51 lines
1.5 KiB
Python
51 lines
1.5 KiB
Python
# Copyright (c) OpenMMLab. All rights reserved.
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from argparse import ArgumentParser
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from mmengine.utils import revert_sync_batchnorm
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from mmseg.apis import inference_model, init_model, show_result_pyplot
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from mmseg.utils import register_all_modules
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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(
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'--device', default='cuda:0', help='Device used for inference')
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parser.add_argument(
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'--save-dir',
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default=None,
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help='Save file dir for all storage backends.')
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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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parser.add_argument(
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'--title', default='result', help='The image identifier.')
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args = parser.parse_args()
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register_all_modules()
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# build the model from a config file and a checkpoint file
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model = init_model(args.config, args.checkpoint, device=args.device)
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if args.device == 'cpu':
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model = revert_sync_batchnorm(model)
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# test a single image
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result = inference_model(model, args.img)
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# show the results
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show_result_pyplot(
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model,
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args.img, [result],
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title=args.title,
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opacity=args.opacity,
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draw_gt=False,
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show=False if args.save_dir is not None else True,
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save_dir=args.save_dir)
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if __name__ == '__main__':
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main()
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