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Getting Started - Web APIs
Quick start guide for integrating VerifEye Web APIs into your applications.
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📋 Prerequisites
- ✅ A VerifEye account and API key
- ✅ HTTP client library (curl, axios, requests, etc.)
- ✅ Basic understanding of REST APIs
- ✅ HTTPS support in your application
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🔐 Authentication
All API requests require authentication using your API key:
Authorization: Bearer YOUR_API_KEY
Content-Type: application/json
Security
Never expose your API key in client-side code. Always make API calls from your backend server.
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🌍 API Endpoints
Choose the region closest to your users for best performance:
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🚀 Quick Start
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cURL Example
curl -X POST https://api-us-east.verifeye.com/v1/face/liveness \
-H "Authorization: Bearer YOUR_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"image": "base64_encoded_image_data"
}'
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JavaScript (Node.js)
const axios = require('axios');
const fs = require('fs');
const apiKey = 'YOUR_API_KEY';
const imageBase64 = fs.readFileSync('face.jpg', 'base64');
axios.post('https://api-us-east.verifeye.com/v1/face/liveness', {
image: imageBase64
}, {
headers: {
'Authorization': `Bearer ${apiKey}`,
'Content-Type': 'application/json'
}
})
.then(response => {
console.log('Result:', response.data);
})
.catch(error => {
console.error('Error:', error.response.data);
});
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Python
import requests
import base64
api_key = 'YOUR_API_KEY'
url = 'https://api-us-east.verifeye.com/v1/face/liveness'
# Read and encode image
with open('face.jpg', 'rb') as f:
image_base64 = base64.b64encode(f.read()).decode('utf-8')
headers = {
'Authorization': f'Bearer {api_key}',
'Content-Type': 'application/json'
}
data = {
'image': image_base64
}
response = requests.post(url, json=data, headers=headers)
result = response.json()
print('Result:', result)
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C# (.NET)
using System;
using System.Net.Http;
using System.Text;
using System.Threading.Tasks;
using Newtonsoft.Json;
var apiKey = "YOUR_API_KEY";
var url = "https://api-us-east.verifeye.com/v1/face/liveness";
using var client = new HttpClient();
client.DefaultRequestHeaders.Add("Authorization", $"Bearer {apiKey}");
var imageBase64 = Convert.ToBase64String(File.ReadAllBytes("face.jpg"));
var data = new { image = imageBase64 };
var json = JsonConvert.SerializeObject(data);
var content = new StringContent(json, Encoding.UTF8, "application/json");
var response = await client.PostAsync(url, content);
var result = await response.Content.ReadAsStringAsync();
Console.WriteLine(result);
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📊 Response Format
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Success Response
{
"success": true,
"data": {
"is_live": true,
"confidence": 0.98,
"face_detected": true,
"face_bounds": {
"x": 120,
"y": 80,
"width": 200,
"height": 250
}
},
"request_id": "req_1234567890"
}
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Error Response
{
"success": false,
"error": {
"code": "INVALID_IMAGE",
"message": "The provided image format is not supported",
"details": "Supported formats: JPEG, PNG, WebP"
},
"request_id": "req_1234567890"
}
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📚 Next Steps
Explore the Web API features:
- Face Liveness Detection
- Face Match Verification
- Face Search
- DeepFake Detection
- Age/Gender Verification
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🆘 Need Help?
Last updated: 2025-01-13