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from argparse import ArgumentParser |
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import numpy as np |
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import requests |
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from mmocr.apis import init_detector, model_inference |
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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('model_name', help='The model name in the server') |
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parser.add_argument( |
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'--inference-addr', |
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default='127.0.0.1:8080', |
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help='Address and port of the inference server') |
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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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'--score-thr', type=float, default=0.5, help='bbox score threshold') |
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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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model = init_detector(args.config, args.checkpoint, device=args.device) |
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model_results = model_inference(model, args.img) |
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model.show_result( |
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args.img, |
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model_results, |
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win_name='model_results', |
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show=True, |
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score_thr=args.score_thr) |
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url = 'http://' + args.inference_addr + '/predictions/' + args.model_name |
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with open(args.img, 'rb') as image: |
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response = requests.post(url, image) |
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serve_results = response.json() |
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model.show_result( |
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args.img, |
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serve_results, |
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show=True, |
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win_name='serve_results', |
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score_thr=args.score_thr) |
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assert serve_results.keys() == model_results.keys() |
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for key in serve_results.keys(): |
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for model_result, serve_result in zip(model_results[key], |
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serve_results[key]): |
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if isinstance(model_result[0], (int, float)): |
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assert np.allclose(model_result, serve_result) |
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elif isinstance(model_result[0], str): |
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assert model_result == serve_result |
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else: |
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raise TypeError |
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if __name__ == '__main__': |
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args = parse_args() |
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main(args) |
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