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Detect objects in an image
Transformers.js

Transformers.js

Detect objects in your images

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Transformers.js

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What is Transformers.js ?

Transformers.js is a lightweight JavaScript library designed to detect objects in images. It leverages modern AI technologies to enable seamless object detection directly in web applications. Built on top of TensorFlow.js, Transformers.js provides an easy-to-use interface for developers to integrate object detection capabilities into their projects.

Features

• Real-time object detection: Quickly identify objects within images. • Model support: Compatible with popular models like YOLOv5 and SSD MobileNet. • Image handling: Accepts images from files, URLs, or video streams. • Result visualization: Displays bounding boxes and class labels. • Cross-browser compatibility: Works on major browsers like Chrome, Firefox, and Safari. • Lightweight: Optimized for web use with minimal dependencies.

How to use Transformers.js ?

  1. Install the library using npm:
    npm install transformers.js
  2. Import the library in your JavaScript file:
    import Transformers from 'transformers.js';
  3. Initialize the detector:
    const detector = new Transformers.Detector();
  4. Load a pre-trained model (e.g., YOLOv5):
    await detector.loadModel('yolov5');
  5. Detect objects in an image:
    const results = await detector.detect(imageElement);
  6. Process the detection results:
    results.forEach(item => console.log(item.class, item.score));

Frequently Asked Questions

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

Can I use custom models with Transformers.js?
Currently, Transformers.js supports popular pre-trained models like YOLOv5 and SSD MobileNet. Custom models are not supported out of the box.

How accurate is Transformers.js for object detection?
Accuracy depends on the model used. Models like YOLOv5 offer high accuracy, but performance may vary based on image quality and complexity.

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