How to Use TensorFlow.js for Image Recognition in JavaScript

Learn how to use TensorFlow.js to build an image recognition model in JavaScript

Photo by Markus Winkler on Unsplash

TensorFlow.js is a JavaScript library for training and deploying machine learning models in web browsers and JavaScript environments. One of the most popular applications of machine learning is image recognition, which allows developers to train models to identify objects, people, and other features in images. In this article, we will show you how to use TensorFlow.js to build an image recognition model in JavaScript.

Let us begin.

First, we need to import the TensorFlow.js library into our JavaScript project. We can do this by adding the following code to the head of our HTML file:

<script src="https://cdn.jsdelivr.net/npm/@tensorflow/tfjs@2.0.1/dist/tf.min.js"></script>

Next, we will load our image dataset. TensorFlow.js provides a convenient tf.data.webcam function that allows us to use the webcam as a source of image data. We can use it to capture images and then convert them into tensors that can be passed to the model.

const webcam = await tf.data.webcam(webcamElement);
const imageTensor = webcam.capture();