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Put a logo on an image
Transformers.js

Transformers.js

Upload an image to detect objects

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What is Transformers.js ?

Transformers.js is a JavaScript library designed to put a logo on an image and upload an image to detect objects using AI. It provides an easy-to-use interface for integrating image manipulation and object detection capabilities into web applications.

Features

• Logo Placement: Easily place logos on images with customizable positioning and styling options.
• Object Detection: Utilizes AI to detect objects within uploaded images, enabling advanced image processing.
• Real-Time Preview: Provides instant feedback for logo placement and object detection results.
• Cross-Browser Support: Compatible with modern browsers for seamless integration.
• Customizable: Offers flexible options for logo opacity, size, and placement.
• JavaScript API: Easy integration with existing web applications using a robust API.

How to use Transformers.js ?

  1. Include the Library: Add the Transformers.js script to your HTML file.

    <script src="transformers.js"></script>  
    
  2. Create an Instance: Initialize the Transformers.js class with your target image.

    const transformer = new Transformers(document.getElementById('image'));  
    
  3. Upload an Image: Use the library's API to upload an image for processing.

    transformer.uploadImage('path/to/image.jpg');  
    
  4. Detect Objects: Apply object detection to the uploaded image.

    transformer.detectObjects().then(results => {  
      console.log(results);  
    });  
    
  5. Add Logo: Place a logo on the image using the detected object positions or custom coordinates.

    transformer.addLogo('logo.png', { x: 100, y: 100 });  
    

Frequently Asked Questions

What formats are supported for images?
Transformers.js supports common image formats like JPEG, PNG, and GIF.

Can I customize the logo opacity?
Yes, the logo opacity can be adjusted using the setOpacity() method.

How do I handle large images?
For very large images, consider resizing them before processing to optimize performance.

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