Documentation

Everything you need to integrate Sightengine's APIs. From quick starts to advanced use cases.

🛡️

Moderate

Automatically detect and filter harmful content across images, videos, text, and audio.

Image Video Text Audio
✓

AI Content Detection

Detect AI-generated content, deepfakes, and synthetic media to ensure authenticity.

AI Images AI Video Deepfakes AI Music
🧑

People & Identity

Analyze faces, people, liveness.

Faces Age Liveness
🔍

Visual Search

Find similar and duplicate content across your image and video libraries with custom search.

Image Search Video Search
📊

Image Analysis & OCR

Analyze faces, extract text, measure quality, and classify image types for better insights.

OCR QR codes Quality Type

Quick Start

Get up and running with Sightengine in minutes. Here's what you need to know:

Need API keys? Create a free account.

1. Choose your models

Select the detection models you need. You can combine multiple models in a single API call for efficiency.

2. Make your first API call

Send an image or video URL to analyze. The API returns a JSON response with detection results.


curl -X POST 'https://api.sightengine.com/1.0/check.json' \
    -F 'media=@/path/to/image.jpg' \
    -F 'models=nudity-2.1,gore-2.0' \
    -F 'api_user={api_user}' \
    -F 'api_secret={api_secret}'



# this example uses requests
import requests
import json

params = {
  'models': 'nudity-2.1,gore-2.0',
  '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' => 'nudity-2.1,gore-2.0',
  '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', 'nudity-2.1,gore-2.0');
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);
});

3. Handle the response

Parse the JSON response and take action based on the confidence scores returned for each model.