Ultralytics YOLO 🚀

Ultralytics YOLOv5 in PyTorch > ONNX > CoreML > TFLite

We write your reusable computer vision tools. 💜

OpenMMLab Detection Toolbox and Benchmark

Label Studio is a multi-type data labeling and annotation tool with standardized output format

YOLOv4 / Scaled-YOLOv4 / YOLO - Neural Networks for Object Detection (Windows and Linux version of Darknet )

Ultralytics YOLOv3 in PyTorch > ONNX > CoreML > TFLite

YOLOX is a high-performance anchor-free YOLO, exceeding yolov3~v5 with MegEngine, ONNX, TensorRT, ncnn, and OpenVINO supported. Documentation: https://yolox.readthedocs.io/

OpenVINO™ is an open source toolkit for optimizing and deploying AI inference

Effortless data labeling with AI support from Segment Anything and other awesome models.

BoxMOT: Pluggable python and c++ SOTA multi-object tracking modules with support for axis-aligned and oriented bounding boxes

Go package for computer vision using OpenCV 4 and beyond. Includes support for DNN, CUDA, OpenCV Contrib, and OpenVINO.

YOLOv6: a single-stage object detection framework dedicated to industrial applications.

Single Shot MultiBox Detector in TensorFlow

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

校招、秋招、春招、实习好项目！带你从零实现一个高性能的深度学习推理库，支持大模型 llama2 、Unet、Yolov5、Resnet等模型的推理。Implement a high-performance deep learning inference library step by step

Effortless AI-assisted data labeling with AI support from YOLO, Segment Anything (SAM+SAM2/2.1+SAM3), MobileSAM!!

A PyTorch implementation of the YOLO v3 object detection algorithm

Self-hosted, local only NVR and AI Computer Vision software. With features such as object detection, motion detection, face recognition and more, it gives you the power to keep an eye on your home, office or any other place you want to monitor.

DAMO-YOLO: a fast and accurate object detection method with some new techs, including NAS backbones, efficient RepGFPN, ZeroHead, AlignedOTA, and distillation enhancement.