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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 using a web app

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What is Transformers.js ?

Transformers.js is a powerful JavaScript library designed for object detection tasks. It allows users to upload an image and detect objects within it using AI models. Built for browser-based environments, Transformers.js provides a lightweight and efficient solution for object detection without requiring extensive setup or dependencies.

Features

• Real-time Object Detection: Detect objects in images efficiently with minimal latency. • Multiple Model Support: Choose from various pre-trained models to suit your accuracy and performance needs. • Browser Compatibility: Works seamlessly across modern web browsers. • Easy Integration: Simple API for integrating into web applications. • Customizable Detection: Adjust detection parameters such as confidence thresholds and model architecture. • Lightweight Design: Optimized for performance without compromising on accuracy.

How to use Transformers.js ?

  1. Include the Library: Add the Transformers.js script to your HTML file.
  2. Initialize the Detector: Create an instance of the detector with your preferred model.
  3. Load an Image: Upload or provide an image for detection.
  4. Run Detection: Call the detect method to analyze the image and receive results.
  5. Process Results: Access detected objects and their properties (e.g., bounding boxes, labels, confidence scores).

Frequently Asked Questions

What browsers are supported by Transformers.js?
Transformers.js is optimized for modern browsers, including Chrome, Firefox, Safari, and Edge. It leverages browser-native technologies for optimal performance.

How accurate is Transformers.js for object detection?
Accuracy depends on the model used. Transformers.js supports popular models known for high accuracy in object detection tasks, such as YOLO and SSD MobileNet.

Can I use Transformers.js for large images?
Yes, but performance may vary. For best results, resize images to a reasonable resolution before performing detection to optimize speed and memory usage.

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