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PaddleOCR/paddleocr/_pipelines/pp_doctranslation.py
Lin Manhui de17179186
[Docs] Fix errors (#16005) 
* Fix docs

* Update MCP docs

* Update English doc and fix docs
2025-07-14 11:44:37 +08:00

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Python
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# 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=False,
use_doc_unwarping=False,
use_textline_orientation=None,
use_seal_recognition=None,
use_table_recognition=None,
use_formula_recognition=None,
use_chart_recognition=False,
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=False,
use_doc_unwarping=False,
use_textline_orientation=None,
use_seal_recognition=None,
use_table_recognition=None,
use_formula_recognition=None,
use_chart_recognition=False,
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.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)
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