In this post, we'll be looking at how to create desktop applications with TensorFlow.js and Node.js.
TensorFlow.js is a powerful tool for machine learning in JavaScript. Node.js is a JavaScript runtime that allows you to run JavaScript code outside of the browser.
Together, these two technologies can be used to create desktop applications that use machine learning.
To get started, you'll need to install Node.js and TensorFlow.js.
Node.js can be downloaded from the Node.js website. TensorFlow.js can be installed using the Node.js package manager:
npm install @tensorflow/tfjs
Once you have Node.js and TensorFlow.js installed, you're ready to start creating your desktop application.
To create a desktop application with TensorFlow.js and Node.js, you'll need to create a Node.js file and a HTML file.
The Node.js file will be used to run your machine learning code. The HTML file will be used to display the results of your machine learning code.
We'll start by creating a Node.js file called main.js
. In this file, we'll require the TensorFlow.js library and load a pre-trained model.
const tf = require('@tensorflow/tfjs');
// Load a pre-trained model.
const model = tf.loadModel('https://storage.googleapis.com/tfjs-models/tfjs/mobilenet_v1_0.25_224/model.json');
Next, we'll create an HTML file called index.html
. In this file, we'll include the following code:
<html>
<head>
<script src="https://cdn.jsdelivr.net/npm/@tensorflow/tfjs"></script>
<script src="main.js"></script>
</head>
<body>
<h1>Hello, TensorFlow.js!</h1>
</body>
</html>
This code includes the TensorFlow.js library and the main.js
file. It also contains a simple <h1>
tag.
Finally, we'll need to run the index.html
file using Node.js. We can do this by running the following command:
node index.html
This will start a local server and open the index.html
file in your default web browser.
In this post, we've seen how to create desktop applications with TensorFlow.js and Node.js. We've also seen how to load a pre-trained model and run it in a Node.js file.
If you're interested in learning more about TensorFlow.js and Node.js, I recommend checking out the following resources: