Face DetectorFace Detector API

OnlineCredit Usage:5 per callRefreshed 1 month ago
avg: 1487ms|p50: 1353ms|p75: 1576ms|p90: 1844ms|p99: 2379ms

Face Detector API analyzes images to detect human faces and returns bounding box coordinates for each detected face.

The Face Detector API provides reliable and fast access to face detector data through a simple REST interface. Built for developers who need consistent, high-quality results with minimal setup time.

To use Face Detector, you need an API key. You can get one by creating a free account and visiting your dashboard.

POST Endpoint

URL
https://api.apiverve.com/v1/facedetect

Code Examples

Here are examples of how to call the Face Detector API in different programming languages:

cURL Request
curl -X POST \
  "https://api.apiverve.com/v1/facedetect" \
  -H "X-API-Key: your_api_key_here" \
  -H "Content-Type: application/json" \
  -d '{
  "url": "https://example.com/group-photo.jpg",
  "confidence": 0.5
}'
JavaScript (Fetch API)
const response = await fetch('https://api.apiverve.com/v1/facedetect', {
  method: 'POST',
  headers: {
    'X-API-Key': 'your_api_key_here',
    'Content-Type': 'application/json'
  },
  body: JSON.stringify({
    "url": "https://example.com/group-photo.jpg",
    "confidence": 0.5
})
});

const data = await response.json();
console.log(data);
Python (Requests)
import requests

headers = {
    'X-API-Key': 'your_api_key_here',
    'Content-Type': 'application/json'
}

payload = {
    "url": "https://example.com/group-photo.jpg",
    "confidence": 0.5
}

response = requests.post('https://api.apiverve.com/v1/facedetect', headers=headers, json=payload)

data = response.json()
print(data)
Node.js (Native HTTPS)
const https = require('https');
const url = require('url');

const options = {
  method: 'POST',
  headers: {
    'X-API-Key': 'your_api_key_here',
    'Content-Type': 'application/json'
  }
};

const postData = JSON.stringify({
  "url": "https://example.com/group-photo.jpg",
  "confidence": 0.5
});

const req = https.request('https://api.apiverve.com/v1/facedetect', options, (res) => {
  let data = '';
  res.on('data', (chunk) => data += chunk);
  res.on('end', () => console.log(JSON.parse(data)));
});

req.write(postData);
req.end();
PHP (cURL)
<?php

$ch = curl_init();

curl_setopt($ch, CURLOPT_URL, 'https://api.apiverve.com/v1/facedetect');
curl_setopt($ch, CURLOPT_RETURNTRANSFER, true);
curl_setopt($ch, CURLOPT_CUSTOMREQUEST, 'POST');
curl_setopt($ch, CURLOPT_HTTPHEADER, [
    'X-API-Key: your_api_key_here',
    'Content-Type: application/json'
]);

curl_setopt($ch, CURLOPT_POSTFIELDS, json_encode({
    'url': 'https://example.com/group-photo.jpg',
    'confidence': 0.5
}));

$response = curl_exec($ch);
curl_close($ch);

$data = json_decode($response, true);
print_r($data);

?>
Go (net/http)
package main

import (
    "fmt"
    "io"
    "net/http"
    "bytes"
    "encoding/json"
)

func main() {
    payload := map[string]interface{}{
        "url": "https://example.com/group-photo.jpg",
        "confidence": "0.5"
    }

    jsonPayload, _ := json.Marshal(payload)
    req, _ := http.NewRequest("POST", "https://api.apiverve.com/v1/facedetect", bytes.NewBuffer(jsonPayload))

    req.Header.Set("X-API-Key", "your_api_key_here")
    req.Header.Set("Content-Type", "application/json")

    client := &http.Client{}
    resp, err := client.Do(req)
    if err != nil {
        panic(err)
    }
    defer resp.Body.Close()

    body, _ := io.ReadAll(resp.Body)
    fmt.Println(string(body))
}
Ruby (Net::HTTP)
require 'net/http'
require 'json'

uri = URI('https://api.apiverve.com/v1/facedetect')
http = Net::HTTP.new(uri.host, uri.port)
http.use_ssl = true

payload = {
  "url": "https://example.com/group-photo.jpg",
  "confidence": 0.5
}

request = Net::HTTP::Post.new(uri)
request['X-API-Key'] = 'your_api_key_here'
request['Content-Type'] = 'application/json'

request.body = payload.to_json

response = http.request(request)
puts JSON.pretty_generate(JSON.parse(response.body))
C# (HttpClient)
using System;
using System.Net.Http;
using System.Text;
using System.Threading.Tasks;

class Program
{
    static async Task Main(string[] args)
    {
        using var client = new HttpClient();
        client.DefaultRequestHeaders.Add("X-API-Key", "your_api_key_here");

        var jsonContent = @"{
        ""url"": ""https://example.com/group-photo.jpg"",
        ""confidence"": 0.5
}";
        var content = new StringContent(jsonContent, Encoding.UTF8, "application/json");

        var response = await client.PostAsync("https://api.apiverve.com/v1/facedetect", content);
        response.EnsureSuccessStatusCode();

        var responseBody = await response.Content.ReadAsStringAsync();
        Console.WriteLine(responseBody);
    }
}

Authentication

The Face Detector API requires authentication via API key. Include your API key in the request header:

Required Header
X-API-Key: your_api_key_here

Learn more about authentication →

Interactive API Playground

Test the Face Detector API directly in your browser with live requests and responses.

Parameters

The Face Detector API supports multiple query options. Use one of the following:

Option 1: Detect Faces from Upload

ParameterTypeRequiredDescriptionDefaultExample
imagestringrequired
Image file upload (JPG, PNG, GIF, WebP supported, max 10MB)
--
confidencenumberoptional
Minimum confidence threshold for face detection (0.1 to 1.0)
Range: 0.1 - 1
0.50.5

Option 2: Detect Faces from URL

ParameterTypeRequiredDescriptionDefaultExample
urlstringrequired
URL of the image to analyze (JPG, PNG, GIF, WebP supported)
-https://example.com/group-photo.jpg
confidencenumberoptional
Minimum confidence threshold for face detection (0.1 to 1.0)
Range: 0.1 - 1
0.50.5

Response

The Face Detector API returns responses in JSON, XML, YAML, and CSV formats:

Example Responses

JSON Response
200 OK
{
  "status": "ok",
  "error": null,
  "data": {
    "faces": [
      {
        "x": 142,
        "y": 85,
        "width": 98,
        "height": 112,
        "confidence": 0.9847
      },
      {
        "x": 312,
        "y": 92,
        "width": 87,
        "height": 103,
        "confidence": 0.9623
      },
      {
        "x": 478,
        "y": 78,
        "width": 95,
        "height": 118,
        "confidence": 0.9412
      }
    ],
    "faceCount": 3,
    "hasFaces": true,
    "imageWidth": 640,
    "imageHeight": 480,
    "averageConfidence": 0.9627,
    "imageCoverage": 10.23
  },
  "code": 200
}
XML Response
200 OK
<?xml version="1.0" encoding="UTF-8"?>
<response>
  <status>ok</status>
  <error xsi:nil="true" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"/>
  <data>
    <faces>
      <face>
        <x>142</x>
        <y>85</y>
        <width>98</width>
        <height>112</height>
        <confidence>0.9847</confidence>
      </face>
      <face>
        <x>312</x>
        <y>92</y>
        <width>87</width>
        <height>103</height>
        <confidence>0.9623</confidence>
      </face>
      <face>
        <x>478</x>
        <y>78</y>
        <width>95</width>
        <height>118</height>
        <confidence>0.9412</confidence>
      </face>
    </faces>
    <faceCount>3</faceCount>
    <hasFaces>true</hasFaces>
    <imageWidth>640</imageWidth>
    <imageHeight>480</imageHeight>
    <averageConfidence>0.9627</averageConfidence>
    <imageCoverage>10.23</imageCoverage>
  </data>
  <code>200</code>
</response>
YAML Response
200 OK
status: ok
error: null
data:
  faces:
    - x: 142
      'y': 85
      width: 98
      height: 112
      confidence: 0.9847
    - x: 312
      'y': 92
      width: 87
      height: 103
      confidence: 0.9623
    - x: 478
      'y': 78
      width: 95
      height: 118
      confidence: 0.9412
  faceCount: 3
  hasFaces: true
  imageWidth: 640
  imageHeight: 480
  averageConfidence: 0.9627
  imageCoverage: 10.23
code: 200
CSV Response
200 OK
keyvalue
faces[{x:142,y:85,width:98,height:112,confidence:0.9847},{x:312,y:92,width:87,height:103,confidence:0.9623},{x:478,y:78,width:95,height:118,confidence:0.9412}]
faceCount3
hasFacestrue
imageWidth640
imageHeight480
averageConfidence0.9627
imageCoverage10.23

Response Structure

All API responses follow a consistent structure with the following fields:

FieldTypeDescriptionExample
statusstringIndicates whether the request was successful ("ok") or failed ("error")ok
errorstring | nullContains error message if status is "error", otherwise nullnull
dataobject | nullContains the API response data if successful, otherwise null{...}

Learn more about response formats →

Response Data Fields

When the request is successful, the data object contains the following fields:

Response fields marked with Premium are available exclusively on paid plans.View pricing
FieldTypeSample ValueDescription
[ ] Array items:array[3]Array of objectsArray of detected faces with bounding boxes and confidence scores
â”” xnumber142X coordinate of face bounding box top-left corner
â”” ynumber85Y coordinate of face bounding box top-left corner
â”” widthnumber98Width of face bounding box in pixels
â”” heightnumber112Height of face bounding box in pixels
â”” confidencenumber0.9847Confidence score for face detection (0.0 to 1.0)
faceCountPremiumnumber3Total number of faces detected in the image
hasFacesbooleantrueWhether any faces were detected in the image
imageWidthPremiumnumber640Width of the analyzed image in pixels
imageHeightPremiumnumber480Height of the analyzed image in pixels
averageConfidencePremiumnumber0.9627Average confidence score across all detected faces
imageCoveragePremiumnumber10.23Percentage of image area covered by detected faces

Headers

Required and optional headers for Face Detector API requests:

Header NameRequiredExample ValueDescription
X-API-Keyrequiredyour_api_key_hereYour APIVerve API key. Found in your dashboard under API Keys.
Acceptoptionalapplication/jsonSpecify response format: application/json (default), application/xml, or application/yaml
User-AgentoptionalMyApp/1.0Identifies your application for analytics and debugging purposes
X-Request-IDoptionalreq_123456789Custom request identifier for tracking and debugging requests
Cache-Controloptionalno-cacheControl caching behavior for the request and response

Learn more about request headers →

GraphQL AccessALPHA

Access Face Detector through GraphQL to combine it with other API calls in a single request. Query only the face detector data you need with precise field selection, and orchestrate complex data fetching workflows.

Test Face Detector in the GraphQL Explorer to confirm availability and experiment with queries.

Credit Cost: Each API called in your GraphQL query consumes its standard credit cost.

GraphQL Endpoint
POST https://api.apiverve.com/v1/graphql
GraphQL Query Example
query {
  facedetect(
    input: {
      url: "https://example.com/group-photo.jpg"
      confidence: 0.5
    }
  ) {
    faces
    faceCount
    hasFaces
    imageWidth
    imageHeight
    averageConfidence
    imageCoverage
  }
}

Note: Authentication is handled via the x-api-key header in your GraphQL request, not as a query parameter.

CORS Support

The Face Detector API supports Cross-Origin Resource Sharing (CORS) with wildcard configuration, allowing you to call Face Detector directly from browser-based applications without proxy servers.

CORS HeaderValueDescription
Access-Control-Allow-Origin*Accepts requests from any origin
Access-Control-Allow-Methods*Accepts any HTTP method
Access-Control-Allow-Headers*Accepts any request headers

Browser Usage: You can call Face Detector directly from JavaScript running in the browser without encountering CORS errors. No proxy server or additional configuration needed.

Learn more about CORS support →

Rate Limiting

Face Detector API requests are subject to rate limiting based on your subscription plan. These limits ensure fair usage and maintain service quality for all Face Detector users.

PlanRate LimitDescription
Free5 requests/minHard rate limit enforced - exceeding will return 429 errors
StarterNo LimitProduction ready - standard traffic priority
ProNo LimitProduction ready - preferred traffic priority
MegaNo LimitProduction ready - highest traffic priority

Learn more about rate limiting →

Rate Limit Headers

When rate limits apply, each Face Detector response includes headers to help you track your usage:

HeaderDescription
X-RateLimit-LimitMaximum number of requests allowed per time window
X-RateLimit-RemainingNumber of requests remaining in the current window
X-RateLimit-ResetUnix timestamp when the rate limit window resets

Handling Rate Limits

Free Plan: When you exceed your rate limit, Face Detector returns a 429 Too Many Requests status code. Your application should implement appropriate backoff logic to handle this gracefully.

Paid Plans: No rate limiting or throttling applied. All paid plans (Starter, Pro, Mega) are production-ready.

Best Practices for Face Detector:

  • Monitor the rate limit headers to track your Face Detector usage (Free plan only)
  • Cache face detector responses where appropriate to reduce API calls
  • Upgrade to Pro or Mega for guaranteed no-throttle Face Detector performance

Note: Face Detector rate limits are separate from credit consumption. You may have credits remaining but still hit rate limits when using Face Detector on Free tier.

Error Codes

The Face Detector API uses standard HTTP status codes to indicate success or failure:

CodeMessageDescriptionSolution
200OKRequest successful, data returnedNo action needed - request was successful
400Bad RequestInvalid request parameters or malformed requestCheck required parameters and ensure values match expected formats
401UnauthorizedMissing or invalid API keyInclude x-api-key header with valid API key from dashboard
403ForbiddenAPI key lacks permission or insufficient creditsCheck credit balance in dashboard or upgrade plan
429Too Many RequestsRate limit exceeded (Free: 5 req/min)Implement request throttling or upgrade to paid plan
500Internal Server ErrorServer error occurredRetry request after a few seconds, contact support if persists
503Service UnavailableAPI temporarily unavailableWait and retry, check status page for maintenance updates

Learn more about error handling →

Need help? Contact support with your X-Request-ID for assistance.

Integrate Face Detector with SDKs

Get started quickly with official Face Detector SDKs for your preferred language. Each library handles authentication, request formatting, and error handling automatically.

Available for Node.js, Python, C#/.NET, and Android/Java. All SDKs are open source and regularly updated.

Integrate Face Detector with No-Code API Tools

Connect the Face Detector API to your favorite automation platform without writing code. Build workflows that leverage face detector data across thousands of apps.

All platforms use your same API key to access Face Detector. Visit our integrations hub for step-by-step setup guides.

Frequently Asked Questions

How do I get an API key for Face Detector?
Sign up for a free account at dashboard.apiverve.com. Your API key will be automatically generated and available in your dashboard. The same key works for Face Detector and all other APIVerve APIs. The free plan includes 1,000 credits plus a 500 credit bonus.
How many credits does Face Detector cost?

Each successful Face Detector API call consumes credits based on plan tier. Check the pricing section above for the exact credit cost. Failed requests and errors don't consume credits, so you only pay for successful face detector lookups.

Can I use Face Detector in production?

The free plan is for testing and development only. For production use of Face Detector, upgrade to a paid plan (Starter, Pro, or Mega) which includes commercial use rights, no attribution requirements, and guaranteed uptime SLAs. All paid plans are production-ready.

Can I use Face Detector from a browser?
Yes! The Face Detector API supports CORS with wildcard configuration, so you can call it directly from browser-based JavaScript without needing a proxy server. See the CORS section above for details.
What happens if I exceed my Face Detector credit limit?

When you reach your monthly credit limit, Face Detector API requests will return an error until you upgrade your plan or wait for the next billing cycle. You'll receive notifications at 80% and 95% usage to give you time to upgrade if needed.

What's Next?

Continue your journey with these recommended resources

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