#mediapipe

[joe-bou-khalil-projects]

Real-Time Hand Tracking with MediaPipe Tasks Vision (ES Module Debug Template)

​A lightweight, single-file HTML5/JavaScript template demonstrating how to implement real-time hand landmark detection using Google MediaPip

Mediapipe hand tracking and movement view.

You can use in your next project.

[halfunusual]

Fun times ahead! 😁

[synthtv]

The most Pointless but fun MIDI controller

The most Pointless but fun MIDI controller

[old-crone-code]

i made my first game in 48hrs.

enjoy.

[yudi115649349]

webサイトを作りました 見てください。

[not-a-duck]

I'm so bad at focusing on stuff, it's unreal. Wanted to try reading a new book I received — it took less than a minute before I got distracted and started playing with pose detection software (mediapipe online pose landmark demo)... It's a pretty cool techdemo though :D

[learnopencv1]

What is Face Detection? – The Ultimate Guide for 2022

Let's understand what face detection is, how it works, what its challenges are, and in what areas face detection is used. You will also see

Face Detection is a computer vision technique in which a computer program can detect the presence of human faces and also find their location in an image or a video stream. Isn’t it mind-boggling how the mobile camera automatically detects your face every time you try to take a selfie? You must’ve also noted that it captures other people’s faces in the frame. Well, all this wouldn’t have been possible without Face Detection algorithms. With every passing year, Facial Detection algorithms are evolving to be faster and more robust.

In this post, you will get an overview of Face Detection itself. We will walk through various state-of-the-art Face Detectors and how they evolved over time.

[learnopencv1]

Driver Drowsiness Detection Using Mediapipe In Python

Driver drowsiness detection systems help reduce mishaps due to tired or sleepy drivers. Learn to build such a robust system using MediaPipe

Continuous driving can be tedious and exhausting. A motorist may get droopy and perhaps nod off due to inactivity. In this article, we will create a drowsy driver detection system to address such an issue. For this, we will use Mediapipe’s Face Mesh solution in python and the Eye Aspect ratio formula. Our goal is to create a robust and easy-to-use application that detects and alerts users if their eyes are closed for a long time.

In this post, we will:

Learn how to detect eye landmarks using the Mediapipe Face Mesh solution pipeline in python.

Introduce and demonstrate the Eye Aspect Ratio (EAR) technique. 

Create a Driver Drowsiness Detection web application using streamlit.

Use streamlit-webrtc to help transmit real-time video/audio streams over the network. 

Deploy it on a cloud service.