mirror of
https://github.com/PaddlePaddle/PaddleOCR.git
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73 lines
1.9 KiB
Python
73 lines
1.9 KiB
Python
# Copyright (c) 2025 PaddlePaddle Authors. All Rights Reserved.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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import time
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from .logging import logger
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def str2bool(v, /):
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return v.lower() in ("true", "yes", "t", "y", "1")
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def get_subcommand_args(args):
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args = vars(args).copy()
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args.pop("subcommand")
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args.pop("executor")
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return args
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def add_simple_inference_args(subparser, *, input_help=None):
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if input_help is None:
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input_help = "Input path or URL."
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subparser.add_argument(
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"-i",
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"--input",
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type=str,
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required=True,
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help=input_help,
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)
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subparser.add_argument(
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"--save_path",
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type=str,
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help="Path to the output directory.",
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)
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def perform_simple_inference(wrapper_cls, params, predict_param_names=None):
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params = params.copy()
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input_ = params.pop("input")
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save_path = params.pop("save_path")
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if predict_param_names is not None:
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predict_params = {}
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for name in predict_param_names:
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predict_params[name] = params.pop(name)
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else:
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predict_params = {}
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init_params = params
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wrapper = wrapper_cls(**init_params)
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result = wrapper.predict_iter(input_, **predict_params)
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t1 = time.time()
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for i, res in enumerate(result):
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logger.info(f"Processed item {i} in {(time.time()-t1) * 1000} ms")
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t1 = time.time()
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res.print()
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if save_path:
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res.save_all(save_path)
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