Basic Motion Capture Pose Detection

This module uses MediaPipe and OpenCV to perform real-time pose detection on video sources. It captures video from a webcam or a file, processes each frame to detect and draw human pose landmarks, and optionally saves the processed video to a file.

An OpenCV game that uses Pose Recognition

Pose detection using YOLO v8

Cloning Your Pose using OpenCV and MediaPipe

Deploying a Pose Detection Model With Computer Vision

The Forculus Automatic Door Access System is designed to enhance security, efficiency, and energy savings in public spaces. By utilizing computer vision algorithms and intelligent person detection, the system ensures safe and contactless operation of automatic doors.

Scripts for detecting and visualizing pose landmarks on images using MediaPipe, including upper body cropping and combined visualizations.

Basic face, hand and pose Tracker.

Human pose estimation from video plays a critical role in various applications such as quantifying physical exercises, sign language recognition, and full-body gesture control.

🧘‍♂️🤖 Flask, OpenCV, and MediaPipe power this yoga project for real-time pose detection. Using a webcam feed, it dynamically classifies poses with MediaPipe, while Flask enables web deployment. OpenCV manages video streaming and image processing, creating an interactive platform for yoga enthusiasts to practice effectively.

Postrue is a Python-based application that empowers users to enhance their posture in real-time by detecting and correcting incorrect postures using Mediapipe and OpenCV libraries.

A pose detection cum timer implementation, however focused on preprocessing of the feed beforehand to filter feed fluctuations.

Machine vision project source code for workout assistent

Calculate OKS(Object Keypoints Similarity) from two sets of keypoints

This project utilizes MediaPipe, OpenCV, and a pose estimation module to create a real-time fitness tracker focusing on counting dumbbell curls. The user stands in front of a camera, and the program calculates the angle between the shoulder, elbow, and wrist to determine the movement direction and count the number of curls performed.

This project is a pose analysis and exercise counter using computer vision techniques with OpenCV, NumPy, and Mediapipe libraries. The program processes a video and tracks specific poses, calculates angles, and performs a curl counter for exercise analysis.

Python3 library for estimating a human pose from an image using machine learning techniques.