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Object Detection
Transformers.js

Transformers.js

Detect objects in images

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Transformers.js

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What is Transformers.js ?

Transformers.js is a JavaScript library designed for object detection in images. It leverages modern JavaScript frameworks and APIs to provide a powerful, browser-based solution for detecting objects within visual content. The library is optimized for performance and ease of use, making it accessible to both developers and non-experts.

Features

• Object Detection: Identify and locate objects within images using pre-trained models.
• Real-Time Processing: Enable real-time object detection in web applications.
• High Accuracy: Pre-trained models ensure accurate detection across various object types.
• Customizable Models: Supports popular models like YOLO, SSD, and others.
• Threshold Adjustment: Configure confidence thresholds for detection accuracy.
• Lightweight: Built for performance in web environments.

How to use Transformers.js ?

  1. Install the Library: Use npm to install the package.
    npm install transformers.js
    
  2. Import in Code: Include the library in your JavaScript project.
    const { ObjectDetector } = require('transformers.js');
    
  3. Load a Model: Initialize a pre-trained object detection model.
    const detector = new ObjectDetector('yolo');
    
  4. Analyze Images/Video: Feed images or video streams to the detector.
    const results = await detector.detect(imageElement);
    
  5. Process Results: Handle detected objects and their coordinates.
    results.forEach(object => {
      console.log)object.label, object.x, object.y);
    });
    

Frequently Asked Questions

1. What browsers are supported by Transformers.js?
Transformers.js is designed to work with modern browsers supporting WebGL and WebAssembly for optimal performance.

2. Can I use custom models with Transformers.js?
Yes, Transformers.js allows integration with custom models as long as they are compatible with its architecture and formatting requirements.

3. How do I handle video streams?
For video streams, use the detect() method iteratively on each frame or use a Web Workers pattern to maintain smooth performance.

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