- [P] Autodistill: use big slow foundation models to train small fast supervised models https://github.com/autodistill/autodistill 5 comments machinelearning
Linking pages
- GitHub - roboflow/supervision: We write your reusable computer vision tools. 💜 https://github.com/roboflow/supervision 44 comments
- GitHub - roboflow/notebooks: 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 and SAM. https://github.com/roboflow/notebooks 1 comment
- My experience starting as a technical writer | James' Coffee Blog https://jamesg.blog/2023/11/27/technical-writing/ 0 comments
Linked pages
- GitHub - roboflow/inference: An opinionated tool for running inference on state-of-the-art computer vision models. https://github.com/roboflow/inference 16 comments
- GitHub - IDEA-Research/Grounded-Segment-Anything: Marrying Grounding DINO with Segment Anything - Openset Detection and Segmentation https://github.com/IDEA-Research/Grounded-Segment-Anything 15 comments
- GitHub - ultralytics/ultralytics: NEW - YOLOv8 🚀 in PyTorch > ONNX > OpenVINO > CoreML > TFLite https://github.com/ultralytics/ultralytics 12 comments
- Roboflow: Give your software the power to see objects in images and video https://roboflow.com/ 2 comments
- Distill Large Vision Models into Smaller, Efficient Models with Autodistill https://blog.roboflow.com/autodistill/ 1 comment
- Comparing AI-Labeled Data to Human-Labeled Data https://blog.roboflow.com/ai-vs-human-labeled-data/ 0 comments
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