GitLab

docs: reorganize inference acceleration sections in README 

docs: reorganize inference acceleration sections in README

Reordered sections related to inference acceleration using CUDA and CANN to provide a clearer structure in both English and Chinese README files.

fix(language): enhance language detection and text processing

fix(language): enhance language detection and text processing

- Improve language detection by removing newline characters from the input text
- Add error handling and fallback mechanism to deal with text containing control characters

Dev

feat(README): update for 1.0.0 release and add automatic language identification feature

- Update README.md and README_zh-CN.md for1.0.0 release
- Add information about new automatic language identification feature
- Include link to Ascend NPU Acceleration documentation
- Highlight improvements in API interface and compatibility

- Change fast-langdetect dependency from version 0.2.0 to >=0.2.3

Dev

- Change the default value of the language dropdown from an empty string to 'auto'
- This ensures a language is always selected by default, improving

- Remove conditional logic for OCR engine selection
- Always use RapidOCR as the OCR engine
- Simplify the __init__ method by removing unused code

- Update clear_bu.add() to exclude 'language' input

Dev

Dev

- Remove YOLO v11 language detection model from model_configs.yaml
- Update language detection utils to use a fixed model path instead of dynamic configuration
- Remove unused model weight parameter for YOLO v11 language detection

- Implement block sorting within image and table blocks
- Ensure correct order of captions and footnotes within blocks
- Improve overall document structure and parsing accuracy

- Update rapid_table dependency to version 0.3.0 in setup.py

refactor(langdetect): simplify language detection model

refactor(langdetect): simplify language detection model

- Remove LangDetectMode and related conditional logic
- Use a single model weight for language detection
- Add logging for language detection results
- Update model initialization and prediction methods

- Add language detection model initialization and integration
- Update model list to include language detection
- Refactor language detection utils for better model management

- Add separate models for Chinese/Japanese and English/French/German detection
- Implement mode-based detection to use appropriate models for different languages
- Update language detection process to use higher DPI for better accuracy
- Modify model initialization and prediction logic to support new language-specific models

refactor(docs): consolidate MS Office document conversion guides

refactor(docs): consolidate MS Office document conversion guides

docs/update_docs

fix(pdf_parse): ensure block bounding boxes do not have negative values 

fix(pdf_parse): ensure block bounding boxes do not have negative values 

- Add logic to set any negative values in block['bbox'] to 0
- This prevents potential errors when processing PDF blocks

add test case