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- # copyright (c) 2024 PaddlePaddle Authors. All Rights Reserve.
- #
- # 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.
- from copy import deepcopy
- from ..inference.models import create_model
- from ..inference.utils.pp_option import PaddlePredictorOption
- from ..utils.config import AttrDict
- class Predictor(object):
- def __init__(self, config):
- model_name = config.Global.model
- predict_config = deepcopy(config.Predict)
- model_dir = predict_config.pop("model_dir", None)
- # if model_dir is None, using official
- model = model_name if model_dir is None else model_dir
- self.input_path = predict_config.pop("input_path")
- pp_option = PaddlePredictorOption(**predict_config.pop("kernel_option", {}))
- self.model = create_model(model, pp_option=pp_option, **predict_config)
- def predict(self):
- for res in self.model(self.input_path):
- res.print()
- def build_predictor(config: AttrDict):
- """build predictor by config for dev"""
- return Predictor(config)
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