61 lines
1.9 KiB
Python
61 lines
1.9 KiB
Python
# 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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import mmcv
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import mmcv_custom # noqa: F401,F403
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import mmdet_custom # noqa: F401,F403
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import os.path as osp
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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('--out', type=str, default="demo", help='out dir')
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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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mmcv.mkdir_or_exist(args.out)
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out_file = osp.join(args.out, osp.basename(args.img))
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# show the results
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model.show_result(
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args.img,
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result,
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score_thr=args.score_thr,
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show=False,
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bbox_color=args.palette,
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text_color=(200, 200, 200),
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mask_color=args.palette,
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out_file=out_file
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)
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print(f"Result is save at {out_file}")
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if __name__ == '__main__':
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args = parse_args()
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main(args) |