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35 lines
833 B
35 lines
833 B
3 years ago
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import argparse
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from model_ENET_SAD import ENet_SAD
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from utils.prob2lines import getLane
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from utils.transforms import *
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img_size = (800, 288)
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net = ENet_SAD(img_size, sad=False)
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mean = (0.485, 0.456, 0.406)
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std = (0.229, 0.224, 0.225)
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transform_img = Resize(img_size)
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transform_to_net = Compose(ToTensor(), Normalize(mean=mean, std=std))
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def parse_args():
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parser = argparse.ArgumentParser()
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parser.add_argument("--img_path", '-i', type=str, default=r"demo/demo.jpg",
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help="Path to demo image")
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parser.add_argument("--weight_path", '-w', type=str, default=r"exp1_best.pth",
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help="Path to model weights")
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args = parser.parse_args()
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return args
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def main():
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########## Begin ##########
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########## End ##########
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if __name__ == "__main__":
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main()
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