Ultralytics

Ultralytics is a platform and open-source library focused on computer vision tasks using YOLO models. It supports object detection, instance segmentation, image classification, pose estimation, and tracking. The core library is installable via pip and requires Python 3.8 or higher and PyTorch 1.8 or above. The Ultralytics Platform offers a unified workflow that includes dataset upload, annotation with manual and AI-assisted tools, cloud GPU training with real-time metrics, model export to multiple formats, deployment across global regions, and monitoring capabilities. It integrates with tools like Weights & Biases, Comet, and ClearML for experiment tracking and supports deployment to 43 regions with one-click endpoints. The platform supports five task types natively and provides annotation tools such as bounding boxes, polygons, keypoints, oriented bounding boxes, and classification labels. AI-assisted annotation features include SAM smart annotation and YOLO auto-labeling. Cloud training is available on GPUs ranging from RTX 4090 to H200. Models can be exported to 17 different formats including ONNX, TensorRT, CoreML, and TFLite. Ultralytics HUB offers a free tier, though detailed pricing for cloud GPU usage and deployment is not publicly specified.