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Object Detection
Transformers.js

Transformers.js

Detect objects in your images

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What is Transformers.js ?

Transformers.js is a JavaScript library designed for object detection tasks. It allows developers to easily integrate AI-powered image analysis into web applications. The library simplifies the process of detecting objects within images by leveraging pre-trained models and providing an intuitive API.

Features

• Real-time Object Detection: Analyze images and detect objects in real-time. • Pre-trained Models: Access to state-of-the-art models optimized for accuracy and performance. • Lightweight Design: Optimized for web environments, ensuring fast loading and smooth operation. • Cross-browser Compatibility: Works seamlessly across modern web browsers.

How to use Transformers.js ?

  1. Include the Library: Add the Transformers.js script to your HTML file using a CDN or by hosting it locally.
  2. Initialize the Detector: Create an instance of the detector with a specific model.
  3. Load and Process the Image: Use the detector to analyze images and retrieve detection results.
  4. Handle Results: Process the detection results to display bounding boxes or other visual feedback.

Example code:

// Import the library
<script src="https://cdn.example.com/transformers.js"></script>

// Initialize the detector
const detector = new Transformers.ObjectDetector('model-name');

// Process an image
detector.detect('image.jpg').then(results => {
  // Handle detection results
  console.log(results);
});

Frequently Asked Questions

What browsers are supported by Transformers.js?
Transformers.js is designed to work with modern browsers, including Chrome, Firefox, Safari, and Edge.

How accurate is the object detection?
The accuracy depends on the specific model used. Transformers.js provides access to high-performance models optimized for various use cases.

Can I use custom models with Transformers.js?
Yes, Transformers.js supports custom models. You can load your own pre-trained models for specific detection tasks.

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