OpenMMLab Detection Toolbox and Benchmark
https://mmdetection.readthedocs.io/
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65 lines
2.0 KiB
65 lines
2.0 KiB
# Copyright (c) OpenMMLab. All rights reserved. |
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import asyncio |
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from argparse import ArgumentParser |
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from mmdet.apis import (async_inference_detector, inference_detector, |
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init_detector, show_result_pyplot) |
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def parse_args(): |
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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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'--palette', |
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default='coco', |
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choices=['coco', 'voc', 'citys', 'random'], |
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help='Color palette used for visualization') |
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parser.add_argument( |
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'--score-thr', type=float, default=0.3, help='bbox score threshold') |
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parser.add_argument( |
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'--async-test', |
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action='store_true', |
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help='whether to set async options for async inference.') |
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args = parser.parse_args() |
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return args |
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def main(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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# test a single image |
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result = inference_detector(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, |
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result, |
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palette=args.palette, |
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score_thr=args.score_thr) |
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async def async_main(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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# test a single image |
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tasks = asyncio.create_task(async_inference_detector(model, args.img)) |
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result = await asyncio.gather(tasks) |
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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, |
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result[0], |
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palette=args.palette, |
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score_thr=args.score_thr) |
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if __name__ == '__main__': |
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args = parse_args() |
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if args.async_test: |
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asyncio.run(async_main(args)) |
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else: |
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main(args)
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