The goal of this project is to implement a committee-based tracking ensemble model for human detection and tracking. This repository contains ML models and FairMOT implementation.
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Updated
May 11, 2022 - Jupyter Notebook
The goal of this project is to implement a committee-based tracking ensemble model for human detection and tracking. This repository contains ML models and FairMOT implementation.
A real time face detection that captures video from your webcam. Highlights detected faces with bounding boxes in the live feed.
This project is designed to control light bulbs using a Raspberry Pi Pico.
Developed a real-time social distancing system with YOLOv3 and SSD for human detection, OpenCV for video processing, and Perspective transformation for bird's-eye view. Used Euclidean distance for accurate distance measurement, categorizing individuals into high, low, and no-risk groups for monitoring in public areas and workplaces.
Some basic works on image processing 🏃
World Smile - Does some computation and returns average smile data by location (DATA MINING).
This repository contains a code for human detection and congestion detection using OpenCV and an Arduino UNO
Implementation of Histogram of Oriented Gradients-based Human Detector from scratch
Hardware implementation for human detection by Histogram of Oriented Gradient (HOG)
To compute the HOG (Histograms of Oriented Gradients) feature from an input image and then classify the HOG feature vector into human or no-human by using a 3-nearest neighbor (NN) classifier.
Detecting persons skin in a video and make it greenish.
Detect humans in real-time, image or video and count the detected people using OpenCV and HOG Descriptor
An IoT embedded system leveraging machine learning to detect human presence and monitor ambient conditions for dynamic environmental control. Ideal for smart homes, workplaces, and sustainable systems.
Checks if human is in a picture or not
The YOLOv8-SORT-Human-Tracking repository demonstrates human tracking using YOLOv8 and the SORT algorithm, showcasing results of using YOLOv8 alone versus the combined method.
Active Crowd Analysis: Pandemic Risk Mitigation for the Blind or Visually Impaired
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