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Object Detection
Transformers.js

Transformers.js

Detect objects in your images

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What is Transformers.js ?

Transformers.js is a lightweight JavaScript library designed for object detection in images. It allows developers to easily integrate Transformer-based models into web applications, enabling real-time detection and analysis of objects within images. The library simplifies the process of loading pre-trained models, processing images, and interpreting results.

Features

• Pre-trained Model Support: Easily load popular Transformer models optimized for object detection.
• Real-time Processing: Efficiently process images and detect objects in real-time.
• Customizable Thresholds: Adjust detection thresholds to filter results based on confidence levels.
• Cross-platform Compatibility: Works seamlessly across modern web browsers.
• Minimal Dependencies: Lightweight and easy to integrate into existing web applications.

How to use Transformers.js ?

  1. Install the Library: Use npm to install the package:
    npm install transformers.js
  2. Import the Library: Include Transformers.js in your JavaScript file:
    const { Transformers } = require('transformers.js');
  3. Load a Pre-trained Model: Initialize the model for object detection:
    const model = new Transformers('object-detection');
  4. Process an Image: Pass an image element or URL to the model:
    const results = await model.detect(imageElement);
  5. Handle Results: Access detected objects and their bounding boxes from the results:
    console.log(results); // Array of objects with confidence scores and coordinates

Frequently Asked Questions

What browsers are supported by Transformers.js?
Transformers.js is designed to work with modern web browsers, including Chrome, Firefox, Safari, and Edge.

Can I use custom models with Transformers.js?
Yes, Transformers.js allows you to load custom Transformer models for specific use cases beyond pre-trained models.

How do I improve detection accuracy?
You can improve accuracy by adjusting the detection threshold or using more advanced models. Lowering the threshold may increase detection sensitivity.

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