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Object Detection
Transformers.js

Transformers.js

Upload images to detect objects

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Transformers.js

Detect objects in images using drag-and-drop

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What is Transformers.js ?

Transformers.js is a lightweight JavaScript library designed for object detection tasks. It allows developers to easily integrate image processing and object detection capabilities into web applications. The library leverages advanced AI models to upload images and detect objects within them, making it a powerful tool for applications requiring visual analysis.

Features

• Real-time Object Detection: Detect objects in images with high accuracy. • Browser Compatibility: Works seamlessly in modern web browsers. • Ease of Use: Simple API for integrating object detection into web apps. • Customizable: Modify detection settings to suit specific use cases. • Support for Multiple Objects: Detect and identify multiple objects in a single image.

How to use Transformers.js ?

  1. Include the Library: Add the Transformers.js script to your HTML file.
  2. Initialize the Detector: Create a new instance of the detector with optional configuration.
  3. Load the Image: Upload or specify the image you want to analyze.
  4. Run Detection: Call the detection method on the loaded image.
  5. Handle Results: Process the detected objects data (e.g., display bounding boxes or object labels).
// Example usage
const detector = new TransformersJS Detector();
const image = document.getElementById('image');
detector.detect(image)
  .then(results => {
    // Handle detected objects
    console.log(results);
  })
  .catch(error => {
    console.error('Error:', error);
  });

Frequently Asked Questions

What browsers are supported by Transformers.js?
Transformers.js is designed to work with modern browsers such as Chrome, Firefox, and Edge. Ensure your browser supports WebGL for optimal performance.

Can I customize the detection model?
Yes, Transformers.js allows you to adjust detection settings like confidence thresholds and model parameters to tailor detection accuracy for your needs.

How do I handle multiple object detections?
The library returns an array of detected objects. You can iterate over this array to access each object's details, such as labels and bounding box coordinates.

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