Identify objects in your images using labels
Identify objects in images
Identify objects in real-time video feed
Detect objects in images and videos using YOLOv5
Identify objects in an image with bounding boxes
Identify objects in images with YOLOS model
Identify objects in images with Transformers.js
Identify the main objects in an image
Detect objects in anime images
Detect objects in images and highlight them
Detect objects in images or videos
Identify segments in an image using a Detectron2 model
Analyze images and videos to detect objects
Transformers.js is a powerful JavaScript library designed for object detection tasks. It allows developers to identify objects within images and classify them using predefined labels. Built with ease of use in mind, Transformers.js enables seamless integration of state-of-the-art object detection models into web applications. Whether you're working on a simple project or a complex AI-driven system, Transformers.js provides the tools necessary to accurately detect and label objects in real-time.
Start by installing the library using npm or yarn:
npm install transformers.js
Import the library into your JavaScript or TypeScript file:
const { ObjectDetector } = require('transformers.js');
Initialize the object detector with your preferred model:
const detector = new ObjectDetector({
model: 'yolov5s', // Choose from available models like yolov5s, RetinaNet, etc.
});
Load an image from a file or URL and pass it to the detector:
const image = new Image();
image.src = 'path/to/your/image.jpg';
image.onload = async () => {
const results = await detector.detect(image);
// Process the detection results
};
Handle the detection results to display bounding boxes and labels:
results.forEach(detection => {
console.log(`Detected ${detection.label} at position ${detection.position}`);
});
1. What models are supported by Transformers.js?
Transformers.js supports a variety of popular object detection models, including YOLOv5, Faster R-CNN, and RetinaNet. The library is continuously updated with the latest models for optimal performance.
2. Can I use Transformers.js in a production environment?
Yes! Transformers.js is designed to be production-ready. It is optimized for performance and provides highly accurate results, making it suitable for real-world applications.
3. How do I handle large images or high-resolution videos?
For large images or high-resolution videos, consider resizing the input to reduce computational overhead while maintaining satisfactory detection accuracy. This can be done using canvas manipulation or dedicated image processing libraries.