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Detect objects in an image
Transformers.js

Transformers.js

Detect objects in an image

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What is Transformers.js ?

Transformers.js is a JavaScript library designed to detect objects in images. It leverages modern transformer-based architectures to provide accurate and efficient object detection capabilities directly in the browser. The library enables developers to easily integrate object detection features into web applications, making it a powerful tool for real-time image analysis.

Features

• Object Detection: Identify objects within images using state-of-the-art transformer models.
• Real-Time Detection: Perform inference in real-time, making it suitable for interactive web applications.
• Pre-Trained Models: Access pre-trained models optimized for accuracy and performance.
• Browser Compatibility: Works seamlessly across modern web browsers.
• Customizable: Configure detection settings and models to meet specific use-case requirements.

How to use Transformers.js ?

  1. Include the Library: Add Transformers.js to your project via a CDN or npm/yarn.
<script src="https://cdn.jsdelivr.net/npm/@transformersjs/core@latest/dist/index.js"></script>
  1. Initialize the Detector: Create a detector instance with a pre-trained model.
const detector = new TransformersJs.Detector('model-name');  
  1. Load the Model: Load the selected model weights.
await detector.load();
  1. Detect Objects: Pass an image element or URL to the detector.
const predictions = await detector.detect(imageElement);
  1. Use Results: Process the detection results (e.g., display bounding boxes).
  2. Clean Up: Release resources when done.
detector.dispose();

Frequently Asked Questions

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

Can I use Transformers.js for real-time object detection?
Yes, Transformers.js is designed to perform real-time object detection, making it ideal for interactive applications.

How do I customize the detection model?
You can customize the detection model by specifying different architectures or fine-tuning pre-trained models to suit your needs.

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