This project focuses on real-time analysis of surveillance camera-generated video data, introducing an automated detection approach that leverages smart networks and algorithms.
-
Updated
Mar 3, 2024 - Jupyter Notebook
This project focuses on real-time analysis of surveillance camera-generated video data, introducing an automated detection approach that leverages smart networks and algorithms.
YOLOv9 Licence Plate Recognizion with easyOCR implementation
Traffic Signal Controll by Tracking, counting and speed estimation of vehicles on surveillance cameras using YOLO v9 and Reinforcement Learning
Counter surveillance system that detects vehicles that may be following you using ALPR. Designed simply with open source projects.
Revolutionizing security by detecting and tracking vehicles and individuals, enabling real-time access management with just a click.
The project focuses on developing a machine learning system capable of detecting the damages in the constructions
This is a Robot which can help you on our daily life with the Humanoid features it can be multitasking (help the unabled to reach objects, assistance on a daily basis)
How to Train YOLOv9 on a Custom Dataset
YOLOv9 Face 🚀 in PyTorch > ONNX > CoreML > TFLite
This repository provides a custom implementation of parsing function to the Gst-nvinferserver plugin when use YOLOv7/YOLOv9 model served by Triton Server using the Efficient NMS plugin exported by ONNX.
Traffic detection and notify C&C (prototype)
Smoke detection in two classes (white, black) with YOLO V9
System designed to provide real-time assistance to visually impaired individuals by detecting obstacles in their path and helping them finding desire objects in their environment.
Implementation of YOLOv9 and V2X Technology for Traffic Signal Priority
Implementation of Nvidia DeepStream 7 with YOLOv9 Models.
Implementation of paper - YOLOv9: Learning What You Want to Learn Using Programmable Gradient Information
The Purpose of this repository is to create a DeepStream/Triton-Server sample application that utilizes yolov7, yolov7-qat, yolov9 models to perform inference on video files or RTSP streams.
Add a description, image, and links to the yolov9 topic page so that developers can more easily learn about it.
To associate your repository with the yolov9 topic, visit your repo's landing page and select "manage topics."