A simple tutorial on MediaPipe Selfie Segmentation.
-
Updated
Sep 18, 2021 - CSS
A simple tutorial on MediaPipe Selfie Segmentation.
An online examination monitoring system employing YOLOv8, along with various other deep learning and machine learning approaches, centered around computer vision.
A website that can live stream and detect data using mediapipe module. Created at Line of Code Hackathon to aid soldiers.
Quick usage of MediaPipe's selfie segmentation model.
"Welcome to our posture detection and pose classification web application repository! Utilizing Python, Flask, and libraries like Mediapipe, we empower users to monitor and classify human poses in real-time through webcam interactions. Perfect for fitness monitoring and gesture-based interfaces."
In this "Rock Paper Scissors" game, your hand signals face off with a robot, combining street smarts with smart machines in an interactive showdown of wits and technology. Experience the thrill as your gestures are swiftly recognized by the Mediapipe AI model, delivering seamless gameplay and immersive engagement.
A go-to fitness app, providing personalized workouts, diet plans, and real-time feedback to optimize your wellness journey and promote a balanced, active lifestyle.
This is my gym application project. This is an application that can count the number of pushups, curls and situps one has done. It can be used to monitor one's excercise.
"Posture Detection & Pose Classification Project: Utilizing Python, Jupyter IDE, and libraries like Mediapipe and Matplotlib, this project detects and classifies human poses such as Tree Pose, T Pose, Warrior II, etc. Ideal for applications like fitness monitoring and gesture-based interfaces."
Add a description, image, and links to the mediapipe topic page so that developers can more easily learn about it.
To associate your repository with the mediapipe topic, visit your repo's landing page and select "manage topics."