GitLab

docs(README): update online demo links and enhance documentation readability

- Update online demo links in both English and Chinese README files

docs(readme): update changelog for v1.1.0 release

docs(readme): update changelog for v1.1.0 release- Update model capabilities: upgrade to latest doclayout_yolo(2501) and unimernet(2501) models

- Improve performance: optimize resource usage and processing pipeline for faster parsing on high-end devices- Enhance parsing effects: add new heading classification feature to online demo
- Refactor changelog structure for better readability and organization

feat(table-config): add sub_model configuration for rapid_table

- Add sub_model configuration option for rapid_table model
- Provide two sub_model options: slanet_plus and unitable

docs(url): update Miners links in header

- Change Miners homepage link from 'https://mineru.org.cn/home?source=online' to 'https://mineru.net/home?source=online'
- Change Miners client download link from 'https://mineru.org.cn/client?source=online' to 'https://mineru.net/client?source=online'

docs(readme):update readme for 1.1.0

- Add timing measurement for formula, text, and title optimization using LLM
- Log the execution time for each LLM aided process

refactor(pdf_parse): uncomment char bbox validation logic

- Add a check to return 0 when either bbox1_area or bbox2_area is zero
- This prevents division by zero errors when calculating IoU

- Restore commented code for filtering out characters with invalid bounding boxes
- This change may affect the filtering of unnecessary characters in PDF parsing

perf(magic_pdf): optimize batch processing for GPU

- Update conditions for batch ratio assignment:
  -8 <= gpu_memory < 10: batch_ratio = 2 - 10 <= gpu_memory <= 12: batch_ratio =4
- This fix ensures proper batch ratio selection for GPU memory sizes

- Improve batch ratio calculation based on GPU memory
- Enhance performance for devices with 8GB or more VRAM

perf(magic_pdf): adjust batch ratio calculation for GPU memory

- Reduce batch_ratio by 1 for better performance and stability
- This change ensures more consistent memory usage when processing documents

perf(magic_pdf): optimize batch ratio calculation for GPU

refactor(magic_pdf): adjust VRAM allocation and MFR batch size- Update VRAM allocation logic to use 'VIRTUAL_VRAM_SIZE' environment variable
- Reduce MFR (Math Formula Recognition) batch size from 64 to 32

- Update GPU memory check and batch ratio calculation logic
- Add support for virtual VRAM size environment variable
- Improve logging for GPU memory and batch ratio

- Reduce YOLO_LAYOUT_BASE_BATCH_SIZE from 4 to 1
- Simplify batch ratio calculation for formula detection
- Remove unused conditional logic in batch ratio determination

fix(models): update unimernet_small model path

- Update model path from 'unimernet_small' to 'unimernet_small_2501' in multiple scripts and configuration files
- This change affects download_models.py, download_models_hf.py, and model_configs.yaml

fix(ocr): improve ONNX model initialization and error handling

- Add key length validation for ONNX model initialization
- Move import statements to the top of the file
- Wrap model initialization in a try-except block for better error handling
- Refactor code to improve readability and maintainability

feat(pdf_parse): remove tilted lines for better text extraction

- Add remove_tilted_line function to filter out lines with angles between 2 and 88 degrees
- Integrate the new function into the text extraction process
- Improve the accuracy of text block processing by removing non-horizontal/vertical lines

LGTM

feat(llm_aided): add reasonability check and fine-tuning guidelines

- Added instructions for checking the reasonability of heading levels
- Included guidelines for making fine adjustments based on context and logic
- Emphasized the importance of aligning the final result with the document's actual structure

fix(magic_pdf): limit batch ratio for GPU memory

- Commented out the original batch ratio calculation
- Set a fixed batch ratio of 2 for GPUs with less than 8 GB memory
- Increased batch ratio to 4 for GPUs with 8 GB or more memory

refactor(model): update config version check to 1.1.1

- Update the version check in download_models.py and download_models_hf.py
- Change the threshold from '1.1.0' to '1.1.1' for model configuration updates

refactor(table): add device configuration for Unitable model

- Import get_device function from magic_pdf.libs.config_reader- Update RapidTableModel initialization to include device parameter for Unitable model

docs(README): update WeChat group link