YOLOv8 object detection, tracking, image segmentation and pose estimation app using Ultralytics API (for detection, segmentation and pose estimation), as well as DeepSORT (for tracking) in Python. This app uses an UI made with streamlit and it can be deployed with Docker.

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YOLOv8 Object Detection with DeepSORT Tracking(ID + Trails)

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Système de détection et de suivi multi-objets (MOT) en temps réel utilisant YOLOv8 pour la détection et DeepSORT pour le tracking robuste.

Real-time object detection and multi-object tracking using YOLOv8 and DeepSORT. Includes edge optimization with TensorFlow Lite, deployment ready with Docker containerization.

This repository contains a project that integrates YOLOv8 with DeepSORT for object tracking and speed estimation. The aim is to perform object detection, tracking, and speed estimation of moving objects in videos.

The YOLOv8 model is used for real-time object detection in car image detection, identifying cars on images and videos. It includes preprocessing, object detection, object tracking with DeepSORT, and vehicle counting. This technology could increase traffic efficiency and improve safety measures.

Hybrid Decision Engine for real-time threat detection. Combines YOLOv8/ONNX object detection, DeepSort tracking, and 5-level state management (NORMAL→CRITICAL). Features temporal analysis, Bayesian fusion, and MCDM scoring. Production-ready with 1000+ FPS performance, comprehensive testing, and seamless integration for smart security systems.

yolov8目标跟踪与行人车辆计数+YOLOv8 Object Detection with DeepSORT Tracking(ID + Trails)

Object Detection using YOLOv8 with DeepSort Tracking

Object Detection & Tracking with YOLOv8 and DeepSORT

YOLOv8 Object Detection with DeepSORT Tracking(ID + Trails)

YOLOv8 Object Detection with DeepSORT Tracking(ID + Trails)

🚗 Real-time vehicle detection, classification, and counting using YOLOv8 with DeepSORT tracking.

Real-time object detection and tracking with YOLOv8, DeepSORT, and Streamlit.

yolov8目标跟踪与行人车辆计数+YOLOv8 Object Detection with DeepSORT Tracking(ID + Trails)

IMSE4175 object detection and tracking project on bicycle lanes(Combining DeepSORT with YOLOv5 & YOLOv8)

YOLOv8 Object Detection & DeepSORT Tracking App built with Streamlit — supports image detection, video analysis, and real-time webcam tracking

Real-time object detection and multi-object tracking system using YOLOv8 and DeepSORT with FastAPI and Streamlit dashboard

Real-Time Vehicle & Object Detection with YOLOv8 This project implements a real-time object detection, tracking, and counting system based on YOLOv8 and DeepSORT (ReID).

Real-time Object Detection and Tracking system using YOLOv8, DeepSORT, and OpenCV with persistent ID tracking and live video processing.

A real-time object detection and multi-object tracking system using YOLOv8 and DeepSORT, with a modern React + FastAPI web interface.

A comprehensive computer vision system that combines YOLOv8 object detection with DeepSORT tracking algorithm to provide real-time multi-object tracking with a beautiful React dashboard.

Real-time multi-object detection, tracking, and counting system using YOLOv8 and DeepSORT, with performance benchmarking and visual analytics dashboard.

This project implements a multiple object tracking system designed to track small randomly moving toys. It combines the object detection model YOLOv8 with the DeepSORT tracking algorithm.

Developed a real-time AI surveillance system using YOLOv8 and DeepSORT for object detection and multi-object tracking with unique ID assignment via webcam

Real-time multi-object tracking pipeline with YOLOv8 detection and ByteTrack/DeepSORT association. Evaluated on MOT17 benchmark with MOTA/IDF1 metrics. Includes Streamlit demo.

WasteVision AI: YOLOv8-powered object detection with DeepSORT tracking for real-time waste classification and monitoring. Designed to enable smarter, sustainable, and automated waste management.

This project implements a real-time object detection and tracking system using a pre-trained YOLOv8 model and DeepSORT tracker. It processes video inputs, detects objects with bounding boxes, tracks unique objects across frames, and generates analytics reports.