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* TLDR-405 remove is_one_column_document_list (#332) * TLDR-405 remove is_one_column_document_list * TLDR-405 fix tests * TLDR-405 review fix * TLDR-448-Fix draw coordinates bug (#330) * Fix draw coordinates bug * Fix draw coordinates conversion * TLDR-451 tutorial new doc type (#331) * docs added * add code testing * some fixes * some fixes * add tabula and some fixes * add python-djvulibre * delete python-djvulibre and add djvulibre-bin * add poppler-utils * add tesseract * some fixes * flake8 stylefix * fix docs after flake8 * update last part of adding_new_doc_type_tutorial * rewrite dedoc_add_new_doc_type_tutorial * minor fixes * minor fixes * minor fixes * some fixes * add more code examples * some fixes --------- Co-authored-by: Nikita Shevtsov <[email protected]> Co-authored-by: Nasty <[email protected]> * updated txt layer correctness classifier (#334) Co-authored-by: Alexander Golodkov <[email protected]> * Esl 137 added boxes into table (#333) * ESL-137 added box extraction skeleton into scan table extraction * ESL-138 ESL-137 a lot of table changes - added CellWithMeta - change output table structure, remove CellProperies in output - change logic bbox extraction from image tables after debugging - change output in CSV, HTML, TABBY, PDF, SCAN readers - change all tests with tables - fixed styles * ESL-137 chnaged draw table script * ESL-148 added script of table word boxes drawing * TLDR-471 added angle rotation from PdfImageReader and Tables * ESL-137 fixed unit-tests * ESL-137 fixed after review; removing some unused functions - fixed after review - removing some unused functions * ESL-137 update docs * ESL-137 after review * Updated columns orientation classifier (#335) * updated txt columns orientation classifier * deleted "no_lines" parameter --------- Co-authored-by: Alexander Golodkov <[email protected]> * fix pdf reader (#337) Co-authored-by: Nikita Shevtsov <[email protected]> * TLDR-472 add flake8-fill-one-line and flake8-multiline-containers and fix lint (#336) * add flake8-fill-one-line and flake8-multiline-containers and fix lint * update precommit hook * TLDR-475 fix table documentation (#338) * TLDR-475 fix table documentation * Small fixes * TLDR-474 remove insert_table parameter (#339) * TLDR-474 remove insert_table parameter * TLDR-474 remove is_inserted attribute * ESL-470 fixed rotation operation of table word boxes (#341) rotates a table image and saving image.shape during rotation. It is important for word bounding box extraction * TLDR-478 docx table refactoring (#342) * TLDR-478 docx table refactoring * Small fixes * TLDR-483 fixed box extraction from cropped cells (#343) * TLDR-473 add dedoc utils (#340) * use dedoc utils BBox class * use AdaptiveBinarizer from dedoc-utils * use SkewCorrector from dedoc-utils * fix style * fix rotated angle error * delete BBox from docs * fix angles * delete print * fix dedocutils * dedocutils set ver. 0.3.5 * fix mistakes and names --------- Co-authored-by: Nikita Shevtsov <[email protected]> * TLDR-481 html refactoring (#344) * delete unused files * Delete unused files, refactor html * Refactor query parameters * Fix tests * Refactor train dataset api * Fix style * Change python version in tests * Review fixes * TLDR-490 changed uuid1 on uuid4; fixed bug in tabby's table uuid (#345) * TLDR-490 changed uuid1 on uuid4; fixed bug in tabby's table uuid * TLDR-490 fixes after review * Added running API examples instruction (#346) * added linewithmeta comparison operator (#347) Co-authored-by: Alexander Golodkov <[email protected]> * ESL-156 fix pdfminer boxes output (#348) * ESL-156 fix pdfminer boxes output * ESL-156 after review * ESL-159 fixed extract boxes from pdfminer reader (#350) * new version 1.0 (#351) --------- Co-authored-by: Andrey Mikhailov <[email protected]> Co-authored-by: Nikita Shevtsov <[email protected]> Co-authored-by: Nikita Shevtsov <[email protected]> Co-authored-by: Alexander Golodkov <[email protected]> Co-authored-by: Alexander Golodkov <[email protected]> Co-authored-by: Oksana Belyaeva <[email protected]> Co-authored-by: Andrew Perminov <[email protected]>
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| resources, | ||
| dedoc/scripts, | ||
| examples, | ||
| docs, | ||
| venv, | ||
| build, | ||
| dedoc.egg-info | ||
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| 0.11.2 | ||
| 1.0 |
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| from typing import Any, Optional | ||
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| from fastapi import Body | ||
| from pydantic import BaseModel | ||
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| class QueryParameters(BaseModel): | ||
| document_type: Optional[str] | ||
| structure_type: Optional[str] | ||
| return_format: Optional[str] | ||
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| with_attachments: Optional[str] | ||
| need_content_analysis: Optional[str] | ||
| recursion_deep_attachments: Optional[str] | ||
| return_base64: Optional[str] | ||
| attachments_dir: Optional[str] | ||
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| insert_table: Optional[str] | ||
| need_pdf_table_analysis: Optional[str] | ||
| table_type: Optional[str] | ||
| orient_analysis_cells: Optional[str] | ||
| orient_cell_angle: Optional[str] | ||
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| pdf_with_text_layer: Optional[str] | ||
| language: Optional[str] | ||
| pages: Optional[str] | ||
| is_one_column_document: Optional[str] | ||
| document_orientation: Optional[str] | ||
| need_header_footer_analysis: Optional[str] | ||
| need_binarization: Optional[str] | ||
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| delimiter: Optional[str] | ||
| encoding: Optional[str] | ||
| html_fields: Optional[str] | ||
| handle_invisible_table: Optional[str] | ||
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| def __init__(self, | ||
| # type of document structure parsing | ||
| document_type: Optional[str] = Body(description="a document type. Default: ''", enum=["", "law", "tz", "diploma"], default=None), # noqa | ||
| structure_type: Optional[str] = Body(description="output structure type (linear or tree). Default: 'tree'", enum=["linear", "tree"], default=None), # noqa | ||
| return_format: Optional[str] = Body(description="an option for returning a response in html form, json, pretty_json or tree. Assume that one should use json in all cases, all other formats are used for debug porpoises only. Default: 'json'", default=None), # noqa | ||
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| # attachments handling | ||
| with_attachments: Optional[str] = Body(description="an option to enable the analysis of attached files. Default: 'false'", default=None), # noqa | ||
| need_content_analysis: Optional[str] = Body(description="turn on if you need parse the contents of the document attachments. Default: 'false'", default=None), # noqa | ||
| recursion_deep_attachments: Optional[str] = Body(description="the depth on which nested attachments will be parsed if need_content_analysis=true. Default: '10'", default=None), # noqa | ||
| return_base64: Optional[str] = Body(description="returns images in base64 format. Default: 'false'", default=None), # noqa | ||
| attachments_dir: Optional[str] = Body(description="path to the directory where to save files' attachments", default=None), # noqa | ||
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| # tables handling | ||
| insert_table: Optional[str] = Body(description="Insert table into the result tree's content or not. Default: 'false'", default=None), # noqa | ||
| need_pdf_table_analysis: Optional[str] = Body(description="include a table analysis into pdfs. Default: 'true'", default=None), # noqa | ||
| table_type: Optional[str] = Body(description="a pipeline mode for a table recognition. Default: ''", default=None), # noqa | ||
| orient_analysis_cells: Optional[str] = Body(description="a table recognition option enables analysis of rotated cells in table headers. Default: 'false'", default=None), # noqa | ||
| orient_cell_angle: Optional[str] = Body(description="an option to set orientation of cells in table headers. \"270\" - cells are rotated 90 degrees clockwise, \"90\" - cells are rotated 90 degrees counterclockwise (or 270 clockwise)", default=None), # noqa | ||
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| # pdf handling | ||
| pdf_with_text_layer: Optional[str] = Body(description="an option to extract text from a text layer to PDF or using OCR methods for image-documents. Default: 'auto_tabby'", enum=["true", "false", "auto", "auto_tabby", "tabby"], default=None), # noqa | ||
| language: Optional[str] = Body(description="a recognition language. Default: 'rus+eng'", enum=["rus+eng", "rus", "eng"], default=None), # noqa | ||
| pages: Optional[str] = Body(description="an option to limit page numbers in pdf, archives with images. left:right, read pages from left to right. Default: ':'", default=None), # noqa | ||
| is_one_column_document: Optional[str] = Body(description="an option to set one or multiple column document. \"auto\" - system predict number of columns in document pages, \"true\" - is one column documents, \"false\" - is multiple column documents. Default: 'auto'", default=None), # noqa | ||
| document_orientation: Optional[str] = Body(description="an option to set vertical orientation of the document without using an orientation classifier \"auto\" - system predict angle (0, 90, 180, 270) and rotate document, \"no_change\" - do not predict orientation. Default: 'auto'", enum=["auto", "no_change"], default=None), # noqa | ||
| need_header_footer_analysis: Optional[str] = Body(description="include header-footer analysis into pdf with text layer. Default: 'false'", default=None), # noqa | ||
| need_binarization: Optional[str] = Body(description="include an adaptive binarization into pdf without a text layer. Default: 'false'", default=None), # noqa | ||
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| # other formats handling | ||
| delimiter: Optional[str] = Body(description="a column separator for csv-files", default=None), # noqa | ||
| encoding: Optional[str] = Body(description="a document encoding", default=None), # noqa | ||
| html_fields: Optional[str] = Body(description="a list of fields for JSON documents to be parsed as HTML documents. It is written as a json string of a list, where each list item is a list of keys to get the field. Default: ''", default=None), # noqa | ||
| handle_invisible_table: Optional[str] = Body(description="handle table without visible borders as tables in html. Default: 'false'", default=None), # noqa | ||
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| **data: Any) -> None: # noqa | ||
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| super().__init__(**data) | ||
| self.document_type: str = document_type or "" | ||
| self.structure_type: str = structure_type or "tree" | ||
| self.return_format: str = return_format or "json" | ||
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| self.with_attachments: str = with_attachments or "false" | ||
| self.need_content_analysis: str = need_content_analysis or "false" | ||
| self.recursion_deep_attachments: str = recursion_deep_attachments or "10" | ||
| self.return_base64: str = return_base64 or "false" | ||
| self.attachments_dir: str = attachments_dir | ||
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| self.insert_table: str = insert_table or "false" | ||
| self.need_pdf_table_analysis: str = need_pdf_table_analysis or "true" | ||
| self.table_type: str = table_type or "" | ||
| self.orient_analysis_cells: str = orient_analysis_cells or "false" | ||
| self.orient_cell_angle: str = orient_cell_angle or "90" | ||
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| self.pdf_with_text_layer: str = pdf_with_text_layer or "auto_tabby" | ||
| self.language: str = language or "rus+eng" | ||
| self.pages: str = pages or ":" | ||
| self.is_one_column_document: str = is_one_column_document or "auto" | ||
| self.document_orientation: str = document_orientation or "auto" | ||
| self.need_header_footer_analysis: str = need_header_footer_analysis or "false" | ||
| self.need_binarization: str = need_binarization or "false" | ||
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| self.delimiter: str = delimiter | ||
| self.encoding: str = encoding | ||
| self.html_fields: str = html_fields or "" | ||
| self.handle_invisible_table: str = handle_invisible_table or "false" | ||
| from dataclasses import asdict, dataclass | ||
| from typing import Optional | ||
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| from fastapi import Form | ||
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| @dataclass | ||
| class QueryParameters: | ||
| # type of document structure parsing | ||
| document_type: str = Form("", enum=["", "law", "tz", "diploma"], description="Document domain") | ||
| structure_type: str = Form("tree", enum=["linear", "tree"], description="Output structure type") | ||
| return_format: str = Form("json", enum=["json", "html", "plain_text", "tree", "collapsed_tree", "ujson", "pretty_json"], | ||
| description="Response representation, most types (except json) are used for debug purposes only") | ||
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| # attachments handling | ||
| with_attachments: str = Form("false", enum=["true", "false"], description="Enable attached files extraction") | ||
| need_content_analysis: str = Form("false", enum=["true", "false"], description="Enable parsing contents of the attached files") | ||
| recursion_deep_attachments: str = Form("10", description="Depth on which nested attachments will be parsed if need_content_analysis=true") | ||
| return_base64: str = Form("false", enum=["true", "false"], description="Save attached images to the document metadata in base64 format") | ||
| attachments_dir: Optional[str] = Form(None, description="Path to the directory where to save files' attachments") | ||
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| # tables handling | ||
| need_pdf_table_analysis: str = Form("true", enum=["true", "false"], description="Enable table recognition for pdf") | ||
| table_type: str = Form("", description="Pipeline mode for table recognition") | ||
| orient_analysis_cells: str = Form("false", enum=["true", "false"], description="Enable analysis of rotated cells in table headers") | ||
| orient_cell_angle: str = Form("90", enum=["90", "270"], | ||
| description='Set cells orientation in table headers, "90" means 90 degrees counterclockwise cells rotation') | ||
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| # pdf handling | ||
| pdf_with_text_layer: str = Form("auto_tabby", enum=["true", "false", "auto", "auto_tabby", "tabby"], | ||
| description="Extract text from a text layer of PDF or using OCR methods for image-like documents") | ||
| language: str = Form("rus+eng", enum=["rus+eng", "rus", "eng"], description="Recognition language") | ||
| pages: str = Form(":", description='Page numbers range for reading PDF or images, "left:right" means read pages from left to right') | ||
| is_one_column_document: str = Form("auto", enum=["auto", "true", "false"], | ||
| description='One or multiple column document, "auto" - predict number of page columns automatically') | ||
| document_orientation: str = Form("auto", enum=["auto", "no_change"], | ||
| description='Orientation of the document pages, "auto" - predict orientation (0, 90, 180, 270 degrees), ' | ||
| '"no_change" - set vertical orientation of the document without using an orientation classifier') | ||
| need_header_footer_analysis: str = Form("false", enum=["true", "false"], description="Exclude headers and footers from PDF parsing result") | ||
| need_binarization: str = Form("false", enum=["true", "false"], description="Binarize document pages (for images or PDF without a textual layer)") | ||
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| # other formats handling | ||
| delimiter: Optional[str] = Form(None, description="Column separator for CSV files") | ||
| encoding: Optional[str] = Form(None, description="Document encoding") | ||
| html_fields: str = Form("", description="List of fields for JSON documents to be parsed as HTML documents") | ||
| handle_invisible_table: str = Form("false", enum=["true", "false"], description="Handle tables without visible borders as tables in HTML") | ||
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| def to_dict(self) -> dict: | ||
| parameters = {} | ||
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| for parameter_name, parameter_value in asdict(self).items(): | ||
| parameters[parameter_name] = getattr(parameter_value, "default", parameter_value) | ||
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| return parameters |
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