modules

geometor.pacioli

Tools for parsing and processing “De Divina Proportione” by Luca Pacioli.

Key Components:

• Parser: The PacioliParser class extracts chapters and content from the transcribed text.

• Execution: The run_parse.py script executes the parsing process.

Usage:

Initialize PacioliParser with resources and output directories, then call parse().

Submodules

• geometor.pacioli.__main__
• geometor.pacioli.app
• geometor.pacioli.extraction
• geometor.pacioli.graphics
• geometor.pacioli.pacioli
• geometor.pacioli.parse_winterberg
• geometor.pacioli.parser
• geometor.pacioli.run_parse
• geometor.pacioli.run_winterberg_parse

Classes

PacioliParser

Functions

extract_all(pdf_path, output_dir[, start_page, ...]) → None	Extract page images and text for the entire volume in parallel.
build_graphics_index(directory) → pathlib.Path	Compile all per-folio <folio>.json files into graphics_index.json.
clean_image(pil_image[, white_point, preserve_color]) → PIL.Image.Image	Normalize aged parchment background and binding shadows to pure white (255).
detect_graphics_cv(image_path) → List[Dict[str, Any]]	Detect full-page plate graphics using OpenCV if available, falling back to SciPy.
detect_initials(image_path) → List[Dict[str, Any]]	Detect woodcut illuminated initial caps by finding 2D ink-density centers along the text column edge.
detect_margin_figures(image_path, is_recto) → List[Dict[str, Any]]	Detect geometric diagrams and marginalia strictly in the outer margin of a text folio.
extract_from_json(json_path[, no_clean]) → None	Extract all margin graphics and illuminated initial caps defined in <folio>.json.

Package Contents

class geometor.pacioli.PacioliParser(resources_dir: pathlib.Path, output_dir: pathlib.Path)

resources_dir

output_dir

transcribed_file

parse()

Execute the parsing process.

This method orchestrates the extraction of TOC and text chapters, merges them, and generates the RST output structure.

create_root_index(book_names: List[str])

process_book(lines: List[str], book_config: Dict)

extract_chapters(lines: List[str], start_marker: str, end_marker: str, prefix: str) → Dict[str, Dict]

Extract chapters from a section of lines.

Parameters:

• lines – The list of lines to process.

• start_marker – The string marking the start of the section.

• end_marker – The string marking the end of the section.

• prefix – The prefix for chapter headers (e.g., “Cap”, “Gap”).

Returns:

A dictionary of chapters keyed by Roman Numeral ID.

Return type:

dict

merge_chapters(toc_chapters: Dict, text_chapters: Dict) → List[Dict]

Merge TOC and Text chapters into a single list.

Parameters:

• toc_chapters – Dictionary of chapters extracted from the TOC.

• text_chapters – Dictionary of chapters extracted from the text.

Returns:

A list of merged chapter dictionaries, sorted by Roman Numeral ID.

Return type:

list

generate_rst_structure(chapters: List[Dict], output_dir: pathlib.Path)

Generate the RST folder structure and files for the chapters.

Parameters:

• chapters – List of chapter dictionaries.

• output_dir – The directory where RST files will be generated.

create_main_index(chapters: List[Dict], output_dir: pathlib.Path)

create_chapter_files(chapter_dir: pathlib.Path, chapter: Dict)

indent_text(text: str, indent: str = '   ') → str

geometor.pacioli.extract_all(pdf_path: pathlib.Path, output_dir: pathlib.Path, start_page: int = 1, end_page: int = 318, dpi: int = 150, max_workers: int = 6, force: bool = False) → None

Extract page images and text for the entire volume in parallel.

geometor.pacioli.build_graphics_index(directory: pathlib.Path) → pathlib.Path

Compile all per-folio <folio>.json files into graphics_index.json.

geometor.pacioli.clean_image(pil_image: PIL.Image.Image, white_point: int = 226, preserve_color: bool = False) → PIL.Image.Image

Normalize aged parchment background and binding shadows to pure white (255).

Uses morphological closing + Gaussian blur to estimate local paper illumination per channel, eliminating yellowed paper cast, bleed-through, and gutter shadows while preserving crisp ink. When preserve_color=True (e.g., red rubrication on folios 0005 and 0311), chromatic ink is kept.

geometor.pacioli.detect_graphics_cv(image_path: pathlib.Path) → List[Dict[str, Any]]

Detect full-page plate graphics using OpenCV if available, falling back to SciPy.

geometor.pacioli.detect_initials(image_path: pathlib.Path) → List[Dict[str, Any]]

Detect woodcut illuminated initial caps by finding 2D ink-density centers along the text column edge.

Woodcut initials in the 1509 Paganini edition have consistent square dimensions: - Standard chapter initials: 120x132 px (padded around the ~112x118 woodcut frame) - Large treatise-opening initials (folios 0017 and 0085): 260x304 px - Title-page red initial D (folio 0005): 184x188 px

geometor.pacioli.detect_margin_figures(image_path: pathlib.Path, is_recto: bool) → List[Dict[str, Any]]

Detect geometric diagrams and marginalia strictly in the outer margin of a text folio.

• Odd (recto) folios: right outer margin (to the right of the main text column).

• Even (verso) folios: left outer margin (to the left of the main text column).

Never falls back to full-page text blocks.

geometor.pacioli.extract_from_json(json_path: pathlib.Path, no_clean: bool = False) → None

Extract all margin graphics and illuminated initial caps defined in <folio>.json.