James 0b41a2174a Merge pull request #275 from roboflow/add-paligemma-link | 2 days ago | |
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.github | 1 year ago | |
assets | 1 year ago | |
automation | 2 days ago | |
notebooks | 2 days ago | |
.gitignore | 1 year ago | |
CONTRIBUTING.md | 1 year ago | |
README.md | 2 days ago |
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.
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!
How to Choose the Best Computer Vision Model for Your Project
Accelerate Image Annotation with SAM and Grounding DINO
SAM - Segment Anything Model by Meta AI: Complete Guide
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
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 Generation | YOLOv5 Custom Dataset Training | YOLOv7 Custom Dataset Training |
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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.