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Neuer Algorithmus in cv_words_first.py: Clustert Tesseract word_boxes direkt zu Spalten (X-Gap) und Zeilen (Y-Proximity), baut Zellen an Schnittpunkten. Kein Spalten-/Zeilenerkennung noetig. - cv_words_first.py: _cluster_columns, _cluster_rows, _build_cells, build_grid_from_words - ocr_pipeline_api.py: grid_method Parameter (v2|words_first) im /words Endpoint - StepWordRecognition.tsx: Dropdown Toggle fuer Grid-Methode - OCR-Pipeline.md: Doku v4.3.0 mit Words-First Algorithmus - 15 Unit-Tests fuer cv_words_first Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
38 lines
1.4 KiB
Python
38 lines
1.4 KiB
Python
"""
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CV-based Document Reconstruction Pipeline for Vocabulary Extraction.
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Re-export facade — all logic lives in the sub-modules:
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cv_vocab_types Dataklassen, Konstanten, IPA, Feature-Flags
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cv_preprocessing Bild-I/O, Orientierung, Deskew, Dewarp
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cv_layout Dokumenttyp, Spalten, Zeilen, Klassifikation
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cv_ocr_engines OCR-Engines, Vocab-Postprocessing, Text-Cleaning
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cv_cell_grid Cell-Grid (v2 + Legacy), Vocab-Konvertierung
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cv_review LLM/Spell Review, Pipeline-Orchestrierung
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Lizenz: Apache 2.0 (kommerziell nutzbar)
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DATENSCHUTZ: Alle Verarbeitung erfolgt lokal.
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"""
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from cv_vocab_types import * # noqa: F401,F403
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from cv_preprocessing import * # noqa: F401,F403
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from cv_layout import * # noqa: F401,F403
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from cv_ocr_engines import * # noqa: F401,F403
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from cv_cell_grid import * # noqa: F401,F403
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from cv_box_detect import * # noqa: F401,F403
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from cv_review import * # noqa: F401,F403
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# Private names used by consumers — not covered by wildcard re-exports.
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from cv_preprocessing import _apply_shear # noqa: F401
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from cv_layout import ( # noqa: F401
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_detect_header_footer_gaps,
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_detect_sub_columns,
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_split_broad_columns,
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)
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from cv_ocr_engines import ( # noqa: F401
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_fix_character_confusion,
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_fix_phonetic_brackets,
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)
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from cv_cell_grid import _cells_to_vocab_entries # noqa: F401
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from cv_words_first import build_grid_from_words # noqa: F401
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