People detection and optional tracking with Tensorflow backend.
-
Updated
Feb 21, 2021 - Python
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.
yolov8 with DeepSort_Tracking
Deep SORT + YOLOv3, Tensorflow, Keras, OpenCV
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.
Add a description, image, and links to the deep-sort-tracking topic page so that developers can more easily learn about it.
To associate your repository with the deep-sort-tracking topic, visit your repo's landing page and select "manage topics."