Yolo X, v3 ~ v12 and several Multi-Object Tracker(SORT, DeepSORT, ByteTrack, BoT-SORT, etc.) in MOT17 and VisDrone2019 Dataset. It uses a unified style and integrated tracker for easy embedding in your own projects.

This repo host a comprehensive solution for multi-object tracking in combination with YOLO and DeepSORT in carla simulator .

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

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This project implements real-time object detection and tracking using YOLO (You Only Look Once) for detection and DeepSORT for multi-object tracking. The system can identify and track multiple objects in video streams using deep learning models.

Real-time multi-object tracking and behavior analysis using YOLO and DeepSORT.

YOLO and DeepSORT multi-object tracking.

Multi-object detection and tracking using YOLOv8 and DeepSORT

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End-to-end person detection and tracking project using YOLOv5, SORT, and DeepSORT. A merged person-only dataset from Roboflow and Kaggle was used for training, followed by detection optimization and comparison of motion-based and appearance-based tracking methods.

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

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基于yolov5和deepsort的行人或车辆跟踪计数系统

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A practical surveillance system using YOLO and DeepSORT for pedestrian detection, multi-object tracking, and region-based behavior analysis with time-window alarm mechanisms.

Everything.AI is a comprehensive real-time object detection and tracking system. It leverages YOLO v4 for object detection and DeepSORT for multi-object tracking, combined with a knowledge base to provide context-rich information about every recognized entity in the scene.

## 🚗 Automatic Number Plate Detection, Tracking & OCR This project performs **real-time vehicle number plate detection, tracking, and text extraction** from video. It combines object detection (**YOLO**), multi-object tracking (**DeepSORT**), and optical character recognition (**EasyOCR**) into one end-to-end pipeline.

YOLO-DeepSORT-Vehicle-Tracking integrates YOLOv8 for real-time vehicle detection with DeepSORT for multi-object tracking. Designed for urban traffic monitoring, it assigns unique IDs to vehicles across frames, enabling precise counting and movement analysis. Ideal for applications in smart cities, surveillance, and traffic analytics.

Collected and preprocessed image/video data, including annotation and frame normalization. Trained object detection models (YOLO / Faster R-CNN) to detect vehicles in video streams. Applied multi-object tracking techniques (SORT / DeepSORT) to count unique cars and avoid duplicate detections.

A fully-integrated YOLO + DeepSORT multi-object tracking pipeline for robotics perception. This repo detects objects in real-time, assigns consistent IDs, and tracks them across occlusions using appearance embeddings + Kalman filters. Ideal for autonomous robots, drones, warehouse systems, and human-robot interaction scenarios.

An AI-based classroom attention tracking system using YOLO for face detection, DeepSORT for multi-object tracking, and a ResNet-50 CNN to estimate attention based on gaze direction. The system computes attention metrics over time from video input without performing identity or emotion recognition.