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| # Copyright (c) OpenMMLab. All rights reserved. | |
| from argparse import ArgumentParser | |
| # import sys | |
| # sys.path.append("..") | |
| # import mmocr | |
| from mmocr.apis.inferencers import MMOCRInferencer | |
| def parse_args(): | |
| parser = ArgumentParser() | |
| parser.add_argument( | |
| 'inputs', type=str, help='Input image file or folder path.') | |
| parser.add_argument( | |
| '--out-dir', | |
| type=str, | |
| default='results/', | |
| help='Output directory of results.') | |
| parser.add_argument( | |
| '--det', | |
| type=str, | |
| default=None, | |
| help='Pretrained text detection algorithm. It\'s the path to the ' | |
| 'config file or the model name defined in metafile.') | |
| parser.add_argument( | |
| '--det-weights', | |
| type=str, | |
| default=None, | |
| help='Path to the custom checkpoint file of the selected det model. ' | |
| 'If it is not specified and "det" is a model name of metafile, the ' | |
| 'weights will be loaded from metafile.') | |
| parser.add_argument( | |
| '--rec', | |
| type=str, | |
| default=None, | |
| help='Pretrained text recognition algorithm. It\'s the path to the ' | |
| 'config file or the model name defined in metafile.') | |
| parser.add_argument( | |
| '--rec-weights', | |
| type=str, | |
| default=None, | |
| help='Path to the custom checkpoint file of the selected recog model. ' | |
| 'If it is not specified and "rec" is a model name of metafile, the ' | |
| 'weights will be loaded from metafile.') | |
| parser.add_argument( | |
| '--kie', | |
| type=str, | |
| default=None, | |
| help='Pretrained key information extraction algorithm. It\'s the path' | |
| 'to the config file or the model name defined in metafile.') | |
| parser.add_argument( | |
| '--kie-weights', | |
| type=str, | |
| default=None, | |
| help='Path to the custom checkpoint file of the selected kie model. ' | |
| 'If it is not specified and "kie" is a model name of metafile, the ' | |
| 'weights will be loaded from metafile.') | |
| parser.add_argument( | |
| '--device', | |
| type=str, | |
| default=None, | |
| help='Device used for inference. ' | |
| 'If not specified, the available device will be automatically used.') | |
| parser.add_argument( | |
| '--batch-size', type=int, default=1, help='Inference batch size.') | |
| parser.add_argument( | |
| '--show', | |
| action='store_true', | |
| help='Display the image in a popup window.') | |
| parser.add_argument( | |
| '--print-result', | |
| action='store_true', | |
| help='Whether to print the results.') | |
| parser.add_argument( | |
| '--save_pred', | |
| action='store_true', | |
| help='Save the inference results to out_dir.') | |
| parser.add_argument( | |
| '--save_vis', | |
| action='store_true', | |
| help='Save the visualization results to out_dir.') | |
| call_args = vars(parser.parse_args()) | |
| init_kws = [ | |
| 'det', 'det_weights', 'rec', 'rec_weights', 'kie', 'kie_weights', | |
| 'device' | |
| ] | |
| init_args = {} | |
| for init_kw in init_kws: | |
| init_args[init_kw] = call_args.pop(init_kw) | |
| return init_args, call_args | |
| def main(): | |
| init_args, call_args = parse_args() | |
| ocr = MMOCRInferencer(**init_args) | |
| ocr(**call_args) | |
| if __name__ == '__main__': | |
| main() | |