Deep SORT + YOLOv3, Tensorflow, Keras, OpenCV
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Updated
Jan 22, 2020 - Python
Deep SORT + YOLOv3, Tensorflow, Keras, OpenCV
Implementation of various methods of single / multi object tracking 🐾🛰
People detection and optional tracking with Tensorflow backend.
Acquiring the demographic details such as Age and Gender of a person from a Surveillance Camera video using a custom trained CNN model.
Approaching Pedestrian Tracking problem on surveillance camera with YoloV5 for pedestrian detection and DeepSORT for tracking.
MOT using deepsort and yolov7 with c++. It also supports yolov5 as a detector.
yolov8 with DeepSort_Tracking
Deepsort with yolo series. This project support the existing yolo detection model algorithm (YOLOV8, YOLOV7, YOLOV6, YOLOV5, YOLOV4Scaled, YOLOV4, YOLOv3', PPYOLOE, YOLOR, YOLOX ).
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.
✌️ Detection and tracking hand from FPV: benchmarks and challenges on rehabilitation exercises dataset
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).
The easiest way to count pedestrians, cyclists, and vehicles on edge computing devices or live video feeds.
People detection and optional tracking with Tensorflow backend.
A really more real-time adaptation of deep sort
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.
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