Face Mesh | mediapipe | deep learning скачать в хорошем качестве

Face Mesh | mediapipe | deep learning

This video is all about detecting and drawing 468 facial landmarks on direct webcam input footage at 30 frames per secong by using mediapipe liberary. In this we have used FaceMesh solution from mediapipe. MediaPipe Face Mesh is a face geometry solution that estimates 468 3D face landmarks in real-time even on mobile devices. It employs machine learning (ML) to infer the 3D surface geometry, requiring only a single camera input without the need for a dedicated depth sensor. Utilizing lightweight model architectures together with GPU acceleration throughout the pipeline, the solution delivers real-time performance critical for live experiences. Additionally, the solution is bundled with the Face Geometry module that bridges the gap between the face landmark estimation and useful real-time augmented reality (AR) applications. It establishes a metric 3D space and uses the face landmark screen positions to estimate face geometry within that space. It is very easy to build and write the code. The code is written in just about 30 lines. refrence - https://google.github.io/mediapipe/so... code - https://github.com/Pawandeep-prog/med... opencv reading from webcam -    • Reading and Saving Images | openCV tutoria...   timestamps: 0:00 - What we going to make 0:31 - Installing liberaries 1:06 - importing libs 1:30 - Reading from webcam 2:05 - coding landmark detection 8:00 - Changing colors 9:03 - Getting x-y co-ordinates 11:17 - Thanks Like and Subscribe LIKE + SHARE + SUBSCRIBE = support :) ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ contact me : 📞 facebook :   / proogramminghub   twitter 🐦 :   / programming_hut   github : https://github.com/Pawandeep-prog discord :   / discord   linkedin :   / programminghut   youtube ❤️:    / programminghutofficial   ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ mediapipe, face mesh, 468 landmarks, fast mesh, FaceMesh mediapipe, machine learning project, deep learning model, facial landmarks, 30 fps mesh, 30 fps face mesh, dl, ml, cv, opencv, numpy