People detection and optional tracking with Tensorflow backend.
A really more real-time adaptation of deep sort
The easiest way to count pedestrians, cyclists, and vehicles on edge computing devices or live video feeds.
Deepsort with yolo series. This project support the existing yolo detection model algorithm (YOLOV8, YOLOV7, YOLOV6, YOLOV5, YOLOV4Scaled, YOLOV4, YOLOv3', PPYOLOE, YOLOR, YOLOX ).
MOT using deepsort and yolov7 with c++. It also supports yolov5 as a detector.
✌️ Detection and tracking hand from FPV: benchmarks and challenges on rehabilitation exercises dataset
Approaching Pedestrian Tracking problem on surveillance camera with YoloV5 for pedestrian detection and DeepSORT for tracking.
Implementation of various methods of single / multi object tracking 🐾🛰
Acquiring the demographic details such as Age and Gender of a person from a Surveillance Camera video using a custom trained CNN model.
This project implements a person detection and tracking system using YOLOv8 for real-time object detection, Deep SORT for object tracking, and OSNet for person re-identification. The model assigns unique IDs to each person and tracks them throughout the video, even after occlusion or re-entry into the frame.
A fish viewer application that uses deep learning models to detect fish types and the length of fish using an image, video or a camera input.
Deep SORT + YOLOv3, Tensorflow, Keras, OpenCV
yolov8 with DeepSort_Tracking
An adaption of the prominent 'Deep Sort' Algorithm, with re-identification features.
People detection and optional tracking with Tensorflow backend.
This tracker is based on the use of a detector in the form of a YOLOv5s neural model and a tracking algorithm for tracking objects (DeepSORT).
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