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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 pathlib import Path
- from .base import BasePredictor, BasicPredictor
- from .image_classification import ClasPredictor
- from .text_detection import TextDetPredictor
- from .text_recognition import TextRecPredictor
- from .table_recognition import TablePredictor
- from .object_detection import DetPredictor
- from .instance_segmentation import InstanceSegPredictor
- from .official_models import official_models
- def create_predictor(model: str, device: str = None, *args, **kwargs) -> BasePredictor:
- model_dir = check_model(model)
- config = BasePredictor.load_config(model_dir)
- model_name = config["Global"]["model_name"]
- return BasicPredictor.get(model_name)(
- model_dir=model_dir,
- config=config,
- device=device,
- *args,
- **kwargs,
- )
- def check_model(model):
- if Path(model).exists():
- return Path(model)
- elif model in official_models:
- return official_models[model]
- else:
- raise Exception(
- f"The model ({model}) is no exists! Please using directory of local model files or model name supported by PaddleX!"
- )
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