Juliofal4822/deepseek-ocr-multigpu-infer
🚀 Run efficient DeepSeek-OCR inference with Python scripts, supporting both single and multi-GPU setups for versatile performance on various hardware.
What's novel
🚀 Run efficient DeepSeek-OCR inference with Python scripts, supporting both single and multi-GPU setups for versatile performance on various hardware.
Code Analysis
4 files read · 2 roundsA thin orchestration wrapper that distributes image files across multiple GPU processes, each of which loads the DeepSeek-OCR VLM model and calls its .infer() method to convert document images to markdown.
Strengths
The multi-GPU process distribution logic is straightforward and functional, with reasonable use of multiprocessing.Manager for shared state and sensible image file discovery. The code is readable with clear logging and a clean CLI interface via argparse.
Weaknesses
Massive code duplication between the single-GPU and multi-GPU files (model loading, GPU info, image discovery, inference calls are nearly identical), the single-GPU file has a critical bug (uses Manager/Process without importing them), and the README describes a downloadable .exe application with PDF support that doesn't exist in the code. There are zero tests, placeholder URLs in setup.py, and unused dependencies (pdf2image).
Score Breakdown
Signal breakdown
Innovation
Craft
Traction
Scope
Evidence
Commits
10
Contributors
2
Files
12
Active weeks
4
Repository
Language
Python
Stars
1
Forks
0
License
MIT