Image to Tags

This package uses TensorFlow.js and the pre-trained MobileNet model to recognize objects and scenes in an image and generate relevant keywords (tags).

Features

• Processes images from a local file path.
• Uses the popular and efficient MobileNet model.
• Written in TypeScript and includes type definitions.
• Provides an easy-to-use and flexible API.

Installation

You can add the package to your project using npm or yarn:

npm install image2tags

or

yarn add image2tags

Usage

After importing the package into your project, you can use the getImageTags function. This function takes the file path of an image as a parameter and returns a Promise. This Promise resolves with an array containing the tags and their probabilities.

import { getImageTags } from 'image2tags';
import * as path from 'path';

async function main() {
  try {
    const imagePath = path.join(__dirname, 'path/to/your/image.jpg');
    const tags = await getImageTags(imagePath);
    
    console.log('Detected Tags:');
    tags.forEach(tag => {
      console.log(`- ${tag.className} (Probability: ${(tag.probability * 100).toFixed(2)}%)`);
    });
  } catch (error) {
    console.error('An error occurred while getting tags:', error);
  }
}

main();

CLI Usage

You can also use this package as a command-line tool.

image2tags <path/to/your/image.jpg>

Options:

• -k, --topK <number>: Specify the number of top predictions to return (default: 10).
• --json: Output results in JSON format.

Example:

image2tags tests/fixtures/sample.jpg -k 5

Example with JSON output:

image2tags tests/fixtures/sample.jpg --json

Which will produce the following output:

[
  {
    "className": "brass, memorial tablet, plaque",
    "probability": 0.28563258051872253,
    "tags": [
      "brass",
      "memorial tablet",
      "plaque"
    ]
  },
  {
    "className": "envelope",
    "probability": 0.19800801575183868,
    "tags": [
      "envelope"
    ]
  }
]

Parameters

• imagePath (string, required): The file path of the image to be processed.
• topK (number, optional, default: 10): The number of top predictions to return.

Running Tests

To run the tests, clone the project, install the dependencies, and then run the test command:

git clone https://github.com/litepacks/image2tags.git
cd image2tags
npm install
npm test

Note: For the tests to run, there must be an image file named sample.jpg in the tests/fixtures folder.

Contributing

Contributions are always welcome! Please open an issue to discuss your proposed changes before submitting a pull request.

License

This project is licensed under the MIT License.