Ultralytics YOLOv8, YOLOv9, YOLOv10, YOLOv11 for ROS 2

Train and Inference your custom YOLO-NAS model by Single Command Line

🚀 ⭐ The list of the most popular YOLO algorithms - awesome YOLO

Object tracking pipelines complete with YOLOv9, YOLO-NAS, YOLOv8, and YOLOv7 detection and BYTETracker tracking

Inference YOLO-NAS ONNX model

This repo provides the C++ implementation of YOLO-NAS based on ONNXRuntime for performing object detection in real-time.Support float32/float16/int8 inference.

Train and Inference your custom YOLO-NAS model by Pytorch on Windows

This repository contains code for object tracking in videos using the YOLO-NAS object detection model and the DeepSORT algorithm.

YOLO-NAS for ROS 2

This repository contains project of yolo-NAS (which gives more accurate result out of all other yolo versions), you can use these projects as a reference for building innovative projects using yolo-nas, It also contain links to some pre-trained custom model which you can use for your work

C++ implementation of YOLO-NAS utilizing OpenVINO backend

An CPP library for object detection with full processing using OpenCV DNN (for ONNX) on YOLO-NAS model.

Multi-object tracking using a tracking-by-detection scheme with YOLO-NAS + DeepSORT.

Go gRPC client for YOLO-NAS, YOLOv8 inference using the Triton Inference Server.

YOLO-NAS module for use with Autodistill.

Object detection Image data analysis or EDA

C++ implementation of YOLO-NAS using DeepSparse

SAMYOL is a Python library that combines an object detection model and a segmentation model.

Third year university dissertation. Continuous Assessment for ECM3401 - Individual Literature Review and Project. Involves the implementation of a human pose estimation computer vision model to detect two combat athletes, and a machine learning algorithm to identify their grappling position.

This repository contains a Streamlit web application for vehicle tracking using different SOTA object detection models. The app offers two options: YOLO-NAS with SORT tracking and YOLOv8 with ByteTrack and Supervision tracking. It enables users to upload a video file, set confidence levels, and visualize the tracking results in real-time.