👤 Face Detection

👤 ระบบตรวจจับใบหน้า

Welcome to Face Detection API, an AI product developed by iApp Technology Co., Ltd. Our API is designed to detect and extract faces from images with high accuracy and speed. The API supports both single and multiple face detection with flexible scoring options.

Try Demo!

Example Images (Click to try)

API Key

Demo key is limited to 10 requests per day per IP
Click here to get your API key

Endpoint URL

cURL Command

Upload Image

Getting Started

1. Prerequisites

   • An API key from iApp Technology
   • Image files containing faces
   • Supported formats: JPEG, JPG, PNG
   • Maximum file size: 10MB

2. Quick Start

   • Fast processing time
   • High accuracy face detection
   • Support for multiple file formats
   • Flexible scoring options

3. Key Features

   • Single and multiple face detection
   • Face bounding box coordinates
   • Detection confidence scores
   • Face image extraction
   • Company-specific scoring options

4. 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

Single Face Detection Request:

Image Preview

curl --location --request POST 'https://api.iapp.co.th/face_detect_single' \
--header 'apikey: {Your API Key}' \
--form 'file=@"{Your Image File Path}"'

Single Face Detection Response:

{
  "bbox": {
    "xmax": 320.15,
    "xmin": 100.23,
    "ymax": 450.78,
    "ymin": 150.45
  },
  "detection_score": 0.9998989105224609,
  "face": "/9j/4AAQ...base64_encoded_image",
  "message": "success",
  "process_time": 0.41
}

Multiple Face Detection Request:

Image Preview

curl --location --request POST 'https://api.iapp.co.th/face_detect_multi' \
--header 'apikey: {Your API Key}' \
--form 'file=@"{Your Image File Path}"'

Multiple Face Detection Response:

{
    "message": "success",
    "process_time": 0.67,
    "result": [
        {
            "bbox": {
                "xmax":1317.7054443359375,
                "xmin":1075.64013671875,
                "ymax":555.1968994140625,
                "ymin":243.38815307617188
            },
            "detection_score": 0.99,
            "face": "/9j/4AAQ...base64_encoded_image"
        },
        {
            "bbox": {
                "xmax":684.1102294921875,
                "xmin":484.45068359375,
                "ymax":520.4813842773438,
                "ymin":265.50823974609375
            },
            "detection_score": 0.99,
            "face": "/9j/4AAQ...base64_encoded_image"
        },
        ...
    ]
}

Features & Capabilities

Core Features

• Single and multiple face detection
• Face bounding box coordinates
• Detection confidence scores
• Base64 encoded face images
• Company-specific scoring options

Supported Fields

Single Face Detection Response

Field	Type	Description
bbox	Dictionary	Face bounding box coordinates
detection_score	Float	Face detection confidence score
face	String	Base64 encoded face image
message	String	Processing status
process_time	Float	Processing time in seconds

Multiple Face Detection Response

Field	Type	Description
message	String	Processing status
process_time	Float	Processing time in seconds
result	Array	Array of detected faces
bbox	Dictionary	Face bounding box coordinates
detection_score	Float	Face detection confidence score
face	String	Base64 encoded face image

Code Examples

Python

import requests

url = "https://api.iapp.co.th/face_detect_single"

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

response = requests.request("POST", url, headers=headers, data=payload, files=files)

print(response.text)

JavaScript

const axios = require('axios');
const FormData = require('form-data');
const fs = require('fs');
let data = new FormData();
data.append('file', fs.createReadStream('/Users/iapp/Downloads/removebg_trial.png'));

let config = {
    method: 'post',
    maxBodyLength: Infinity,
    url: 'https://api.iapp.co.th/face_detect_single',
    headers: {
    'apikey': 'YOUR_API_KEY',
    ...data.getHeaders()
    },
    data : data
};

axios.request(config)
.then((response) => {
console.log(JSON.stringify(response.data));
})
.catch((error) => {
console.log(error);
});

PHP

<?php

$curl = curl_init();

curl_setopt_array($curl, array(
    CURLOPT_URL => 'https://api.iapp.co.th/face_detect_single',
    CURLOPT_RETURNTRANSFER => true,
    CURLOPT_ENCODING => '',
    CURLOPT_MAXREDIRS => 10,
    CURLOPT_TIMEOUT => 0,
    CURLOPT_FOLLOWLOCATION => true,
    CURLOPT_HTTP_VERSION => CURL_HTTP_VERSION_1_1,
    CURLOPT_CUSTOMREQUEST => 'POST',
    CURLOPT_POSTFIELDS => array('file'=> new CURLFILE('{YOUR UPLOADED IMAGE}')),
    CURLOPT_HTTPHEADER => array(
        'apikey: {YOUR API KEY}'
        ),
    ));

$response = curl_exec($curl);

curl_close($curl);
echo $response;

Swift

let parameters = [[
    "key": "file",
    "src": "{YOUR UPLOADED IMAGE}",
    "type": "file"
    ]] 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_detect_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","file",
        File("{YOUR API KEY}").asRequestBody("application/octet-stream".toMediaType()))
    .build()
val request = Request.Builder()
    .url("https://api.iapp.co.th/face_detect_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","file",
        RequestBody.create(MediaType.parse("application/octet-stream"),
        new File("{YOUR UPLOADED IMAGE}")))
    .build();
Request request = new Request.Builder()
    .url("https://api.iapp.co.th/face_detect_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_detect_single'));
request.files.add(await http.MultipartFile.fromPath('file', '{YOUR UPLOADED IMAGE}'));
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 file size: 10MB
• Supported formats: JPEG, JPG, PNG
• Maximum number of faces per image: 50

Best Practices

1. Ensure good image quality
2. Check detection scores
3. Handle error messages appropriately
4. Consider using company-specific scoring
5. Optimize image size before upload

Accuracy & Performance

Overall Accuracy

• Detection score typically above 95%
• Performance varies with image quality

Processing Speed

• Single face: 0.3-0.5 seconds
• Multiple faces: 0.5-1.0 seconds

Factors Affecting Accuracy

1. Image Quality
   • Resolution
   • Lighting
   • Focus
2. Face Orientation
   • Head pose
   • Facial expressions
   • Occlusions

History

Version 1.0 (Released: Jan 2023)

• Key Improvements: Initial Release

Version 0.9 (Released: Nov 2022)

• Key Improvements: Beta Testing

Version 0.8 (Released: Sep 2022)

• Key Improvements: Internal Testing

Pricing

AI API Service Name	Endpoint	IC Per Request	On-Premise
Face Detection	iapp_face_detection_v2_multiple_face	0.2 IC/Request	Contact
	iapp_face_detection_v2_single_face	0.2 IC/Request