ultralytics

YOLOv5 🚀 in PyTorch > ONNX > CoreML > TFLite

Ultralytics YOLO11 🚀

YOLOv3 in PyTorch > ONNX > CoreML > TFLite

NVIDIA DeepStream SDK 7.1 / 7.0 / 6.4 / 6.3 / 6.2 / 6.1.1 / 6.1 / 6.0.1 / 6.0 / 5.1 implementation for YOLO models

Open Source Generative Process Automation (i.e. Generative RPA). AI-First Process Automation with Large ([Language (LLMs) / Action (LAMs) / Multimodal (LMMs)] / Visual Language (VLMs)) Models

🚀 Easier & Faster YOLO Deployment Toolkit for NVIDIA 🛠️

Convert JSON annotations into YOLO format.

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

Aim-bot based on AI for all FPS games

Ultralytics YOLOv8, YOLOv9, YOLOv10, YOLOv11, YOLOv12 for ROS 2

🚀 Use YOLO11 in real-time for object detection tasks, with edge performance ⚡️ powered by ONNX-Runtime.

Packaged version of ultralytics/yolov5 + many extra features

Ultralytics assets

Converting COCO annotation (CVAT) to annotation for YOLO-seg (instance segmentation) and YOLO-obb (oriented bounding box detection)

xView 2018 Object Detection Challenge: YOLOv3 Training and Inference.

ROS/ROS 2 package for Ultralytics YOLOv8 real-time object detection and segmentation. https://github.com/ultralytics/ultralytics

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

A PyTorch implementation of Spiking-YOLOv3. Two branches are provided, based on two common PyTorch implementation of YOLOv3(ultralytics/yolov3 & eriklindernoren/PyTorch-YOLOv3), with support for Spiking-YOLOv3-Tiny at present.

Easy-to-use finetuned YOLOv8 models.

YOLOv8-3D is a LowCode, Simple 2D and 3D Bounding Box Object Detection and Tracking , Python 3.10