Transformers.js

What is Transformers.js ?

Transformers.js is a JavaScript library designed for object detection tasks. It allows developers to upload images and detect objects within them using advanced AI models. Built on top of modern JavaScript capabilities, Transformers.js provides an intuitive interface for integrating object detection into web applications.

Features

• Cross-browser support: Works seamlessly across major web browsers. • Real-time object detection: Quickly identifies objects within uploaded images. • Customizable models: Supports various pre-trained models for different detection needs. • Asynchronous processing: Efficiently handles image processing without blocking the main thread. • Integration with popular frameworks: Compatible with React, Vue, and Angular. • Lightweight design: Optimized for performance with a small footprint.

How to use Transformers.js ?

1. Install the library: Use npm to install Transformers.js in your project.

   npm install transformers.js
   

2. Import the library: Include Transformers.js in your JavaScript file.

   const Transformers = require('transformers.js');
   

3. Initialize the detector: Create a new instance of the object detector.

   const detector = new Transformers.Detector();
   

4. Load a model: Load a pre-trained model for object detection.

   detector.loadModel('coco-ssd');
   

5. Detect objects: Pass an image element or URL to the detector.

   const img = document.getElementById('image');
   detector.detect(img).then(results => {
     // Handle detection results
   });
   

6. Process results: Use the returned results to display detected objects.
7. Clean up: Release resources when done.

   detector.dispose();
   

Frequently Asked Questions

What browsers are supported by Transformers.js?
Transformers.js supports modern browsers including Chrome, Firefox, Safari, and Edge.

Can I use Transformers.js with video inputs?
Yes, Transformers.js can process video streams by capturing frames and detecting objects in real-time.

How do I improve detection accuracy?
For better accuracy, use higher-resolution images and experiment with different pre-trained models suitable for your specific use case.