Ultralytics Python Packages

ultralytics

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

ultralytics-thop

PyTorch model profiler for computing MACs and parameter counts to measure deep learning model complexity.

ultralytics-platform

Official Python SDK for the Ultralytics Platform API

yolov5

Packaged version of ultralytics/yolov5 + many extra features

epokio

Phone alerts when an ML training run stalls, hits NaN or finishes, from the logs it already writes. No code changes, no account.

ultralytics-opencv-headless

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

trackforge

Unified, high-performance computer vision tracking library

ultralytics-actions

Ultralytics GitHub Actions for formatting, PR reviews, labeling, CI retries, CLA checks, and dependency updates.

esmoe

Drop-in expert-sparse MoE block for Ultralytics YOLO, with a router loss that reaches the optimiser.

ultralytics-yolov5

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

pixpick

Interactive vision input toolkit for CV frameworks, generate bbox, polygons, lines and points for Ultralytics, SAM, Supervision and many more.

yolo-scout

A repository to analyse the quality of your YOLO dataset

visionstyle

Configurable bounding boxes, labels and tracking trails for object detection. 22 presets, a live Studio editor and a CLI.

ultralytics-dev

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

asone

Easy & Modular Computer Vision Detectors, Trackers & SAM - Run YOLOv9,v8,v7,v6,v5,R,X in under 10 lines of code.

waffle-hub

🧇Waffle Hub🧇 is Deep Learning 🛠️Open Source Framework Adapter. It provides you 😎no-code, 😏easy training and inference!

trajectory-forecast

Forecast where tracked objects will move next. A lightweight extension to Ultralytics YOLO that adds Kalman-filtered trajectory prediction; stable, low-jitter, and efficient for real-time systems.

visiofirm

VisioFirm: Cross-Platform AI-assisted Annotation Tool for Computer Vision

ml-pipes-ultralytics

Compose YOLO-powered pipelines with ml-pipes, using Ultralytics operators for prediction, embeddings, tracking, and result processing.

ml-pipes-supervision

Compose computer-vision pipelines with ml-pipes, using Supervision operators for annotation, tracking, detection processing, and zone counting.

syml-ultralytics

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

ultralytics-rknn

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

streamgrid

Multi-stream video inference with Ultralytics YOLO - Display multiple video streams in a grid layout with real-time object detection.

modeyolo

ModeYOLO: Elevate image processing with this Python package. Seamlessly perform color space transformations, simplify dataset modification for deep learning, and leverage OpenCV and NumPy. Ideal for YOLO projects, computer vision tasks, and efficient machine learning workflows.