curl --request POST \
  --url https://api.spoofsense.ai/v1/liveness_detection \
  --header 'Authorization: Bearer <token>' \
  --header 'Content-Type: application/json' \
  --data '
{
  "data": "<string>",
  "image_url": "<string>",
  "threshold": 0.5,
  "thresholds": {},
  "min_face_check": true
}
'

import requests

url = "https://api.spoofsense.ai/v1/liveness_detection"

payload = {
    "data": "<string>",
    "image_url": "<string>",
    "threshold": 0.5,
    "thresholds": {},
    "min_face_check": True
}
headers = {
    "Authorization": "Bearer <token>",
    "Content-Type": "application/json"
}

response = requests.post(url, json=payload, headers=headers)

print(response.text)

const options = {
  method: 'POST',
  headers: {Authorization: 'Bearer <token>', 'Content-Type': 'application/json'},
  body: JSON.stringify({
    data: '<string>',
    image_url: '<string>',
    threshold: 0.5,
    thresholds: {},
    min_face_check: true
  })
};

fetch('https://api.spoofsense.ai/v1/liveness_detection', options)
  .then(res => res.json())
  .then(res => console.log(res))
  .catch(err => console.error(err));

<?php

$curl = curl_init();

curl_setopt_array($curl, [
  CURLOPT_URL => "https://api.spoofsense.ai/v1/liveness_detection",
  CURLOPT_RETURNTRANSFER => true,
  CURLOPT_ENCODING => "",
  CURLOPT_MAXREDIRS => 10,
  CURLOPT_TIMEOUT => 30,
  CURLOPT_HTTP_VERSION => CURL_HTTP_VERSION_1_1,
  CURLOPT_CUSTOMREQUEST => "POST",
  CURLOPT_POSTFIELDS => json_encode([
    'data' => '<string>',
    'image_url' => '<string>',
    'threshold' => 0.5,
    'thresholds' => [
        
    ],
    'min_face_check' => true
  ]),
  CURLOPT_HTTPHEADER => [
    "Authorization: Bearer <token>",
    "Content-Type: application/json"
  ],
]);

$response = curl_exec($curl);
$err = curl_error($curl);

curl_close($curl);

if ($err) {
  echo "cURL Error #:" . $err;
} else {
  echo $response;
}

package main

import (
	"fmt"
	"strings"
	"net/http"
	"io"
)

func main() {

	url := "https://api.spoofsense.ai/v1/liveness_detection"

	payload := strings.NewReader("{\n  \"data\": \"<string>\",\n  \"image_url\": \"<string>\",\n  \"threshold\": 0.5,\n  \"thresholds\": {},\n  \"min_face_check\": true\n}")

	req, _ := http.NewRequest("POST", url, payload)

	req.Header.Add("Authorization", "Bearer <token>")
	req.Header.Add("Content-Type", "application/json")

	res, _ := http.DefaultClient.Do(req)

	defer res.Body.Close()
	body, _ := io.ReadAll(res.Body)

	fmt.Println(string(body))

}

HttpResponse<String> response = Unirest.post("https://api.spoofsense.ai/v1/liveness_detection")
  .header("Authorization", "Bearer <token>")
  .header("Content-Type", "application/json")
  .body("{\n  \"data\": \"<string>\",\n  \"image_url\": \"<string>\",\n  \"threshold\": 0.5,\n  \"thresholds\": {},\n  \"min_face_check\": true\n}")
  .asString();

require 'uri'
require 'net/http'

url = URI("https://api.spoofsense.ai/v1/liveness_detection")

http = Net::HTTP.new(url.host, url.port)
http.use_ssl = true

request = Net::HTTP::Post.new(url)
request["Authorization"] = 'Bearer <token>'
request["Content-Type"] = 'application/json'
request.body = "{\n  \"data\": \"<string>\",\n  \"image_url\": \"<string>\",\n  \"threshold\": 0.5,\n  \"thresholds\": {},\n  \"min_face_check\": true\n}"

response = http.request(request)
puts response.read_body

{
  "product": "face_liveness",
  "decision": "real",
  "genuine_score": 0.9333,
  "threshold": 0.5,
  "spoof_type": null,
  "latency_ms": 190,
  "credits_remaining": 1240,
  "session_id": "d2f8c1e4a90b4f0f8f1f2a3b4c5d6e7f",
  "request_id": "9b1c2d3e4f5a6b7c8d9e0f1a2b3c4d5e"
}

{
  "error": {
    "code": "BAD_REQUEST",
    "message": "Provide 'data' (base64) or 'image_url'"
  }
}

{
  "error": {
    "code": "UNAUTHORIZED",
    "message": "Missing, invalid, or revoked API key"
  }
}

{
  "error": {
    "code": "INSUFFICIENT_CREDITS",
    "message": "Insufficient credits"
  }
}

{
  "error": {
    "code": "IMAGE_TOO_LARGE",
    "message": "Image too large (max 10 MB)"
  }
}

{
  "error": {
    "code": "FACE_NOT_DETECTED",
    "message": "No face found in the image"
  }
}

{
  "error": {
    "code": "UPSTREAM_ERROR",
    "message": "Inference service unavailable"
  }
}