Where blog posts go to become runnable code

What it does This repository is the companion code vault for LearnOpenCV.com. Each folder corresponds to a blog post, providing code examples that readers can run rather than transcribe from articles. The collection covers classical OpenCV, deep learning, and recent generative AI.

The interesting bit The breadth is the point. You will find minimal working examples for YOLO variants, Gaussian Splatting, vision-language models, medical imaging, edge deployment on Jetson and Arduino, and even LLM serving—making it a useful search target when you need to see a recent CV technique in code.

Key highlights

• Massive topical range: object detection, pose estimation, 3D reconstruction, VLM fine-tuning, RAG pipelines, and robotics
• Directly tied to specific blog posts with linked explanations
• Includes edge and embedded examples (Jetson Nano, Arduino) alongside desktop workflows
• Covers both core OpenCV techniques and recent model releases (YOLO26, Qwen3, SAM-3)
• 22,992 stars suggest it has served as a de facto reference for many developers

Caveats

• Not a library or framework; each folder is standalone and consistency varies
• Some blog posts listed in the README have no corresponding code folder
• The repository is essentially an index; there is no shared infrastructure between examples

Verdict Worth bookmarking if you learn by dissecting working examples, or if you need a quick sanity check for a new vision paper’s implementation. Skip it if you are looking for a maintained package to import.