mirror of https://github.com/open-mmlab/mmocr.git
45 lines
1.4 KiB
Python
45 lines
1.4 KiB
Python
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from argparse import ArgumentParser
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import mmcv
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from mmdet.apis import init_detector
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from mmocr.apis.inference import model_inference
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from mmocr.datasets import build_dataset # noqa: F401
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from mmocr.models import build_detector # noqa: F401
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def main():
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parser = ArgumentParser()
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parser.add_argument('img', help='Image file.')
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parser.add_argument('config', help='Config file.')
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parser.add_argument('checkpoint', help='Checkpoint file.')
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parser.add_argument('save_path', help='Path to save visualized image.')
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parser.add_argument(
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'--device', default='cuda:0', help='Device used for inference.')
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parser.add_argument(
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'--imshow',
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action='store_true',
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help='Whether show image with OpenCV.')
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args = parser.parse_args()
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# build the model from a config file and a checkpoint file
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model = init_detector(args.config, args.checkpoint, device=args.device)
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if model.cfg.data.test['type'] == 'ConcatDataset':
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model.cfg.data.test.pipeline = model.cfg.data.test['datasets'][
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0].pipeline
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# test a single image
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result = model_inference(model, args.img)
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print(f'result: {result}')
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# show the results
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img = model.show_result(args.img, result, out_file=None, show=False)
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mmcv.imwrite(img, args.save_path)
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if args.imshow:
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mmcv.imshow(img, 'predicted results')
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if __name__ == '__main__':
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main()
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