In this Project Holistic Detection, it detect Left and Right Hand, Face Mesh, and Pose Detection using Libraries Opencv and Mediapipe in Python.
An OpenCV Python Holistic Detection We are going to detect left and right hand, face mesh, and pose detection. MediaPipe has a lot of built-in customizable Machine Learning Solutions. MediaPipe is the newest and fastest within machine learning solutions and can be run on common hardware which we are going to see throughout this article.
OpenCV is short for Open Source Computer Vision. Intuitively by the name, it is an open-source Computer Vision and Machine Learning library. This library is capable of processing real-time images and videos while also boasting analytical capabilities. It supports the Deep Learning frameworks.
MediaPipe is a Framework for building machine learning pipelines for processing time-series data like video, audio, etc. This cross-platform Framework works in Desktop/Server, Android, iOS, and embedded devices like Raspberry Pi and Jetson Nano.
MediaPipe Holistic utilizes the pose, face and hand landmark models in MediaPipe Pose, MediaPipe Face Mesh and MediaPipe Hands respectively to generate a total of 543 landmarks (33 pose landmarks, 468 face landmarks, and 21 hand landmarks per hand).
- Installed Python 3.10 and PyCharm on your computer.
- Install Mediapipe and setup Mediapipe Holistic for Python.
- Access a real time video feed from your webcam using OpenCV.
- Detect and visualise facial landmarks, body poses and hand poses.
