file')
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parser.add_argument('--images', type=str, default='data/samples', help='path to images')
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parser.add_argument('--images', type=str, default='data/samples', help='path to images')
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parser.add_argument('--img-size', type=int, default=416, help='inference size (pixels)')
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parser.add_argument('--img-size', type=int, default=416, help='inference size (pixels)')
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parser.add_argument('--conf-thres', type=float, default=0.5, help='object confidence threshold')
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parser.add_argument('--conf-thres', type=float, default=0.5, help='object confidence threshold')
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