image-labeling1

The image-labeling1 MCP server offers an efficient and powerful solution for adding semantic labels to your images. This server leverages state-of-the-art, pre-trained deep learning models to classify thousands of unique labels across a wide variety of categories. Designed for seamless integration, this service allows developers to incorporate advanced machine learning capabilities into their applications with ease.

Features

• Semantic Image Labeling: Automatically assign semantic labels to images. This functionality is particularly useful for categorizing and organizing image data in applications that require detailed image analysis.
• Affordable and Scalable: The server is designed to efficiently serve requests at scale, enabling cost-effective deployment of machine learning models. This ensures that users can benefit from high-quality image labeling without incurring excessive costs.
• Easy Integration: Simply provide an image URL, and the server will handle the processing and return a list of probable labels along with their confidence scores. This straightforward approach ensures minimal integration effort and quick deployment.

MCP Tools

• image_labeling: Utilize the image labeling tool to add semantic labels to your images. This tool processes the given image URL and returns a set of labels, each associated with a confidence score indicating the likelihood of the image belonging to that category.

Usage with Different Platforms

python

python
import requests

url = 'http://image-labeling1-server/api/label'
image_url = 'http://example.com/image.jpg'
response = requests.post(url, json={'image_url': image_url})
labels = response.json()
print(labels)

nodejs

javascript
const axios = require('axios');

const url = 'http://image-labeling1-server/api/label';
const imageUrl = 'http://example.com/image.jpg';

axios.post(url, { image_url: imageUrl })
  .then(response => {
    console.log(response.data);
  })
  .catch(error => {
    console.error(error);
  });