ultralytics/notebooks

In this repo there are some tips and a template to train your YOLO model for any kind of computer vision application

Ultralytics YOLOv5 in PyTorch for object detection, instance segmentation, classification, training, and export.

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, and Qwen3-VL.

Ready-to-use Cog deployments and CI/CD for running Ultralytics YOLO11, YOLO World, YOLOE, and YOLO26 models on Replicate.

All-in-one training for vision models (YOLO, ViTs, RT-DETR, DINOv3): pretraining, fine-tuning, distillation.

Easily train or fine-tune SOTA computer vision models with one open source training library. The home of Yolo-NAS.

Ultralytics YOLO27, YOLO26, YOLO11, YOLOv8 — object detection, instance segmentation, semantic segmentation, image classification, pose estimation, object tracking

OpenMMLab YOLO series toolbox and benchmark. Implemented RTMDet, RTMDet-Rotated,YOLOv5, YOLOv6, YOLOv7, YOLOv8,YOLOX, PPYOLOE, etc.