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notebooks | inference | autodistill | collect

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👋 hello

Over the years we have created dozens of Computer Vision tutorials. This repository contains examples and tutorials on using SOTA computer vision models and techniques. Learn everything from old-school ResNet, through YOLO and object-detection transformers like DETR, to the latest models like Grounding DINO, SAM, and GPT-4 Vision.

Curious to learn more about GPT-4 Vision? Check out our GPT-4V experiments 🧪 repository.

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🚀 model tutorials (42 notebooks)

notebookopen in colab / kaggle / sagemaker studio labcomplementary materialsrepository / paper
Fine-Tune GPT-4oColab KaggleRoboflow YouTube
YOLO11 Object DetectionColab KaggleRoboflow YouTubeGitHub
YOLO11 Instance SegmentationColab KaggleYouTubeGitHub
Segment Images with SAM2Colab KaggleRoboflow YouTubeGitHub arXiv
Segment Videos with SAM2Colab KaggleRoboflow YouTubeGitHub arXiv
RT-DETR Object DetectionColab KaggleRoboflowGitHub arXiv
Fine-Tune Florence-2 on Object Detection DatasetColab KaggleRoboflow YouTubearXiv
Run Different Vision Tasks with Florence-2Colab KaggleRoboflow YouTubearXiv
Fine-Tune PaliGemma on Object Detection DatasetColab KaggleRoboflow YouTubeGitHub arXiv
YOLOv10 Object DetectionColab KaggleRoboflowGitHub arXiv
Zero-Shot Object Detection with YOLO-WorldColab KaggleRoboflow YouTubeGitHub arXiv
YOLOv9 Object DetectionColab KaggleRoboflow YouTubeGitHub arXiv
RTMDet Object DetectionColab KaggleRoboflow YouTubeGitHub arXiv
Fast Segment Anything Model (FastSAM)Colab KaggleRoboflow YouTubeGitHub arXiv
YOLO-NAS Object DetectionColab KaggleRoboflow YouTubeGitHub
Segment Anything Model (SAM)Colab KaggleRoboflow YouTubeGitHub arXiv
Zero-Shot Object Detection with Grounding DINOColab KaggleRoboflow YouTubeGitHub arXiv
DETR Transformer Object DetectionColab KaggleRoboflow YouTubeGitHub arXiv
DINOv2 Image ClassificationColab KaggleRoboflowGitHub arXiv
YOLOv8 Object DetectionColab KaggleRoboflow YouTubeGitHub
YOLOv8 Pose EstimationColab KaggleRoboflowGitHub
YOLOv8 Oriented Bounding BoxesColab KaggleRoboflowGitHub
YOLOv8 Instance SegmentationColab KaggleRoboflow YouTubeGitHub
YOLOv8 ClassificationColab KaggleRoboflowGitHub
YOLOv7 Object DetectionColab KaggleRoboflow YouTubeGitHub arXiv
YOLOv7 Instance SegmentationColab KaggleRoboflow YouTubeGitHub arXiv
YOLOv7 Object Detection OpenVINO + TorchORTColab KaggleRoboflowGitHub arXiv
MT-YOLOv6 Object DetectionColab KaggleRoboflow YouTubeGitHub arXiv
YOLOv5 Object DetectionColab KaggleRoboflow YouTubeGitHub
YOLOv5 ClassificationColab KaggleRoboflow YouTubeGitHub
YOLOv5 Instance SegmentationColab KaggleRoboflow YouTubeGitHub
Detection2 Instance SegmentationColab KaggleRoboflow YouTubeGitHub arXiv
SegFormer Instance SegmentationColab KaggleRoboflow YouTubeGitHub arXiv
Vision Transformer ClassificationColab KaggleRoboflow YouTubeGitHub arXiv
Scaled-YOLOv4 Object DetectionColab KaggleRoboflow YouTubeGitHub arXiv
YOLOS Object DetectionColab KaggleRoboflow YouTubeGitHub arXiv
YOLOR Object DetectionColab KaggleRoboflow YouTubeGitHub arXiv
YOLOX Object DetectionColab KaggleRoboflow YouTubeGitHub arXiv
Resnet34 fast.ai ClassificationColab KaggleRoboflow YouTube
OpenAI Clip ClassificationColab KaggleRoboflow YouTubeGitHub arXiv
YOLOv4-tiny Darknet Object DetectionColab KaggleRoboflow YouTubeGitHub arXiv
Train a YOLOv8 Classification Model with No LabelingColab KaggleRoboflowGitHub

📸 computer vision skills (20 notebooks)

notebookopen in colab / kaggle / sagemaker studio labcomplementary materialsrepository / paper
Football AIColab KaggleRoboflow YouTubeGitHub
Automated Dataset Annotation with GroundedSAM 2Colab KaggleRoboflowGitHub
How to Estimate Vehicle SpeedColab KaggleRoboflow YouTubeGitHub
Detect and Count Objects in Polygon Zone with YOLOv5 / YOLOv8 / Detectron2 + SupervisionColab KaggleRoboflow YouTubeGitHub
Track and Count Vehicles with YOLOv8 + ByteTRACK + SupervisionColab KaggleRoboflow YouTubeGitHub arXiv
Football Players Tracking with YOLOv5 + ByteTRACKColab KaggleRoboflow YouTubeGitHub arXiv
Auto Train YOLOv8 Model with AutodistillColab KaggleRoboflow YouTubeGitHub
Image Embeddings Analysis - Part 1Colab KaggleYouTubeGitHub arXiv
Automated Dataset Annotation and Evaluation with Grounding DINO and SAMColab KaggleRoboflow YouTubeGitHub arXiv
Automated Dataset Annotation and Evaluation with Grounding DINOColab KaggleYouTubeGitHub arXiv
Roboflow Video Inference with Custom AnnotatorsColab KaggleRoboflowGitHub
DINO-GPT-4V Object DetectionColab KaggleRoboflow
Train a Segmentation Model with No LabelingColab KaggleRoboflowGitHub
DINOv2 Image RetrievalColab KaggleGitHub arXiv
Vector Analysis with Scikit-learn and BokehColab KaggleRoboflow
RF100 Object Detection Model BenchmarkingColab KaggleRoboflow YouTubeGitHub arXiv
Create Segmentation Masks with RoboflowColab KaggleRoboflow
How to Use PolygonZone and Roboflow SupervisionColab KaggleRoboflow
Train a Package Detector With Two Labeled ImagesColab KaggleRoboflowGitHub
Image-to-Image Search with CLIP and faissColab KaggleRoboflow
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🎬 videos

Almost every week we create tutorials showing you the hottest models in Computer Vision. 🔥 Subscribe, and stay up to date with our latest YouTube videos!

<p align="left"> <a href="https://youtu.be/CilXrt3S-ws" title="How to Choose the Best Computer Vision Model for Your Project"><img src="https://github.com/roboflow/notebooks/assets/26109316/73a01d3b-cf70-40c3-a5e4-e4bc5be38d42" alt="How to Choose the Best Computer Vision Model for Your Project" width="300px" align="left" /></a> <a href="https://youtu.be/CilXrt3S-ws" title="How to Choose the Best Computer Vision Model for Your Project"><strong>How to Choose the Best Computer Vision Model for Your Project</strong></a> <div><strong>Created: 26 May 2023</strong> | <strong>Updated: 26 May 2023</strong></div> <br/> In this video, we will dive into the complexity of choosing the right computer vision model for your unique project. From the importance of high-quality datasets to hardware considerations, interoperability, benchmarking, and licensing issues, this video covers it all... </p> <br/> <p align="left"> <a href="https://youtu.be/oEQYStnF2l8" title="Accelerate Image Annotation with SAM and Grounding DINO"><img src="https://github.com/SkalskiP/SkalskiP/assets/26109316/ae1ca38e-40b7-4b35-8582-e8ea5de3806e" alt="Accelerate Image Annotation with SAM and Grounding DINO" width="300px" align="left" /></a> <a href="https://youtu.be/oEQYStnF2l8" title="Accelerate Image Annotation with SAM and Grounding DINO"><strong>Accelerate Image Annotation with SAM and Grounding DINO</strong></a> <div><strong>Created: 20 Apr 2023</strong> | <strong>Updated: 20 Apr 2023</strong></div> <br/> Discover how to speed up your image annotation process using Grounding DINO and Segment Anything Model (SAM). Learn how to convert object detection datasets into instance segmentation datasets, and see the potential of using these models to automatically annotate your datasets for real-time detectors like YOLOv8... </p> <br/> <p align="left"> <a href="https://youtu.be/D-D6ZmadzPE" title="SAM - Segment Anything Model by Meta AI: Complete Guide"><img src="https://github.com/SkalskiP/SkalskiP/assets/26109316/6913ff11-53c6-4341-8d90-eaff3023c3fd" alt="SAM - Segment Anything Model by Meta AI: Complete Guide" width="300px" align="left" /></a> <a href="https://youtu.be/D-D6ZmadzPE" title="SAM - Segment Anything Model by Meta AI: Complete Guide"><strong>SAM - Segment Anything Model by Meta AI: Complete Guide</strong></a> <div><strong>Created: 11 Apr 2023</strong> | <strong>Updated: 11 Apr 2023</strong></div>

<br/> Discover the incredible potential of Meta AI's Segment Anything Model (SAM)! We dive into SAM, an efficient and promptable model for image segmentation, which has revolutionized computer vision tasks. With over 1 billion masks on 11M licensed and privacy-respecting images, SAM's zero-shot performance is often superior to prior fully supervised results... </p>

💻 run locally

We try to make it as easy as possible to run Roboflow Notebooks in Colab and Kaggle, but if you still want to run them locally, below you will find instructions on how to do it. Remember don't install your dependencies globally, use venv.

# clone repository and navigate to root directory
git clone git@github.com:roboflow-ai/notebooks.git
cd notebooks

# setup python environment and activate it
python3 -m venv venv
source venv/bin/activate

# install and run jupyter notebook
pip install notebook
jupyter notebook

☁️ run in sagemaker studio lab

You can now open our tutorial notebooks in Amazon SageMaker Studio Lab - a free machine learning development environment that provides the compute, storage, and security—all at no cost—for anyone to learn and experiment with ML.

Stable Diffusion Image GenerationYOLOv5 Custom Dataset TrainingYOLOv7 Custom Dataset Training
SageMakerSageMakerSageMaker

🐞 bugs & 🦸 contribution

Computer Vision moves fast! Sometimes our notebooks lag a tad behind the ever-pushing forward libraries. If you notice that any of the notebooks is not working properly, create a bug report and let us know.

If you have an idea for a new tutorial we should do, create a feature request. We are constantly looking for new ideas. If you feel up to the task and want to create a tutorial yourself, please take a peek at our contribution guide. There you can find all the information you need.

We are here for you, so don't hesitate to reach out.