Real-Time Animal Identification & Deterrence 🐱👁
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Updated
May 12, 2023 - JavaScript
Real-Time Animal Identification & Deterrence 🐱👁
Simple script to create your own .cfg to train a Darknet YOLO model
People tracking in crowded locations using multiple object Tracking (MOT)
Application to process YouTube videos and detect objects within the video frames, deployed in GCP with Terraform
Draw a shape in space with your hand and make the drone replicate this shape!
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.
This is a project of Object Detection using YOLOv4 and Deep SORT
Project: Implementation of cat (fluffy object) detection on Raspberry Pi 4, and its android mobile application.
The objective of this project is to demonstrate the implementation of object detection using the YOLO model, transformers library, and OpenCV. The provided Python script utilizes a pre-trained YOLO model (hustvl/yolos-tiny) for detecting objects in images.
A lightweight face mask detection model with a high ability to detect a person with the mask or without a mask at any type of movement.
Blackbeard - Smart glasses blackjack AI project for Harvard Wearable & Computer Vision Class DGMD E-14 Fall 2021
It's a work-in-progress repo!
NTU Biophotonics and Bioimaging Lab dairy cow face monitoring project. Tensorflow Lite + OpenCV + Raspicam.
A ROS C++ pacakge for Swarm of 20 robots(TurtleBot3) to perform a search and rescue operation. Each robot navigates autonomously to a designated waypoint, searches for humans, if a human is detected, plans a path to the nearest fire exit, and then returns back to its home location.
Base Image Processing repo focuses on YOLO (You Only Look Once) used in Jetson Nano & Raspberry Pi 4
Using YoloV4 Tiny for Traffic Light Recognition
ESP32-Cam Graphical User Interface using PyQt5
This repository contains an object detection tutorial to detect swimming pools and cars using YOLOv4-tiny with satellite imagery. The project includes training scripts, dataset configurations, and instructions for running the model on Google Colab.
This sample is an example of running an AI container on the Jetson platform utilizing GPU acceleration.
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