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from argparse import ArgumentParser
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from mmaction.apis.inferencers import MMAction2Inferencer
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def parse_args():
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parser = ArgumentParser()
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parser.add_argument(
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'inputs', type=str, help='Input video file or rawframes folder path.')
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parser.add_argument(
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'--vid-out-dir',
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type=str,
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default='',
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help='Output directory of videos.')
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parser.add_argument(
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'--rec',
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type=str,
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default=None,
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help='Pretrained action recognition algorithm. It\'s the path to the '
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'config file or the model name defined in metafile.')
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parser.add_argument(
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'--rec-weights',
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type=str,
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default=None,
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help='Path to the custom checkpoint file of the selected recog model. '
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'If it is not specified and "rec" is a model name of metafile, the '
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'weights will be loaded from metafile.')
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parser.add_argument(
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'--label-file', type=str, default=None, help='label file for dataset.')
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parser.add_argument(
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'--device',
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type=str,
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default=None,
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help='Device used for inference. '
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'If not specified, the available device will be automatically used.')
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parser.add_argument(
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'--batch-size', type=int, default=1, help='Inference batch size.')
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parser.add_argument(
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'--show',
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action='store_true',
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help='Display the video in a popup window.')
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parser.add_argument(
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'--print-result',
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action='store_true',
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help='Whether to print the results.')
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parser.add_argument(
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'--pred-out-file',
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type=str,
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default='',
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help='File to save the inference results.')
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call_args = vars(parser.parse_args())
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init_kws = ['rec', 'rec_weights', 'device', 'label_file']
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init_args = {}
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for init_kw in init_kws:
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init_args[init_kw] = call_args.pop(init_kw)
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return init_args, call_args
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def main():
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init_args, call_args = parse_args()
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mmaction2 = MMAction2Inferencer(**init_args)
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mmaction2(**call_args)
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if __name__ == '__main__':
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main()
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