mirror of
https://github.com/open-mmlab/mmsegmentation.git
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55 lines
1.6 KiB
Python
55 lines
1.6 KiB
Python
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# Copyright (c) OpenMMLab. All rights reserved.
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from argparse import ArgumentParser
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from mmseg.apis import MMSegInferencer
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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('model', help='Config file')
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parser.add_argument('--checkpoint', default=None, help='Checkpoint file')
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parser.add_argument(
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'--out-dir', default='', help='Path to save result file')
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parser.add_argument(
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'--show',
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action='store_true',
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default=False,
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help='Whether to display the drawn image.')
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parser.add_argument(
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'--save-mask',
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action='store_true',
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default=False,
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help='Enable save the mask file')
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parser.add_argument(
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'--dataset-name',
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default='cityscapes',
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help='Color palette used for segmentation map')
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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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'--opacity',
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type=float,
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default=0.5,
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help='Opacity of painted segmentation map. In (0, 1] range.')
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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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mmseg_inferencer = MMSegInferencer(
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args.model,
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args.checkpoint,
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dataset_name=args.dataset_name,
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device=args.device)
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# test a single image
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mmseg_inferencer(
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args.img,
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show=args.show,
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out_dir=args.out_dir,
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save_mask=args.save_mask,
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opacity=args.opacity)
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if __name__ == '__main__':
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main()
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