Models / AI-Generated Image Detection

AI-Generated Image Detection

Overview

The AI-Generated Image Detection Model can help you determine if an image was entirely generated by an AI model, or if it is a real image. This model was trained on millions of artificially-created and human-created images spanning all sorts of content such as photography, art, drawings, memes and more.

The Model works by analyzing the visual (pixel) content of the image. No meta-data is used in the analysis. Tampering with meta-data such as EXIF data therefore has no effect on the scoring.

The Model was trained to detect images generated by the main models currently in use: Stable Diffusion, Stable Diffusion XL, MidJourney, Dall-E, Adobe Firefly, GANs... Additional models will be added over time as they become available.

Use cases

Tag AI-generated imagery as such, to limit the spread of misinformation and fake news
Implement stricter moderation rules on AI-generated imagery
Detect potential fraud with fake ids, fake profiles or fake claims
Limit ai-generated spam
Enact bans on AI-generated imagery

Related model

The following 2 models can provide a useful complement to the AI-generated detection model:

Deepfake Detection: Detect swapped or modified faces.
Type Detection: Detect if an image is a photography or an illustration.

Examples

AI-generated images

Stable Diffusion

MidJourney 6.1

Firefly 3

DALL-E 3

Ideogram v2

Flux 1.1

StyleGan2 (thispersondoesnotexist)

Use the model

If you haven't already, create an account to get your own API keys.

Detect if an image was AI-generated

Let's say you want to check the following image:

You can either send the image URL, or upload the raw binary image.

Option 1: Send image URL

Here's how to proceed if you choose to share the image URL:


curl -X GET -G 'https://api.sightengine.com/1.0/check.json' \
    -d 'models=genai' \
    -d 'api_user={api_user}&api_secret={api_secret}' \
    --data-urlencode 'url=https://sightengine.com/assets/img/examples/example-prop-c1.jpg'


# this example uses requests
import requests
import json

params = {
  'url': 'https://sightengine.com/assets/img/examples/example-prop-c1.jpg',
  'models': 'genai',
  'api_user': '{api_user}',
  'api_secret': '{api_secret}'
}
r = requests.get('https://api.sightengine.com/1.0/check.json', params=params)

output = json.loads(r.text)


$params = array(
  'url' =>  'https://sightengine.com/assets/img/examples/example-prop-c1.jpg',
  'models' => 'genai',
  'api_user' => '{api_user}',
  'api_secret' => '{api_secret}',
);

// this example uses cURL
$ch = curl_init('https://api.sightengine.com/1.0/check.json?'.http_build_query($params));
curl_setopt($ch, CURLOPT_RETURNTRANSFER, true);
$response = curl_exec($ch);
curl_close($ch);

$output = json_decode($response, true);


// this example uses axios
const axios = require('axios');

axios.get('https://api.sightengine.com/1.0/check.json', {
  params: {
    'url': 'https://sightengine.com/assets/img/examples/example-prop-c1.jpg',
    'models': 'genai',
    'api_user': '{api_user}',
    'api_secret': '{api_secret}',
  }
})
.then(function (response) {
  // on success: handle response
  console.log(response.data);
})
.catch(function (error) {
  // handle error
  if (error.response) console.log(error.response.data);
  else console.log(error.message);
});

See request parameter description

Parameter	Type	Description
url	string	URL of the image to analyze
models	string	comma-separated list of models to apply
api_user	string	your API user id
api_secret	string	your API secret

Option 2: Send raw image

Here's how to proceed if you choose to upload the raw image:


curl -X POST 'https://api.sightengine.com/1.0/check.json' \
    -F 'media=@/path/to/image.jpg' \
    -F 'models=genai' \
    -F 'api_user={api_user}' \
    -F 'api_secret={api_secret}'


# this example uses requests
import requests
import json

params = {
  'models': 'genai',
  'api_user': '{api_user}',
  'api_secret': '{api_secret}'
}
files = {'media': open('/path/to/image.jpg', 'rb')}
r = requests.post('https://api.sightengine.com/1.0/check.json', files=files, data=params)

output = json.loads(r.text)


$params = array(
  'media' => new CurlFile('/path/to/image.jpg'),
  'models' => 'genai',
  'api_user' => '{api_user}',
  'api_secret' => '{api_secret}',
);

// this example uses cURL
$ch = curl_init('https://api.sightengine.com/1.0/check.json');
curl_setopt($ch, CURLOPT_POST, true);
curl_setopt($ch, CURLOPT_RETURNTRANSFER, true);
curl_setopt($ch, CURLOPT_POSTFIELDS, $params);
$response = curl_exec($ch);
curl_close($ch);

$output = json_decode($response, true);


// this example uses axios and form-data
const axios = require('axios');
const FormData = require('form-data');
const fs = require('fs');

data = new FormData();
data.append('media', fs.createReadStream('/path/to/image.jpg'));
data.append('models', 'genai');
data.append('api_user', '{api_user}');
data.append('api_secret', '{api_secret}');

axios({
  method: 'post',
  url:'https://api.sightengine.com/1.0/check.json',
  data: data,
  headers: data.getHeaders()
})
.then(function (response) {
  // on success: handle response
  console.log(response.data);
})
.catch(function (error) {
  // handle error
  if (error.response) console.log(error.response.data);
  else console.log(error.message);
});

See request parameter description

Parameter	Type	Description
media	binary	image to analyze
models	string	comma-separated list of models to apply
api_user	string	your API user id
api_secret	string	your API secret

Response

The API will then return a JSON response with the ai_generated score. This score is a float between 0 and 1. The higher the value, the higher the confidence that the image is AI-generated:

                
                
{
    "status": "success",
    "request": {
        "id": "req_0zrbHDeitGYY7wEGncAne",
        "timestamp": 1491402308.4762,
        "operations": 1
    },
    "type": {
      "ai_generated": 0.01
    },
    "media": {
        "id": "med_0zrbk8nlp4vwI5WxIqQ4u",
        "uri": "https://sightengine.com/assets/img/examples/example-prop-c2.jpg"
    }
}

Any other needs?

See our full list of Image/Video models for details on other filters and checks you can run on your images and videos. You might also want to check our Text models to moderate text-based content: messages, reviews, comments, usernames...

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