ultralytics

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

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

PyTorch implementation of YOLOv3, YOLOv3-SPP, and YOLOv3-tiny for real-time object detection with training, validation, inference, and multi-format export.

Legacy JSON-to-YOLO dataset converter for COCO, LabelMe, Labelbox, VoTT, INFOLKS, and ATH annotations. Superseded by convert_coco() in the Ultralytics package.

Shared Ultralytics logos, media, sample images, pretrained model weights, dataset artifacts, and release assets.

Ultralytics YOLO iOS App source code for running YOLO in your own iOS apps 🌟

Flutter plugin for Ultralytics YOLO

Ultralytics Platform tutorials and support

Ultralytics YOLO tutorials for Colab, Kaggle, and SageMaker covering training, inference, export, and vision tasks.

Machine learning and Structure-from-Motion tools for estimating vehicle speed from imagery for traffic monitoring, road safety, and autonomous systems research.

Ultralytics model comparison docs and automated QA for websites, links, spelling, sitemaps, and image sizes.

Zero-dependency JavaScript AI chat widget with SSE streaming, search, page context, accessibility, and theming.

Retired Python SDK for the shut-down Ultralytics HUB API, kept for reference; build new integrations on the Ultralytics Platform REST API

Daily Ultralytics analytics for GitHub, PyPI, Google Analytics, Reddit, and Platform metrics, published as static JSON with historical star tracking.

MkDocs plugin for SEO metadata, social cards, JSON-LD, Git authors, Copy for LLM, and llms.txt generation.

Reusable Ultralytics pre-commit hooks for automated code-quality checks, formatting standards, and consistent repository hygiene.

AntiNeutrino Global Map (AGM) 2015 production code

MATLAB tools for machine-learning Earth observation, geospatial analysis, neutron mapping, and visualization.

Automated Python and OpenCV tool for resizing iOS screenshots to Apple App Store specifications across iPhone and iPad device formats.

CocoaPods specification repository for integrating the Ultralytics YOLO Swift library and Core ML computer vision models into iOS applications.

Deploy YOLO models to Replicate with ready-to-use Cog configurations and automated CI/CD. Includes optimized deployments for YOLO11, and reference implementations for custom model deployment.