Implementation of "YOLOv13: Real-Time Object Detection with Hypergraph-Enhanced Adaptive Visual Perception".

Using yolov3 & yolov4 weights objects are being detected from live video frame along with the measurement of the object from the camera without the support of any extra hardware device.

This project aims to do real-time object detection through a laptop cam using OpenCV. The idea is to loop over each frame of the video stream, detect objects, and bound each detection in a box.

Implementation of the paper "YOLACT Real-time Instance Segmentation" in Tensorflow 2

Fast Moving Objects Detection (demo version)

AI-powered Driver Drowsiness Detection System using Computer Vision & Machine Learning for real-time driver alertness monitoring and accident prevention.

Real time object detection with OpenCV and deep learning models

Tensorflow 2.x implementation YOLACT

C++ implementation of YOLOv6 using TensorRT

Real-Time object detection app, built with Tensorflow.js.

Plug and Play Real-Time Object Detection App with Tensorflow and OpenCV. Run on Jetson TX2

Real-time American Sign Language (ASL) letters detection, via PyTorch, OpenCV, YOLOv5, Roboflow and LabelImg 🤟

A sample project for super fast real time object detection and counting using CHOOCH AI API and OpenCV.

This repository contains the code for real-time object detection. I'm using video stream coming from webcam. MobileNet-SSD and OpenCv has been used as base-line approach. TensorFlow object detection API has been used in revised approach.

This project addresses the escalating challenge of gun violence through the development of an advanced gun detection system.

Takes a youtube video/livestream and performs object detection by using the YOLO or SSD algorithm

ai app (text classifier, image classifier, real time object detection) using flutter and tflite packages

This project is a multi-AI app that features 🔢 digit recognition, 🕵️ object detection, and ⚡ real-time detection using Flutter and TensorFlow Lite.

Applied SSD integrated with MobileNet model for object (sign gestures) detection and recognition and the model is trained using Transfer Learning, with the aim to develop a web app for real-time ASL recognition from user input & then to generate text in English.