#137 · Primary category： Education & Research
notebooks
A collection of tutorials on state-of-the-art computer vision models and techniques. Explore everything from foundational architectures like ResNet to cutting-edge models like RF-DETR, YOLO11, SAM 3, and Qwen3-VL.
Project last updated：08/14/26
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Why we included this project
Anyone learning computer vision by writing code instead of just reading about it will find this repo useful. It's a set of Jupyter notebooks, each a complete, runnable tutorial you can open in Google Colab and follow end to end. Examples start with older workhorses like ResNet and extend to recent models such as YOLO11, RF-DETR, SAM 3, and Qwen3-VL, covering detection, segmentation, and zero-shot tasks. The notebooks are kept current and share a consistent format, so they work both as a self-study path and as templates teams can adapt when wiring a new model into their own pipelines. If you prefer copying a working recipe over parsing a paper, this is a good place to start.
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