The following optimization measures are recommended for best performance:
- Document Preprocessing: Control the image resolution within 12 megapixels (about 4000×3000), and set DPI=200 to balance quality and speed when parsing PDFs.
- Task-specific tips: Select specific cues as needed (e.g.
prompt_layout_only_en(detecting only the layout) to avoid wasting resources on full-featured parsing - Batch Processing Configuration: Multi-page PDF parsing added
--num_threadsparameter (recommended value 64) to take full advantage of multi-core CPUs - hardware acceleration: Using CUDA 12.x environment with vLLM deployment, the recommended video memory utilization is set to 0.95 (
--gpu-memory-utilization 0.95) - Exception handlingSpecial characters can be switched to text-only alert mode, and continuous symbols require additional cleaning.
This answer comes from the articledots.ocr: a unified visual-linguistic model for multilingual document layout parsingThe
May not be reproduced without permission:AI productivity tools " What are some important performance optimization suggestions when using dots.ocr?
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