# 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 ( get_subcommand_args, str2bool, ) from .._utils.logging import logger from .base import PaddleXPipelineWrapper, PipelineCLISubcommandExecutor from .utils import create_config_from_structure class PPDocTranslation(PaddleXPipelineWrapper): def __init__( self, layout_detection_model_name=None, layout_detection_model_dir=None, layout_threshold=None, layout_nms=None, layout_unclip_ratio=None, layout_merge_bboxes_mode=None, chart_recognition_model_name=None, chart_recognition_model_dir=None, chart_recognition_batch_size=None, region_detection_model_name=None, region_detection_model_dir=None, doc_orientation_classify_model_name=None, doc_orientation_classify_model_dir=None, doc_unwarping_model_name=None, doc_unwarping_model_dir=None, text_detection_model_name=None, text_detection_model_dir=None, text_det_limit_side_len=None, text_det_limit_type=None, text_det_thresh=None, text_det_box_thresh=None, text_det_unclip_ratio=None, textline_orientation_model_name=None, textline_orientation_model_dir=None, textline_orientation_batch_size=None, text_recognition_model_name=None, text_recognition_model_dir=None, text_recognition_batch_size=None, text_rec_score_thresh=None, table_classification_model_name=None, table_classification_model_dir=None, wired_table_structure_recognition_model_name=None, wired_table_structure_recognition_model_dir=None, wireless_table_structure_recognition_model_name=None, wireless_table_structure_recognition_model_dir=None, wired_table_cells_detection_model_name=None, wired_table_cells_detection_model_dir=None, wireless_table_cells_detection_model_name=None, wireless_table_cells_detection_model_dir=None, table_orientation_classify_model_name=None, table_orientation_classify_model_dir=None, seal_text_detection_model_name=None, seal_text_detection_model_dir=None, seal_det_limit_side_len=None, seal_det_limit_type=None, seal_det_thresh=None, seal_det_box_thresh=None, seal_det_unclip_ratio=None, seal_text_recognition_model_name=None, seal_text_recognition_model_dir=None, seal_text_recognition_batch_size=None, seal_rec_score_thresh=None, formula_recognition_model_name=None, formula_recognition_model_dir=None, formula_recognition_batch_size=None, use_doc_orientation_classify=None, use_doc_unwarping=None, use_textline_orientation=None, use_seal_recognition=None, use_table_recognition=None, use_formula_recognition=None, use_chart_recognition=None, use_region_detection=None, chat_bot_config=None, **kwargs, ): params = locals().copy() params.pop("self") params.pop("kwargs") self._params = params super().__init__(**kwargs) @property def _paddlex_pipeline_name(self): return "PP-DocTranslation" def visual_predict_iter( self, input, *, use_doc_orientation_classify=None, use_doc_unwarping=None, use_textline_orientation=None, use_seal_recognition=None, use_table_recognition=None, use_formula_recognition=None, use_chart_recognition=None, use_region_detection=None, layout_threshold=None, layout_nms=None, layout_unclip_ratio=None, layout_merge_bboxes_mode=None, text_det_limit_side_len=None, text_det_limit_type=None, text_det_thresh=None, text_det_box_thresh=None, text_det_unclip_ratio=None, text_rec_score_thresh=None, seal_det_limit_side_len=None, seal_det_limit_type=None, seal_det_thresh=None, seal_det_box_thresh=None, seal_det_unclip_ratio=None, seal_rec_score_thresh=None, use_wired_table_cells_trans_to_html=False, use_wireless_table_cells_trans_to_html=False, use_table_orientation_classify=True, use_ocr_results_with_table_cells=True, use_e2e_wired_table_rec_model=False, use_e2e_wireless_table_rec_model=True, **kwargs, ): return self.paddlex_pipeline.visual_predict( input, use_doc_orientation_classify=use_doc_orientation_classify, use_doc_unwarping=use_doc_unwarping, use_textline_orientation=use_textline_orientation, use_seal_recognition=use_seal_recognition, use_table_recognition=use_table_recognition, use_formula_recognition=use_formula_recognition, use_chart_recognition=use_chart_recognition, use_region_detection=use_region_detection, layout_threshold=layout_threshold, layout_nms=layout_nms, layout_unclip_ratio=layout_unclip_ratio, layout_merge_bboxes_mode=layout_merge_bboxes_mode, text_det_limit_side_len=text_det_limit_side_len, text_det_limit_type=text_det_limit_type, text_det_thresh=text_det_thresh, text_det_box_thresh=text_det_box_thresh, text_det_unclip_ratio=text_det_unclip_ratio, text_rec_score_thresh=text_rec_score_thresh, seal_det_limit_side_len=seal_det_limit_side_len, seal_det_limit_type=seal_det_limit_type, seal_det_thresh=seal_det_thresh, seal_det_box_thresh=seal_det_box_thresh, seal_det_unclip_ratio=seal_det_unclip_ratio, seal_rec_score_thresh=seal_rec_score_thresh, use_wired_table_cells_trans_to_html=use_wired_table_cells_trans_to_html, use_wireless_table_cells_trans_to_html=use_wireless_table_cells_trans_to_html, use_table_orientation_classify=use_table_orientation_classify, use_ocr_results_with_table_cells=use_ocr_results_with_table_cells, use_e2e_wired_table_rec_model=use_e2e_wired_table_rec_model, use_e2e_wireless_table_rec_model=use_e2e_wireless_table_rec_model, **kwargs, ) def visual_predict( self, input, *, use_doc_orientation_classify=None, use_doc_unwarping=None, use_textline_orientation=None, use_seal_recognition=None, use_table_recognition=None, use_formula_recognition=None, use_chart_recognition=None, use_region_detection=None, layout_threshold=None, layout_nms=None, layout_unclip_ratio=None, layout_merge_bboxes_mode=None, text_det_limit_side_len=None, text_det_limit_type=None, text_det_thresh=None, text_det_box_thresh=None, text_det_unclip_ratio=None, text_rec_score_thresh=None, seal_det_limit_side_len=None, seal_det_limit_type=None, seal_det_thresh=None, seal_det_box_thresh=None, seal_det_unclip_ratio=None, seal_rec_score_thresh=None, use_wired_table_cells_trans_to_html=False, use_wireless_table_cells_trans_to_html=False, use_table_orientation_classify=True, use_ocr_results_with_table_cells=True, use_e2e_wired_table_rec_model=False, use_e2e_wireless_table_rec_model=True, **kwargs, ): return list( self.visual_predict_iter( input, use_doc_orientation_classify=use_doc_orientation_classify, use_doc_unwarping=use_doc_unwarping, use_textline_orientation=use_textline_orientation, use_seal_recognition=use_seal_recognition, use_table_recognition=use_table_recognition, use_formula_recognition=use_formula_recognition, use_chart_recognition=use_chart_recognition, use_region_detection=use_region_detection, layout_threshold=layout_threshold, layout_nms=layout_nms, layout_unclip_ratio=layout_unclip_ratio, layout_merge_bboxes_mode=layout_merge_bboxes_mode, text_det_limit_side_len=text_det_limit_side_len, text_det_limit_type=text_det_limit_type, text_det_thresh=text_det_thresh, text_det_box_thresh=text_det_box_thresh, text_det_unclip_ratio=text_det_unclip_ratio, text_rec_score_thresh=text_rec_score_thresh, seal_det_limit_side_len=seal_det_limit_side_len, seal_det_limit_type=seal_det_limit_type, seal_det_thresh=seal_det_thresh, seal_det_box_thresh=seal_det_box_thresh, seal_det_unclip_ratio=seal_det_unclip_ratio, seal_rec_score_thresh=seal_rec_score_thresh, use_wired_table_cells_trans_to_html=use_wired_table_cells_trans_to_html, use_wireless_table_cells_trans_to_html=use_wireless_table_cells_trans_to_html, use_table_orientation_classify=use_table_orientation_classify, use_ocr_results_with_table_cells=use_ocr_results_with_table_cells, use_e2e_wired_table_rec_model=use_e2e_wired_table_rec_model, use_e2e_wireless_table_rec_model=use_e2e_wireless_table_rec_model, **kwargs, ) ) def translate_iter( self, ori_md_info_list, *, target_language="zh", chunk_size=5000, task_description=None, output_format=None, rules_str=None, few_shot_demo_text_content=None, few_shot_demo_key_value_list=None, glossary=None, llm_request_interval=0.0, chat_bot_config=None, **kwargs, ): return self.paddlex_pipeline.translate( ori_md_info_list, target_language=target_language, chunk_size=chunk_size, task_description=task_description, output_format=output_format, rules_str=rules_str, few_shot_demo_text_content=few_shot_demo_text_content, few_shot_demo_key_value_list=few_shot_demo_key_value_list, glossary=glossary, llm_request_interval=llm_request_interval, chat_bot_config=chat_bot_config, **kwargs, ) def translate( self, ori_md_info_list, *, target_language="zh", chunk_size=5000, task_description=None, output_format=None, rules_str=None, few_shot_demo_text_content=None, few_shot_demo_key_value_list=None, glossary=None, llm_request_interval=0.0, chat_bot_config=None, **kwargs, ): return list( self.translate_iter( ori_md_info_list, target_language=target_language, chunk_size=chunk_size, task_description=task_description, output_format=output_format, rules_str=rules_str, few_shot_demo_text_content=few_shot_demo_text_content, few_shot_demo_key_value_list=few_shot_demo_key_value_list, glossary=glossary, llm_request_interval=llm_request_interval, chat_bot_config=chat_bot_config, **kwargs, ) ) def load_from_markdown(self, input): return self.paddlex_pipeline.load_from_markdown(input) def concatenate_markdown_pages(self, markdown_list): return self.paddlex_pipeline.concatenate_markdown_pages(markdown_list) @classmethod def get_cli_subcommand_executor(cls): return PPDocTranslationCLISubcommandExecutor() def _get_paddlex_config_overrides(self): # HACK: We should consider reducing duplication. STRUCTURE = { "SubPipelines.LayoutParser.SubPipelines.DocPreprocessor.use_doc_orientation_classify": self._params[ "use_doc_orientation_classify" ], "SubPipelines.LayoutParser.SubPipelines.DocPreprocessor.use_doc_unwarping": self._params[ "use_doc_unwarping" ], "SubPipelines.LayoutParser.use_doc_preprocessor": self._params[ "use_doc_orientation_classify" ] or self._params["use_doc_unwarping"], "SubPipelines.LayoutParser.SubPipelines.GeneralOCR.use_textline_orientation": self._params[ "use_textline_orientation" ], "SubPipelines.LayoutParser.use_seal_recognition": self._params[ "use_seal_recognition" ], "SubPipelines.LayoutParser.use_table_recognition": self._params[ "use_table_recognition" ], "SubPipelines.LayoutParser.use_formula_recognition": self._params[ "use_formula_recognition" ], "SubPipelines.LayoutParser.use_chart_recognition": self._params[ "use_chart_recognition" ], "SubPipelines.LayoutParser.use_region_detection": self._params[ "use_region_detection" ], "SubPipelines.LayoutParser.SubModules.LayoutDetection.model_name": self._params[ "layout_detection_model_name" ], "SubPipelines.LayoutParser.SubModules.LayoutDetection.model_dir": self._params[ "layout_detection_model_dir" ], "SubPipelines.LayoutParser.SubModules.LayoutDetection.threshold": self._params[ "layout_threshold" ], "SubPipelines.LayoutParser.SubModules.LayoutDetection.layout_nms": self._params[ "layout_nms" ], "SubPipelines.LayoutParser.SubModules.LayoutDetection.layout_unclip_ratio": self._params[ "layout_unclip_ratio" ], "SubPipelines.LayoutParser.SubModules.LayoutDetection.layout_merge_bboxes_mode": self._params[ "layout_merge_bboxes_mode" ], "SubPipelines.LayoutParser.SubModules.ChartRecognition.model_name": self._params[ "chart_recognition_model_name" ], "SubPipelines.LayoutParser.SubModules.ChartRecognition.model_dir": self._params[ "chart_recognition_model_dir" ], "SubPipelines.LayoutParser.SubModules.ChartRecognition.batch_size": self._params[ "chart_recognition_batch_size" ], "SubPipelines.LayoutParser.SubModules.RegionDetection.model_name": self._params[ "region_detection_model_name" ], "SubPipelines.LayoutParser.SubModules.RegionDetection.model_dir": self._params[ "region_detection_model_dir" ], "SubPipelines.LayoutParser.SubPipelines.DocPreprocessor.SubModules.DocOrientationClassify.model_name": self._params[ "doc_orientation_classify_model_name" ], "SubPipelines.LayoutParser.SubPipelines.DocPreprocessor.SubModules.DocOrientationClassify.model_dir": self._params[ "doc_orientation_classify_model_dir" ], "SubPipelines.LayoutParser.SubPipelines.DocPreprocessor.SubModules.DocUnwarping.model_name": self._params[ "doc_unwarping_model_name" ], "SubPipelines.LayoutParser.SubPipelines.DocPreprocessor.SubModules.DocUnwarping.model_dir": self._params[ "doc_unwarping_model_dir" ], "SubPipelines.LayoutParser.SubPipelines.GeneralOCR.SubModules.TextDetection.model_name": self._params[ "text_detection_model_name" ], "SubPipelines.LayoutParser.SubPipelines.GeneralOCR.SubModules.TextDetection.model_dir": self._params[ "text_detection_model_dir" ], "SubPipelines.LayoutParser.SubPipelines.GeneralOCR.SubModules.TextDetection.limit_side_len": self._params[ "text_det_limit_side_len" ], "SubPipelines.LayoutParser.SubPipelines.GeneralOCR.SubModules.TextDetection.limit_type": self._params[ "text_det_limit_type" ], "SubPipelines.LayoutParser.SubPipelines.GeneralOCR.SubModules.TextDetection.thresh": self._params[ "text_det_thresh" ], "SubPipelines.LayoutParser.SubPipelines.GeneralOCR.SubModules.TextDetection.box_thresh": self._params[ "text_det_box_thresh" ], "SubPipelines.LayoutParser.SubPipelines.GeneralOCR.SubModules.TextDetection.unclip_ratio": self._params[ "text_det_unclip_ratio" ], "SubPipelines.LayoutParser.SubPipelines.GeneralOCR.SubModules.TextLineOrientation.model_name": self._params[ "textline_orientation_model_name" ], "SubPipelines.LayoutParser.SubPipelines.GeneralOCR.SubModules.TextLineOrientation.model_dir": self._params[ "textline_orientation_model_dir" ], "SubPipelines.LayoutParser.SubPipelines.GeneralOCR.SubModules.TextLineOrientation.batch_size": self._params[ "textline_orientation_batch_size" ], "SubPipelines.LayoutParser.SubPipelines.GeneralOCR.SubModules.TextRecognition.model_name": self._params[ "text_recognition_model_name" ], "SubPipelines.LayoutParser.SubPipelines.GeneralOCR.SubModules.TextRecognition.model_dir": self._params[ "text_recognition_model_dir" ], "SubPipelines.LayoutParser.SubPipelines.GeneralOCR.SubModules.TextRecognition.batch_size": self._params[ "text_recognition_batch_size" ], "SubPipelines.LayoutParser.SubPipelines.GeneralOCR.SubModules.TextRecognition.score_thresh": self._params[ "text_rec_score_thresh" ], "SubPipelines.LayoutParser.SubPipelines.TableRecognition.SubModules.TableClassification.model_name": self._params[ "table_classification_model_name" ], "SubPipelines.LayoutParser.SubPipelines.TableRecognition.SubModules.TableClassification.model_dir": self._params[ "table_classification_model_dir" ], "SubPipelines.LayoutParser.SubPipelines.TableRecognition.SubModules.WiredTableStructureRecognition.model_name": self._params[ "wired_table_structure_recognition_model_name" ], "SubPipelines.LayoutParser.SubPipelines.TableRecognition.SubModules.WiredTableStructureRecognition.model_dir": self._params[ "wired_table_structure_recognition_model_dir" ], "SubPipelines.LayoutParser.SubPipelines.TableRecognition.SubModules.WirelessTableStructureRecognition.model_name": self._params[ "wireless_table_structure_recognition_model_name" ], "SubPipelines.LayoutParser.SubPipelines.TableRecognition.SubModules.WirelessTableStructureRecognition.model_dir": self._params[ "wireless_table_structure_recognition_model_dir" ], "SubPipelines.LayoutParser.SubPipelines.TableRecognition.SubModules.WiredTableCellsDetection.model_name": self._params[ "wired_table_cells_detection_model_name" ], "SubPipelines.LayoutParser.SubPipelines.TableRecognition.SubModules.WiredTableCellsDetection.model_dir": self._params[ "wired_table_cells_detection_model_dir" ], "SubPipelines.LayoutParser.SubPipelines.TableRecognition.SubModules.WirelessTableCellsDetection.model_name": self._params[ "wireless_table_cells_detection_model_name" ], "SubPipelines.LayoutParser.SubPipelines.TableRecognition.SubModules.WirelessTableCellsDetection.model_dir": self._params[ "wireless_table_cells_detection_model_dir" ], "SubPipelines.LayoutParser.SubPipelines.TableRecognition.SubModules.TableOrientationClassify.model_name": self._params[ "table_orientation_classify_model_name" ], "SubPipelines.LayoutParser.SubPipelines.TableRecognition.SubModules.TableOrientationClassify.model_dir": self._params[ "table_orientation_classify_model_dir" ], "SubPipelines.LayoutParser.SubPipelines.TableRecognition.SubPipelines.GeneralOCR.SubModules.TextDetection.model_name": self._params[ "text_detection_model_name" ], "SubPipelines.LayoutParser.SubPipelines.TableRecognition.SubPipelines.GeneralOCR.SubModules.TextDetection.model_dir": self._params[ "text_detection_model_dir" ], "SubPipelines.LayoutParser.SubPipelines.TableRecognition.SubPipelines.GeneralOCR.SubModules.TextDetection.limit_side_len": self._params[ "text_det_limit_side_len" ], "SubPipelines.LayoutParser.SubPipelines.TableRecognition.SubPipelines.GeneralOCR.SubModules.TextDetection.limit_type": self._params[ "text_det_limit_type" ], "SubPipelines.LayoutParser.SubPipelines.TableRecognition.SubPipelines.GeneralOCR.SubModules.TextDetection.thresh": self._params[ "text_det_thresh" ], "SubPipelines.LayoutParser.SubPipelines.TableRecognition.SubPipelines.GeneralOCR.SubModules.TextDetection.box_thresh": self._params[ "text_det_box_thresh" ], "SubPipelines.LayoutParser.SubPipelines.TableRecognition.SubPipelines.GeneralOCR.SubModules.TextDetection.unclip_ratio": self._params[ "text_det_unclip_ratio" ], "SubPipelines.LayoutParser.SubPipelines.TableRecognition.SubPipelines.GeneralOCR.SubModules.TextLineOrientation.model_name": self._params[ "textline_orientation_model_name" ], "SubPipelines.LayoutParser.SubPipelines.TableRecognition.SubPipelines.GeneralOCR.SubModules.TextLineOrientation.model_dir": self._params[ "textline_orientation_model_dir" ], "SubPipelines.LayoutParser.SubPipelines.TableRecognition.SubPipelines.GeneralOCR.SubModules.TextLineOrientation.batch_size": self._params[ "textline_orientation_batch_size" ], "SubPipelines.LayoutParser.SubPipelines.TableRecognition.SubPipelines.GeneralOCR.SubModules.TextRecognition.model_name": self._params[ "text_recognition_model_name" ], "SubPipelines.LayoutParser.SubPipelines.TableRecognition.SubPipelines.GeneralOCR.SubModules.TextRecognition.model_dir": self._params[ "text_recognition_model_dir" ], "SubPipelines.LayoutParser.SubPipelines.TableRecognition.SubPipelines.GeneralOCR.SubModules.TextRecognition.batch_size": self._params[ "text_recognition_batch_size" ], "SubPipelines.LayoutParser.SubPipelines.TableRecognition.SubPipelines.GeneralOCR.SubModules.TextRecognition.score_thresh": self._params[ "text_rec_score_thresh" ], "SubPipelines.LayoutParser.SubPipelines.SealRecognition.SubPipelines.SealOCR.SubModules.TextDetection.model_name": self._params[ "seal_text_detection_model_name" ], "SubPipelines.LayoutParser.SubPipelines.SealRecognition.SubPipelines.SealOCR.SubModules.TextDetection.model_dir": self._params[ "seal_text_detection_model_dir" ], "SubPipelines.LayoutParser.SubPipelines.SealRecognition.SubPipelines.SealOCR.SubModules.TextDetection.limit_side_len": self._params[ "text_det_limit_side_len" ], "SubPipelines.LayoutParser.SubPipelines.SealRecognition.SubPipelines.SealOCR.SubModules.TextDetection.limit_type": self._params[ "seal_det_limit_type" ], "SubPipelines.LayoutParser.SubPipelines.SealRecognition.SubPipelines.SealOCR.SubModules.TextDetection.thresh": self._params[ "seal_det_thresh" ], "SubPipelines.LayoutParser.SubPipelines.SealRecognition.SubPipelines.SealOCR.SubModules.TextDetection.box_thresh": self._params[ "seal_det_box_thresh" ], "SubPipelines.LayoutParser.SubPipelines.SealRecognition.SubPipelines.SealOCR.SubModules.TextDetection.unclip_ratio": self._params[ "seal_det_unclip_ratio" ], "SubPipelines.LayoutParser.SubPipelines.SealRecognition.SubPipelines.SealOCR.SubModules.TextRecognition.model_name": self._params[ "seal_text_recognition_model_name" ], "SubPipelines.LayoutParser.SubPipelines.SealRecognition.SubPipelines.SealOCR.SubModules.TextRecognition.model_dir": self._params[ "seal_text_recognition_model_dir" ], "SubPipelines.LayoutParser.SubPipelines.SealRecognition.SubPipelines.SealOCR.SubModules.TextRecognition.batch_size": self._params[ "seal_text_recognition_batch_size" ], "SubPipelines.LayoutParser.SubPipelines.FormulaRecognition.SubModules.FormulaRecognition.model_name": self._params[ "formula_recognition_model_name" ], "SubPipelines.LayoutParser.SubPipelines.FormulaRecognition.SubModules.FormulaRecognition.model_dir": self._params[ "formula_recognition_model_dir" ], "SubPipelines.LayoutParser.SubPipelines.FormulaRecognition.SubModules.FormulaRecognition.batch_size": self._params[ "formula_recognition_batch_size" ], "SubModules.LLM_Chat": self._params["chat_bot_config"], } return create_config_from_structure(STRUCTURE) class PPDocTranslationCLISubcommandExecutor(PipelineCLISubcommandExecutor): @property def subparser_name(self): return "pp_doctranslation" def _update_subparser(self, subparser): subparser.add_argument( "-i", "--input", type=str, required=True, help="Input path or URL.", ) subparser.add_argument( "--save_path", type=str, help="Path to the output directory.", ) subparser.add_argument( "--target_language", type=str, default="zh", help="Target language.", ) subparser.add_argument( "--layout_detection_model_name", type=str, help="Name of the layout detection model.", ) subparser.add_argument( "--layout_detection_model_dir", type=str, help="Path to the layout detection model directory.", ) subparser.add_argument( "--layout_threshold", type=float, help="Score threshold for the layout detection model.", ) subparser.add_argument( "--layout_nms", type=str2bool, help="Whether to use NMS in layout detection.", ) subparser.add_argument( "--layout_unclip_ratio", type=float, help="Expansion coefficient for layout detection.", ) subparser.add_argument( "--layout_merge_bboxes_mode", type=str, help="Overlapping box filtering method.", ) subparser.add_argument( "--chart_recognition_model_name", type=str, help="Name of the chart recognition model.", ) subparser.add_argument( "--chart_recognition_model_dir", type=str, help="Path to the chart recognition model directory.", ) subparser.add_argument( "--chart_recognition_batch_size", type=int, help="Batch size for the chart recognition model.", ) subparser.add_argument( "--region_detection_model_name", type=str, help="Name of the region detection model.", ) subparser.add_argument( "--region_detection_model_dir", type=str, help="Path to the region detection model directory.", ) 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 text image unwarping model.", ) subparser.add_argument( "--doc_unwarping_model_dir", type=str, help="Path to the image unwarping model directory.", ) subparser.add_argument( "--text_detection_model_name", type=str, help="Name of the text detection model.", ) subparser.add_argument( "--text_detection_model_dir", type=str, help="Path to the text detection model directory.", ) subparser.add_argument( "--text_det_limit_side_len", type=int, help="This sets a limit on the side length of the input image for the text detection model.", ) subparser.add_argument( "--text_det_limit_type", type=str, help="This determines how the side length limit is applied to the input image before feeding it into the text deteciton model.", ) subparser.add_argument( "--text_det_thresh", type=float, help="Detection pixel threshold for the text detection model. Pixels with scores greater than this threshold in the output probability map are considered text pixels.", ) subparser.add_argument( "--text_det_box_thresh", type=float, help="Detection box threshold for the text detection model. A detection result is considered a text region if the average score of all pixels within the border of the result is greater than this threshold.", ) subparser.add_argument( "--text_det_unclip_ratio", type=float, help="Text detection expansion coefficient, which expands the text region using this method. The larger the value, the larger the expansion area.", ) subparser.add_argument( "--textline_orientation_model_name", type=str, help="Name of the text line orientation classification model.", ) subparser.add_argument( "--textline_orientation_model_dir", type=str, help="Path to the text line orientation classification directory.", ) subparser.add_argument( "--textline_orientation_batch_size", type=int, help="Batch size for the text line orientation classification model.", ) subparser.add_argument( "--text_recognition_model_name", type=str, help="Name of the text recognition model.", ) subparser.add_argument( "--text_recognition_model_dir", type=str, help="Path to the text recognition model directory.", ) subparser.add_argument( "--text_recognition_batch_size", type=int, help="Batch size for the text recognition model.", ) subparser.add_argument( "--text_rec_score_thresh", type=float, help="Text recognition threshold used in general OCR. Text results with scores greater than this threshold are retained.", ) subparser.add_argument( "--table_classification_model_name", type=str, help="Name of the table classification model.", ) subparser.add_argument( "--table_classification_model_dir", type=str, help="Path to the table classification model directory.", ) subparser.add_argument( "--wired_table_structure_recognition_model_name", type=str, help="Name of the wired table structure recognition model.", ) subparser.add_argument( "--wired_table_structure_recognition_model_dir", type=str, help="Path to the wired table structure recognition model directory.", ) subparser.add_argument( "--wireless_table_structure_recognition_model_name", type=str, help="Name of the wireless table structure recognition model.", ) subparser.add_argument( "--wireless_table_structure_recognition_model_dir", type=str, help="Path to the wired table structure recognition model directory.", ) subparser.add_argument( "--wired_table_cells_detection_model_name", type=str, help="Name of the wired table cells detection model.", ) subparser.add_argument( "--wired_table_cells_detection_model_dir", type=str, help="Path to the wired table cells detection model directory.", ) subparser.add_argument( "--wireless_table_cells_detection_model_name", type=str, help="Name of the wireless table cells detection model.", ) subparser.add_argument( "--wireless_table_cells_detection_model_dir", type=str, help="Path to the wireless table cells detection model directory.", ) subparser.add_argument( "--seal_text_detection_model_name", type=str, help="Name of the seal text detection model.", ) subparser.add_argument( "--seal_text_detection_model_dir", type=str, help="Path to the seal text detection model directory.", ) subparser.add_argument( "--seal_det_limit_side_len", type=int, help="This sets a limit on the side length of the input image for the seal text detection model.", ) subparser.add_argument( "--seal_det_limit_type", type=str, help="This determines how the side length limit is applied to the input image before feeding it into the seal text deteciton model.", ) subparser.add_argument( "--seal_det_thresh", type=float, help="Detection pixel threshold for the seal text detection model. Pixels with scores greater than this threshold in the output probability map are considered text pixels.", ) subparser.add_argument( "--seal_det_box_thresh", type=float, help="Detection box threshold for the seal text detection model. A detection result is considered a text region if the average score of all pixels within the border of the result is greater than this threshold.", ) subparser.add_argument( "--seal_det_unclip_ratio", type=float, help="Seal text detection expansion coefficient, which expands the text region using this method. The larger the value, the larger the expansion area.", ) subparser.add_argument( "--seal_text_recognition_model_name", type=str, help="Name of the seal text recognition model.", ) subparser.add_argument( "--seal_text_recognition_model_dir", type=str, help="Path to the seal text recognition model directory.", ) subparser.add_argument( "--seal_text_recognition_batch_size", type=int, help="Batch size for the seal text recognition model.", ) subparser.add_argument( "--seal_rec_score_thresh", type=float, help="Seal text recognition threshold. Text results with scores greater than this threshold are retained.", ) subparser.add_argument( "--formula_recognition_model_name", type=str, help="Name of the formula recognition model.", ) subparser.add_argument( "--formula_recognition_model_dir", type=str, help="Path to the formula recognition model directory.", ) subparser.add_argument( "--formula_recognition_batch_size", type=int, help="Batch size for the formula recognition model.", ) 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.", ) subparser.add_argument( "--use_textline_orientation", type=str2bool, help="Whether to use text line orientation classification.", ) subparser.add_argument( "--use_seal_recognition", type=str2bool, help="Whether to use seal recognition.", ) subparser.add_argument( "--use_table_recognition", type=str2bool, help="Whether to use table recognition.", ) subparser.add_argument( "--use_formula_recognition", type=str2bool, help="Whether to use formula recognition.", ) subparser.add_argument( "--use_chart_recognition", type=str2bool, help="Whether to use chart recognition.", ) subparser.add_argument( "--use_region_detection", type=str2bool, help="Whether to use region detection.", ) # FIXME: Passing API key through CLI is not secure; consider using # environment variables. subparser.add_argument( "--qianfan_api_key", type=str, help="Configuration for the embedding model.", ) def execute_with_args(self, args): params = get_subcommand_args(args) input = params.pop("input") target_language = params.pop("target_language") save_path = params.pop("save_path") qianfan_api_key = params.pop("qianfan_api_key") if qianfan_api_key is not None: params["chat_bot_config"] = { "module_name": "chat_bot", "model_name": "ernie-3.5-8k", "base_url": "https://qianfan.baidubce.com/v2", "api_type": "openai", "api_key": qianfan_api_key, } chatocr = PPDocTranslation(**params) logger.info("Start analyzing images") result_visual = chatocr.visual_predict_iter(input) ori_md_info_list = [] for res in result_visual: ori_md_info_list.append(res["layout_parsing_result"].markdown) if save_path: res["layout_parsing_result"].save_all(save_path) logger.info("Start translation") result_translate = chatocr.translate_iter( ori_md_info_list, target_language=target_language, ) for res in result_translate: res.print() if save_path: res.save_to_markdown(save_path)