Getting Started with Face Landmark Detection with TensorFlow.JS

Getting Started with Face Landmark Detection with TensorFlow.JS

This tutorial is going to demonstrate similar logic for detecting the keypoints of a full face mesh using the `facemesh` model library.

In this tutorial, our work on implementing various demo apps using the TensorFlow.js library continues. In the most recent tutorial on using TensorFlow.js, we detected a specific hand gesture—a “thumbs-up” pose using the handpose library. This tutorial is going to demonstrate similar logic for detecting the keypoints of a full face mesh using the facemesh model library.

Specifically, we’ll learn how to detect face poses using the webcam and then draw the facial landmarks that make up a face mesh, using path and triangular face data matrices. The idea is to create a React app with a webcam stream that feeds the video data to the model, allowing it to make keypoint predictions.

Then, we’re going to load the facemesh library from TensorFlow.js and estimate the key points from the video stream. Lastly, we will draw these key points and triangles on a JavaScript canvas using the estimated data matrices.

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