# 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. from .._utils.cli import ( add_simple_inference_args, get_subcommand_args, perform_simple_inference, str2bool, ) from .base import PaddleXPipelineWrapper, PipelineCLISubcommandExecutor from .utils import create_config_from_structure class DocPreprocessor(PaddleXPipelineWrapper): def __init__( self, doc_orientation_classify_model_name=None, doc_orientation_classify_model_dir=None, doc_unwarping_model_name=None, doc_unwarping_model_dir=None, use_doc_orientation_classify=None, use_doc_unwarping=None, **kwargs, ): self._params = { "doc_orientation_classify_model_name": doc_orientation_classify_model_name, "doc_orientation_classify_model_dir": doc_orientation_classify_model_dir, "doc_unwarping_model_name": doc_unwarping_model_name, "doc_unwarping_model_dir": doc_unwarping_model_dir, "use_doc_orientation_classify": use_doc_orientation_classify, "use_doc_unwarping": use_doc_unwarping, } super().__init__(**kwargs) @property def _paddlex_pipeline_name(self): return "doc_preprocessor" def predict_iter( self, input, *, use_doc_orientation_classify=None, use_doc_unwarping=None, ): return self.paddlex_pipeline.predict( input, use_doc_orientation_classify=use_doc_orientation_classify, use_doc_unwarping=use_doc_unwarping, ) def predict( self, input, *, use_doc_orientation_classify=None, use_doc_unwarping=None, ): return list( self.predict_iter( input, use_doc_orientation_classify=use_doc_orientation_classify, use_doc_unwarping=use_doc_unwarping, ) ) @classmethod def get_cli_subcommand_executor(cls): return DocPreprocessorCLISubcommandExecutor() def _get_paddlex_config_overrides(self): STRUCTURE = { "SubModules.DocOrientationClassify.model_name": self._params[ "doc_orientation_classify_model_name" ], "SubModules.DocOrientationClassify.model_dir": self._params[ "doc_orientation_classify_model_dir" ], "SubModules.DocUnwarping.model_name": self._params[ "doc_unwarping_model_name" ], "SubModules.DocUnwarping.model_dir": self._params[ "doc_unwarping_model_dir" ], "use_doc_orientation_classify": self._params[ "use_doc_orientation_classify" ], "use_doc_unwarping": self._params["use_doc_unwarping"], } return create_config_from_structure(STRUCTURE) class DocPreprocessorCLISubcommandExecutor(PipelineCLISubcommandExecutor): @property def subparser_name(self): return "doc_preprocessor" def _update_subparser(self, subparser): add_simple_inference_args(subparser) subparser.add_argument( "--doc_orientation_classify_model_name", type=str, help="Name of the document image orientation classification model.", ) subparser.add_argument( "--doc_orientation_classify_model_dir", type=str, help="Path to the document image orientation classification model directory.", ) subparser.add_argument( "--doc_unwarping_model_name", type=str, help="Name of the document image unwarping model.", ) subparser.add_argument( "--doc_unwarping_model_dir", type=str, help="Path to the document image unwarping model directory.", ) subparser.add_argument( "--use_doc_orientation_classify", type=str2bool, help="Whether to use document image orientation classification.", ) subparser.add_argument( "--use_doc_unwarping", type=str2bool, help="Whether to use text image unwarping.", ) def execute_with_args(self, args): params = get_subcommand_args(args) perform_simple_inference(DocPreprocessor, params)