👤 Face Recognition

👤 ระบบจดจำใบหน้า

Welcome to Face Recognition API, an AI product developed by iApp Technology Co., Ltd. Our API is designed to recognize faces in images with high accuracy and speed. The API supports both single and multiple face recognition with flexible scoring options.

Try Demo

Visit our API Portal to test the Face Recognition API with your own images.

Getting Started

Prerequisites
- An API key from iApp Technology
- Image files containing faces
- Supported formats: JPEG, JPG, PNG
- Maximum file size: 2MB
Quick Start
- Fast processing time
- High accuracy face recognition
- Support for multiple file formats
- Flexible scoring options
Key Features
- Single and multiple face recognition
- Face bounding box coordinates
- Recognition confidence scores
- Face image extraction
- Company-specific scoring options
Security & Compliance
- GDPR and PDPA compliant
- No data retention after processing

How to get API Key?

Please visit API Portal to view your existing API key or request a new one.

Example

Face Recognition Request:

Image Preview

Face Detection Example

  curl  --location 'https://api.iapp.co.th/face_recog_single' \
        --header 'apikey: {YOUR API KEY}' \
        --form 'file=@"{YOUR UPLOADED FILE}"' \
        --form 'company="{YOUR COMPANY NAME}"'

Face Recognition Response:

{
    "bbox": {
        "xmax": 255.44717407226562,
        "xmin": 154.39295959472656,
        "ymax": 282.8843688964844,
        "ymin": 155.49319458007812
    },
    "company": "{YOUR COMPANY NAME}",
    "detection_score": 0.9998624324798584,
    "message": "successfully performed",
    "name": "unknown",
    "process_time": 0.4776473045349121,
    "recognition_score": 0.0
}

Features & Capabilities

Core Features

Single and multiple face recognition in images
Face detection with bounding box coordinates
Face feature extraction and matching
Customizable detection and recognition score thresholds
Face database management (add/remove faces)
Export/import of face features

Supported Fields

Face bounding box coordinates (xmin, xmax, ymin, ymax)
Detection confidence score
Recognition confidence score
Person name identification
Processing time

API Reference

Face Recognition Endpoints

Single Face Recognition (/face_recog_single)
- Recognizes the most prominent face in an image
- Returns face position and identity
Multiple Face Recognition (/face_recog_multi)
- Recognizes all faces in an image
- Returns array of face position and identities
Single Face Recognition (/face_recog_facecrop)
- Recognizes the name of the person in the picture by using only face image
- Returns face position and identity

Code Examples

Python

    import requests

    def recognize_face(image_path, api_key, company):
        url = "https://api.iapp.co.th/face_recog_single"

        payload = {'company': {YOUR COMPANY NAME}}
        files = [
            ('file', ({YOUR UPLOADED FILE}, open({YOUR UPLOADED FILE}, 'rb'), 'image/jpeg'))
        ]
        headers = {
            'apikey': {YOUR API KEY}
        }

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

JavaScript

const myHeaders = new Headers();
myHeaders.append("apikey", "{YOUR API KEY}");

const formdata = new FormData();
formdata.append("file", fileInput.files[0], "{YOUR UPLOADED FILE}");
formdata.append("company", "{YOUR COMPANY NAME}");

const requestOptions = {
  method: "POST",
  headers: myHeaders,
  body: formdata,
  redirect: "follow"
};

fetch("https://api.iapp.co.th/face_recog_single", requestOptions)
  .then((response) => response.text())
  .then((result) => console.log(result))
  .catch((error) => console.error(error));

PHP

    <?php
    $curl = curl_init();

    curl_setopt_array($curl, array(
        CURLOPT_URL => 'https://api.iapp.co.th/face_recog_single',
        CURLOPT_RETURNTRANSFER => true,
        CURLOPT_CUSTOMREQUEST => 'POST',
        CURLOPT_POSTFIELDS => array(
            'file' => new CURLFILE('{YOUR UPLOADED FILE}'),
            'company' => '{YOUR COMPANY NAME}'
        ),
        CURLOPT_HTTPHEADER => array(
            'apikey: {YOUR API KEY}'
        ),
    ));

    $response = curl_exec($curl);
    curl_close($curl);
    echo $response;

Swift

let parameters = [
  [
    "key": "file",
    "src": "{YOUR UPLOADED FILE}",
    "type": "file"
  ],
  [
    "key": "company",
    "value": "{YOUR COMPANY NAME}",
    "type": "text"
  ]] as [[String: Any]]

let boundary = "Boundary-\(UUID().uuidString)"
var body = Data()
var error: Error? = nil
for param in parameters {
  if param["disabled"] != nil { continue }
  let paramName = param["key"]!
  body += Data("--\(boundary)\r\n".utf8)
  body += Data("Content-Disposition:form-data; name=\"\(paramName)\"".utf8)
  if param["contentType"] != nil {
    body += Data("\r\nContent-Type: \(param["contentType"] as! String)".utf8)
  }
  let paramType = param["type"] as! String
  if paramType == "text" {
    let paramValue = param["value"] as! String
    body += Data("\r\n\r\n\(paramValue)\r\n".utf8)
  } else {
    let paramSrc = param["src"] as! String
    let fileURL = URL(fileURLWithPath: paramSrc)
    if let fileContent = try? Data(contentsOf: fileURL) {
      body += Data("; filename=\"\(paramSrc)\"\r\n".utf8)
      body += Data("Content-Type: \"content-type header\"\r\n".utf8)
      body += Data("\r\n".utf8)
      body += fileContent
      body += Data("\r\n".utf8)
    }
  }
}
body += Data("--\(boundary)--\r\n".utf8);
let postData = body


var request = URLRequest(url: URL(string: "https://api.iapp.co.th/face_recog_single")!,timeoutInterval: Double.infinity)
request.addValue("{YOUR API KEY}", forHTTPHeaderField: "apikey")
request.addValue("multipart/form-data; boundary=\(boundary)", forHTTPHeaderField: "Content-Type")

request.httpMethod = "POST"
request.httpBody = postData

let task = URLSession.shared.dataTask(with: request) { data, response, error in
  guard let data = data else {
    print(String(describing: error))
    return
  }
  print(String(data: data, encoding: .utf8)!)
}

task.resume()

Kotlin

val client = OkHttpClient()
val mediaType = "text/plain".toMediaType()
val body = MultipartBody.Builder().setType(MultipartBody.FORM)
  .addFormDataPart("file","{YOUR UPLOADED FILE}",
    File("{YOUR UPLOADED FILE}").asRequestBody("application/octet-stream".toMediaType()))
  .addFormDataPart("company","{YOUR COMPANY NAME}")
  .build()
val request = Request.Builder()
  .url("https://api.iapp.co.th/face_recog_single")
  .post(body)
  .addHeader("apikey", "{YOUR API KEY}")
  .build()
val response = client.newCall(request).execute()

Java

OkHttpClient client = new OkHttpClient().newBuilder()
  .build();
MediaType mediaType = MediaType.parse("text/plain");
RequestBody body = new MultipartBody.Builder().setType(MultipartBody.FORM)
  .addFormDataPart("file","{YOUR UPLOADED FILE}",
    RequestBody.create(MediaType.parse("application/octet-stream"),
    new File("{YOUR UPLOADED FILE}")))
  .addFormDataPart("company","{YOUR COMPANY NAME}")
  .build();
Request request = new Request.Builder()
  .url("https://api.iapp.co.th/face_recog_single")
  .method("POST", body)
  .addHeader("apikey", "{YOUR API KEY}")
  .build();
Response response = client.newCall(request).execute();

Dart

var headers = {
  'apikey': '{YOUR API KEY}'
};
var request = http.MultipartRequest('POST', Uri.parse('https://api.iapp.co.th/face_recog_single'));
request.fields.addAll({
  'company': '{YOUR COMPANY NAME}'
});
request.files.add(await http.MultipartFile.fromPath('file', '{YOUR UPLOADED FILE}'));
request.headers.addAll(headers);

http.StreamedResponse response = await request.send();

if (response.statusCode == 200) {
  print(await response.stream.bytesToString());
}
else {
  print(response.reasonPhrase);
}

Limitations and Best Practices

Limitations

Maximum image size: 2MB
Minimum image dimensions: 600x400 pixels
Minimum face size: 112x112 pixels
Supported formats: JPG, JPEG, PNG
Queue length restrictions apply

Best Practices

Use well-lit, clear face images
Ensure faces are not obscured
Submit appropriate image sizes
Handle API errors appropriately
Set optimal detection/recognition thresholds

Accuracy & Performance

Overall Accuracy

High accuracy for frontal faces
Performance varies with image quality
Recognition accuracy depends on registered face quality

Processing Speed

Typical response time: 0.3-1.0 seconds
May vary with server load
Queue system manages high traffic

Factors Affecting Accuracy

Image quality and lighting
Face angle and expression
Face size in image
Number of registered faces
Detection/recognition threshold settings

History

The Face Recognition System has evolved to provide robust face detection and recognition capabilities while maintaining high performance and accuracy standards.

Pricing

AI API Service Name	Endpoint	IC Per Request	On-Premise
Face Recognition	iapp_face_recog_v2_multiple_face	0.5 IC/Request	Contact
	iapp_face_recog_v2_only_face	0.3 IC/Request
	iapp_face_recog_v2_single_face	0.3 IC/Request

Getting Started​

Example​

Face Recognition Request:​

Face Recognition Response:​

Features & Capabilities​

Core Features​

Supported Fields​

API Reference​

Face Recognition Endpoints​

Code Examples​

Python​

JavaScript​

PHP​

Swift​

Kotlin​

Java​

Dart​

Limitations and Best Practices​

Limitations​

Best Practices​

Accuracy & Performance​

Overall Accuracy​

Processing Speed​

Factors Affecting Accuracy​

History​

Pricing​