This project is a Node.js application that uses TensorFlow.js and NSFW.js for image classification. It's designed to detect and handle NSFW (Not Safe For Work) images uploaded to an S3 bucket.

These instructions will get you a copy of the project up and running on your local machine for development and testing purposes.

• Node.js
• npm

1. Clone the repository

git clone https://github.com/GalaxyBotTeam/NSFW-Classifier.git

2. Navigate to the project directory

cd your-project-directory

3. Install the dependencies

npm install

This project consists of two main components:

1. ImageClassificationHandler.js: This handles the image classification process. It fetches an image from an S3 bucket, converts it into a TensorFlow tensor, classifies the image using the NSFW.js model, and validates the classification results.

2. NSFW.js: This initializes the NSFW.js model and provides a method to get the model.

The application needs a configuration file to run. Create a config.json file in the root directory of the project with the following content: The content for the config.json is defined in the config-example.json file.

We use MinIO as an S3-compatible object storage server. You can use any S3-compatible object storage server by changing the s3 configuration in the config.json file.

Start the application by running the following command:

  npm start

The application provides a Webserver that listens for POST requests on the /api/v1/classifyImage endpoint. To classify an image, send a POST request to the /api/v1/classifyImage endpoint with the following payload:

{
  "key": "your-s3-key", //The key of the image in the S3 bucket. The bucket is defined in the config file
  "deleteOnClassification": false //Boolean, should the image automaticly deleted if nsfw has been detected?
  "metadata": {
    "userID": "userID", //Guild ID for Discord Log
    "guildID": "guildID" //User ID for Discord Log
  }
}

Returns a JSON object with the classification results. The result field indicates the classification result. The data field contains the classification probabilities for each category. In this example, the image is classified as porn with a probability of 0.8237768411636353.

{
  "nsfw": true,
  "deletedImage": false,
  "result": "porn",
  "data": {
    "porn": 0.8237768411636353,
    "sexy": 0.16640673577785492,
    "hentai": 0.006222452502697706,
    "neutral": 0.003563188249245286,
    "drawing": 0.00003067585203098133
  }
}

This project is licensed under the MIT License - see the LICENSE.md file for details.