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Object Detection
Transformers.js

Transformers.js

Upload an image to detect objects

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Transformers.js

Detect objects in images

0

What is Transformers.js ?

Transformers.js is a JavaScript library designed for object detection tasks. It allows users to upload an image and detect objects within it using advanced AI models. The library leverages pre-trained models to provide accurate and efficient object detection capabilities directly in web applications.

Features

  • Real-time Object Detection: Detect objects in images instantly with high accuracy.
  • Support for Multiple Models: Compatible with various pre-trained models for flexibility.
  • JavaScript Integration: Easily integrate into web applications with a simple API.
  • Customizable: Adjust detection parameters to suit your application needs.
  • Cross-Browser Compatibility: Works seamlessly across modern web browsers.
  • High Performance: Optimized for fast processing and minimal latency.

How to use Transformers.js ?

  1. Install the Library: Include Transformers.js in your project using npm or CDN.
  2. Import the Library: Add the necessary script tags or imports in your HTML/JavaScript file.
  3. Initialize the Detector: Create an instance of the object detector with your preferred model.
  4. Upload an Image: Provide an image input for the user to upload or capture.
  5. Detect Objects: Use the detector to analyze the image and retrieve detection results.
  6. Process Results: Handle the detected objects (e.g., display bounding boxes or labels).

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.

Can I use Transformers.js with any object detection model?
Yes, Transformers.js supports multiple pre-trained models. You can choose the one that best fits your application requirements.

How accurate is Transformers.js?
The accuracy depends on the underlying model used. Advanced models like YOLO or SSD provide high accuracy, but performance may vary based on image quality and complexity.

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