Ready-to-Use NSFW Detection API

This repository contains a simple Flask API for detecting NSFW images using this NSFW detection model.

👩🏼‍💻 Developer setup

Linked is our guide for setting up all Vrooli repos. No extra steps are required.

Minimum requirements for Virtual Private Server (VPS)

• Memory: 2GB
• CPUs: 1

Usage

Send a POST request to http://localhost:<PORT_NSFW> if testing locally, or https://<your-domain> if testing on a Virtual Private Server (VPS). The request must contain the following structure:

{
    "key": "<your-api-key>", // Only if API_KEY environment variable is set
    "images": [{
        "buffer": "<base64-encoded-image>",
        "hash": "<unique-hash-for-image>" // If provided, used to prevent computing for the image if it is passed again
    }]
}

As a curl request, it looks like this:

curl -X POST \
     -H "Content-Type: application/json" \
     -H "key: <your_api_key>" \
     -d '{"images": [{"buffer": "<base64-encoded-image>", "hash": "<unique-hash-for-image>"}]}' \
     http://localhost:<PORT_NSFW>

If you are authenticated, it will return an object of this shape:

{
    "predictions": [
        "<unique-hash-for-image>": {
            "drawings": 0.12345678,
            "hentai": 2.12121212,
            "neutral": 69.42000000,
            "porn": 1.88888888,
            "sexy": 8.76543210,
        }
    ]
}

Updating the model

The model is taken from the NSFW detection model's release page. All you need to do is:

1. Download the mobilenet*.zip from the latest release
2. Unzip it
3. Copy the .h5 for the model (not the weights!) to this repo's models folder

Contributions

Contributions are always welcome! If you have suggestions for improvements, please create an issue or a pull request💖