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