roboflow/notebooks

★ 9,675⑂ 0

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

About roboflow/notebooks

roboflow/notebooks is an open-source project on GitHub, mainly written in Jupyter Notebook. A collection of tutorials on state-of-the-art computer vision models and techniques. It currently holds 9,675 stars and 0 forks with 0 open issues, and was last pushed on an unknown date (repository created unknown).

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GitHub Repository Details

Repository roboflow/notebooks · default branch - · size 0 KB · watchers 0 · source: GitHub REST API and repository README

README


notebooks | inference | autodistill | RF-DETR


👋 hello

This repository offers a growing collection of computer vision tutorials. Learn to use SOTA models like YOLOv11, SAM 2, Florence-2, PaliGemma 2, and Qwen2.5-VL for tasks ranging from object detection, segmentation, and pose estimation to data extraction and OCR. Dive in and explore the exciting world of computer vision!

🚀 model tutorials (61 notebooks)

| notebook | open in colab / kaggle / sagemaker studio lab | complementary materials | repository / paper | |:------------:|:-------------------------------------------------:|:---------------------------:|:----------------------:| | RF-DETR Keypoint Detection and Fine-Tuning | Colab Kaggle | | GitHub | | Object Detection with Google Gemini 3.5 Flash | Colab Kaggle | | | | How to Perform OCR with GLM-OCR | Colab Kaggle | YouTube | GitHub arXiv| | How to Track Objects with RF-DETR and ByteTrack Tracker | Colab Kaggle | YouTube | GitHub arXiv| | Fine-Tune YOLO26 on Object Detection Dataset | Colab Kaggle | Roboflow YouTube | GitHub | | Fine-Tune YOLO26 on Instance Segmentation Dataset | Colab Kaggle | Roboflow YouTube | GitHub | | Segment Images with SAM3 | Colab Kaggle | Roboflow YouTube | GitHub arXiv| | Segment Videos with SAM3 | Colab Kaggle | Roboflow YouTube | GitHub arXiv| | Open Vocabulary Object Detection with Qwen3-VL | Colab Kaggle | | GitHub | | Fine-Tune RF-DETR Segmentation on Custom Dataset | Colab Kaggle | Roboflow YouTube | GitHub arXiv| | Zero-Shot Object Detection and Segmentation with Google Gemini 2.5 | Colab Kaggle | Roboflow | arXiv| | Fine-Tune RF-DETR on Object Detection Dataset | Colab Kaggle | Roboflow YouTube | GitHub arXiv| | Zero-Shot Object Detection and Segmentation with YOLOE | Colab Kaggle | Roboflow YouTube | GitHub arXiv| | Fine-Tune YOLOv12 on Object Detection Dataset | Colab Kaggle | Roboflow | GitHub arXiv| | Zero-Shot Object Detection with Qwen2.5-VL | Colab Kaggle | Roboflow YouTube | GitHub arXiv| | Fine-Tune Qwen2.5-VL for JSON Data Extraction | Colab Kaggle | YouTube | GitHub arXiv| | Fine-Tune PaliGemma2 on Object Detection Dataset | Colab Kaggle | Roboflow | GitHub arXiv| | Fine-Tune PaliGemma2 for JSON Data Extraction | Colab Kaggle | Roboflow | GitHub arXiv| | Fine-Tune PaliGemma2 for LaTeX OCR | Colab Kaggle | Roboflow | GitHub arXiv| | Fine-Tune SAM-2.1 | Colab Kaggle | Roboflow YouTube | GitHub | | Fine-Tune GPT-4o on Object Detection Dataset | Colab Kaggle | Roboflow YouTube | | | Fine-Tune YOLO11 on Object Detection Dataset | Colab Kaggle | Roboflow YouTube | GitHub | | Fine-Tune YOLO11 on Instance Segmentation Dataset | Colab [![Kaggle](https://kaggle.com/static/images/open-in-ka

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