Fix: Prevent auto-splitting of French accented words in text recognition

[Ihebdhouibi]

Pull Request: Fix Auto-Splitting of French Accented Words in Text Recognition

📋 Summary

This PR fixes a bug where French words containing accented characters (é, è, à, ç, etc.) and contractions (n'êtes, l'été) were incorrectly split at each accented character during OCR text recognition word grouping.

🐛 Problem Description

Issue

The BaseRecLabelDecode.get_word_info() method in ppocr/postprocess/rec_postprocess.py only recognized basic ASCII letters (a-z, A-Z) as word characters. Accented characters used in French and other Latin-based languages were incorrectly classified as "splitters", causing words to be broken apart.

Example of the Bug

Before the fix:

• Input: "été" (summer)

• Output: 3 separate words: ["é", "t", "é"] ❌

• Input: "français" (French)

• Output: 3 separate words: ["fran", "ç", "ais"] ❌

• Input: "n'êtes" (you are)

• Output: 3 separate words: ["n", "'", "êtes"] ❌

After the fix:

• Input: "été" → Output: 1 word: ["été"] ✅
• Input: "français" → Output: 1 word: ["français"] ✅
• Input: "n'êtes" → Output: 1 word: ["n'êtes"] ✅

✨ Solution

Changes Made

1. Added unicodedata import for Unicode character category detection
2. Implemented is_latin_char() helper function that properly identifies Latin letters with diacritics
3. Modified get_word_info() method to include accented characters in word grouping logic
4. Added apostrophe handling for French contractions

Technical Details

The fix uses Python's unicodedata module to check if a character belongs to the Letter category (L*) and has a Latin or French-based Unicode name. This ensures that characters like:

• é (LATIN SMALL LETTER E WITH ACUTE)
• è (LATIN SMALL LETTER E WITH GRAVE)
• à (LATIN SMALL LETTER A WITH GRAVE)
• ç (LATIN SMALL LETTER C WITH CEDILLA)

...are correctly recognized as word characters.

📁 Files Modified

Core Changes

• ppocr/postprocess/rec_postprocess.py
  • Added unicodedata import
  • Added is_latin_char() function
  • Modified BaseRecLabelDecode.get_word_info() method

Test Files

• test_french_accents.py (new)
  • Comprehensive test suite for French accented character handling
  • Tests various scenarios: simple accents, contractions, mixed text

🧪 Testing

Test Coverage

The included test script validates:

• Simple accented words: été, élève
• Words with ç: français
• Contractions with apostrophes: n'êtes, C'était
• Words with à: à demain
• Complex sentences with multiple accents

Running Tests

python test_french_accents.py

🔄 Backward Compatibility

✅ Fully backward compatible

This fix:

• Only adds new functionality (recognition of accented characters)
• Does not change behavior for existing ASCII text
• Does not modify the API or function signatures
• Uses standard library (unicodedata) - no new dependencies

All existing functionality remains unchanged. Code that worked before will continue to work exactly as before, with the added benefit of proper French (and other Latin-based language) support.

🌍 Impact

Languages Benefited

This fix improves OCR text recognition for all Latin-based languages that use diacritics, including:

• French: é, è, ê, à, â, ù, û, ç, ï, etc.
• Spanish: á, é, í, ó, ú, ñ, ü
• Portuguese: ã, õ, á, é, í, ó, ú, â, ê, ô, ç
• German: ä, ö, ü, ß
• Italian: à, è, é, ì, ò, ù
• And many more...

Use Cases

• Document digitization in French-speaking regions
• Multilingual OCR applications
• Legal and administrative document processing
• Educational material processing
• International business document handling

📊 Performance Impact

Negligible performance impact:

• The is_latin_char() function is only called for non-ASCII characters
• Uses efficient unicodedata standard library functions
• No additional loops or complex operations
• Same time complexity as the original implementation

🔍 Code Quality

✅ Passes all pre-commit hooks:

• black (code formatting)
• flake8 (linting)
• trailing whitespace check
• line ending normalization

📝 Related Issues

This fix addresses the issue where French and other Latin-based language texts are incorrectly segmented during OCR post-processing, improving the accuracy and usability of PaddleOCR for international users.

✅ Checklist

• [x] Code follows project style guidelines
• [x] Self-review completed
• [x] Comments added for complex logic
• [x] No breaking changes
• [x] Test script included
• [x] Documentation updated (this PR doc)
• [x] All pre-commit hooks pass

🙏 Acknowledgments

This fix was developed and tested on real-world French OCR scenarios, ensuring practical applicability and effectiveness.

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Ready for review and merge! 🚀

[CLAassistant]

All committers have signed the CLA.

[paddle-bot[bot]]

Thanks for your contribution!

[Ihebdhouibi]

The test failure appears to be unrelated to this PR. The error is: ModuleNotFoundError: No module named 'langchain.docstore'

This is occurring in PaddleX's retriever module (paddlex/inference/pipelines/components/retriever/base.py:25), which is trying to import:

from langchain.docstore.document import Document

This import path was deprecated in langchain and moved to:

from langchain_core.documents import Document

Refer to API reference : https://reference.langchain.com/python/integrations/langchain_google_community/?h=document#langchain_google_community.DocumentAIWarehouseRetriever