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roboflow/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
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 9,682 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
README
👋 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 |
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| Object Detection with Google Gemini 3.5 Flash | | | |
| How to Perform OCR with GLM-OCR | | 
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| How to Track Objects with RF-DETR and ByteTrack Tracker | | | 
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| Fine-Tune YOLO26 on Object Detection Dataset | | 
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| Fine-Tune YOLO26 on Instance Segmentation Dataset | | | |
| Segment Images with SAM3 | | | 
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| Segment Videos with SAM3 | | | |
| Open Vocabulary Object Detection with Qwen3-VL | | | |
| Fine-Tune RF-DETR Segmentation on Custom Dataset | | | 
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| Zero-Shot Object Detection and Segmentation with Google Gemini 2.5 | | | 
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| Fine-Tune RF-DETR on Object Detection Dataset | | | |
| Zero-Shot Object Detection and Segmentation with YOLOE | | | 
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| Fine-Tune YOLOv12 on Object Detection Dataset | | | 
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| Zero-Shot Object Detection with Qwen2.5-VL | | | 
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| Fine-Tune Qwen2.5-VL for JSON Data Extraction | | | |
| Fine-Tune PaliGemma2 on Object Detection Dataset | | | 
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| Fine-Tune PaliGemma2 for JSON Data Extraction | | | |
| Fine-Tune PaliGemma2 for LaTeX OCR | | | |
| Fine-Tune SAM-2.1 | | | |
| Fine-Tune GPT-4o on Object Detection Dataset | | | |
| Fine-Tune YOLO11 on Object Detection Dataset | | | |
| Fine-Tune YOLO11 on Instance Segmentation Dataset | [
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