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- # Copyright (c) 2024 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.
- from importlib import import_module
- from pathlib import Path
- from typing import Any, Dict, Optional, Union
- from ...utils import errors
- from ..utils.hpi import HPIConfig
- from ..utils.official_models import official_models
- # from .table_recognition import TablePredictor
- # from .general_recognition import ShiTuRecPredictor
- from .anomaly_detection import UadPredictor
- from .base import BasePredictor
- from .common.genai import GenAIConfig, need_local_model
- from .doc_vlm import DocVLMPredictor
- from .face_feature import FaceFeaturePredictor
- from .formula_recognition import FormulaRecPredictor
- from .image_classification import ClasPredictor
- from .image_feature import ImageFeaturePredictor
- from .image_multilabel_classification import MLClasPredictor
- from .image_unwarping import WarpPredictor
- from .instance_segmentation import InstanceSegPredictor
- from .keypoint_detection import KptPredictor
- from .m_3d_bev_detection import BEVDet3DPredictor
- # from .face_recognition import FaceRecPredictor
- from .multilingual_speech_recognition import WhisperPredictor
- from .object_detection import DetPredictor
- from .open_vocabulary_detection import OVDetPredictor
- from .open_vocabulary_segmentation import OVSegPredictor
- from .semantic_segmentation import SegPredictor
- from .table_structure_recognition import TablePredictor
- from .text_detection import TextDetPredictor
- from .text_recognition import TextRecPredictor
- from .ts_anomaly_detection import TSAdPredictor
- from .ts_classification import TSClsPredictor
- from .ts_forecasting import TSFcPredictor
- from .video_classification import VideoClasPredictor
- from .video_detection import VideoDetPredictor
- def create_predictor(
- model_name: str,
- model_dir: Optional[str] = None,
- device: Optional[str] = None,
- pp_option=None,
- use_hpip: bool = False,
- hpi_config: Optional[Union[Dict[str, Any], HPIConfig]] = None,
- genai_config: Optional[Union[Dict[str, Any], GenAIConfig]] = None,
- *args,
- **kwargs,
- ) -> BasePredictor:
- # TODO: Check if the model is a genai model
- if genai_config is not None:
- genai_config = GenAIConfig.model_validate(genai_config)
- if need_local_model(genai_config):
- if model_dir is None:
- assert (
- model_name in official_models
- ), f"The model ({model_name}) is not supported! Please using directory of local model files or model name supported by PaddleX!"
- model_dir = official_models[model_name]
- else:
- assert Path(model_dir).exists(), f"{model_dir} is not exists!"
- model_dir = Path(model_dir)
- config = BasePredictor.load_config(model_dir)
- assert (
- model_name == config["Global"]["model_name"]
- ), f"Model name mismatch,please input the correct model dir."
- else:
- config = None
- return BasePredictor.get(model_name)(
- model_dir=model_dir,
- config=config,
- device=device,
- pp_option=pp_option,
- use_hpip=use_hpip,
- hpi_config=hpi_config,
- genai_config=genai_config,
- model_name=model_name,
- *args,
- **kwargs,
- )
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