人脸活体检测API
人脸活体检测接口（API）采用自研深度学习算法与图像处理技术，实现人脸活体检测能力。可以检测图像中的人脸是否为来自认证设备端的近距离裸拍活体人脸对象，可广泛应用在人脸实时采集场景，满足人脸注册认证的真实性和安全性要求。活体判断的前置条件是图像中有人脸。
￥0.00
（100次）
价格：
更多价格，联系右下角“客服”
接口信息
请求URL：https://face-api.shiliuai.com/api/face_liveness/v1
请求方式：POST
返回类型：JSON
接口参数
请求参数（Header）
方式一：简单认证
| 参数 | 类型 | 说明 |
|---|---|---|
| Content-type | string | application/json |
| Authorization | string | 'APPCODE ' + 您的AppCode (注意英文空格) |
方式二：签名认证
| 参数 | 类型 | 说明 |
|---|---|---|
| Content-type | string | application/json |
| x-ca-key | string | 您的AppKey |
| x-ca-timestamp | string | 时间戳（毫秒） |
| x-ca-signature | string | 签名sign |
注：签名方法
str = app_key×tamp&app_secret
sign = md5(str)
请求参数（Query）
请求参数（Body）
| 参数 | 是否必填 | 类型 | 说明 |
|---|---|---|---|
| image_base64 | 必填 | string | base64编码的图片文件,像素范围：[15,8192]，小于20M |
平台通过已登录用户信息获取当前账号临时 Access Keys、"发起请求" 可能对当前账号发起线上资源操作，请小心操作
简单认证
签名认证
Python
PHP
Java
C#
Python
PHP
Java
C#
75 lines
import com.alibaba.fastjson2.JSON;
import com.alibaba.fastjson2.JSONObject;
import org.apache.http.HttpResponse;
import org.apache.http.client.methods.HttpPost;
import org.apache.http.entity.StringEntity;
import org.apache.http.impl.client.CloseableHttpClient;
import org.apache.http.impl.client.HttpClients;
import org.apache.http.util.EntityUtils;
import org.apache.commons.io.FileUtils;
import java.io.File;
import java.io.IOException;
import java.util.HashMap;
import java.util.Map;
import java.util.Base64;
public class Main {
public static String get_base64(String path) {
String b64 = "";
try {
// 使用Commons IO简化文件读取
byte[] content = FileUtils.readFileToByteArray(new File(path));
// 使用JDK自带的Base64
b64 = Base64.getEncoder().encodeToString(content);
} catch (IOException e) {
e.printStackTrace();
}
return b64;
}
public static void main(String[] args) {
String url = "https://face-api.shiliuai.com/api/face_liveness/v1";
String appcode = "你的APPCODE";
String imgFile = "本地图片路径";
Map headers = new HashMap<>();
headers.put("Authorization", "APPCODE " + appcode);
headers.put("Content-Type", "application/json");
JSONObject requestObj = new JSONObject();
requestObj.put("image_base64", get_base64(imgFile));
String bodys = requestObj.toString();
try (CloseableHttpClient httpClient = HttpClients.createDefault()) {
HttpPost httpPost = new HttpPost(url);
for (Map.Entry entry : headers.entrySet()) {
httpPost.addHeader(entry.getKey(), entry.getValue());
}
StringEntity entity = new StringEntity(bodys, "UTF-8");
httpPost.setEntity(entity);
HttpResponse response = httpClient.execute(httpPost);
int stat = response.getStatusLine().getStatusCode();
if (stat != 200) {
System.out.println("Http code: " + stat);
return;
}
String res = EntityUtils.toString(response.getEntity());
JSONObject res_obj = JSON.parseObject(res);
System.out.println(res_obj.toJSONString());
} catch (Exception e) {
e.printStackTrace();
}
}
}
44 lines
//图片转base64
function get_base64($path){
if($fp = fopen($path, "rb", 0)) {
$binary = fread($fp, filesize($path)); // 文件读取
fclose($fp);
$b64 = base64_encode($binary); // 转base64
}else{
$b64="";
printf("%s 文件不存在", $path);
}
return $b64;
}
$url = "https://face-api.shiliuai.com/api/face_liveness/v1";
$appcode = "你的appcode";
$img_path = "图片路径";
$method = "POST";
//请求头
$headers = array();
array_push($headers, "Authorization:APPCODE " . $appcode);
array_push($headers, "Content-Type:application/json");
//请求体
$b64 = get_base64($img_path);
$data = array(
"image_base64" => $b64
);
$post_data = json_encode($data);
//请求
$curl = curl_init();
curl_setopt($curl, CURLOPT_CUSTOMREQUEST, $method);
curl_setopt($curl, CURLOPT_URL, $url);
curl_setopt($curl, CURLOPT_HTTPHEADER, $headers);
curl_setopt($curl, CURLOPT_FAILONERROR, false);
curl_setopt($curl, CURLOPT_RETURNTRANSFER, true);
curl_setopt($curl, CURLOPT_HEADER, true);
curl_setopt($curl, CURLOPT_SSL_VERIFYPEER, false);
curl_setopt($curl, CURLOPT_SSL_VERIFYHOST, false);
curl_setopt($curl, CURLOPT_POSTFIELDS, $post_data);
$result = curl_exec($curl);
var_dump($result);
36 lines
# -*- coding: utf-8 -*-
import requests
import base64
import json
# 请求接口
URL = "https://face-api.shiliuai.com/api/face_liveness/v1"
# 图片转base64
def get_base64(file_path):
with open(file_path, 'rb') as f:
data = f.read()
b64 = base64.b64encode(data).decode('utf8')
return b64
def demo(appcode, file_path):
# 请求头
headers = {
'Authorization': 'APPCODE %s' % appcode,
'Content-Type': 'application/json'
}
# 请求体
b64 = get_base64(file_path)
data = {"image_base64": b64}
# 请求
response = requests.post(url=URL, headers=headers, json=data)
content = json.loads(response.content)
print(content)
if __name__=="__main__":
appcode = "你的APPCODE"
file_path = "本地图片路径"
demo(appcode, file_path)
78 lines
using System.Text;
using Newtonsoft.Json;
using Newtonsoft.Json.Linq;
namespace MyCSharpApp
{
public class Program
{
public static string GetBase64(string path)
{
string b64 = "";
try
{
// 读取文件内容
byte[] content = File.ReadAllBytes(path);
// 转换为Base64
b64 = Convert.ToBase64String(content);
}
catch (Exception e)
{
Console.WriteLine(e.Message);
}
return b64;
}
public static async Task Main(string[] args)
{
string url = "https://face-api.shiliuai.com/api/face_liveness/v1"; // 请求接口
string appcode = "你的APPCODE";
string imgFile = "本地图片路径";
// 设置请求头
Dictionary headers = new Dictionary
{
{ "Authorization", "APPCODE " + appcode }
// Content-Type 将在创建 StringContent 时设置
};
// 请求体
JObject requestObj = new JObject();
requestObj["image_base64"] = GetBase64(imgFile);
string body = requestObj.ToString();
try
{
using (HttpClient client = new HttpClient())
{
// 设置请求头
foreach (var header in headers)
{
client.DefaultRequestHeaders.Add(header.Key, header.Value);
}
// 创建请求内容
StringContent content = new StringContent(body, Encoding.UTF8, "application/json");
// 发送请求并获取响应
HttpResponseMessage response = await client.PostAsync(url, content);
if (!response.IsSuccessStatusCode)
{
Console.WriteLine($"Http code: {(int)response.StatusCode}");
return;
}
// 读取响应内容
string responseContent = await response.Content.ReadAsStringAsync();
JObject resObj = JObject.Parse(responseContent);
Console.WriteLine(resObj.ToString(Formatting.Indented));
}
}
catch (Exception e)
{
Console.WriteLine(e.Message);
}
}
}
}
48 lines
import requests
import base64
import json
import hashlib
import time
# 请求接口
URL = "https://face-api.shiliuai.com/api/face_liveness/v1"
# 图片转base64
def get_base64(file_path):
with open(file_path, 'rb') as f:
data = f.read()
b64 = base64.b64encode(data).decode('utf8')
return b64
# md5
def md5(s):
return hashlib.md5(s.encode("utf8")).hexdigest()
def demo(app_key, app_secret, file_path):
# 请求头
t = int(time.time() * 1000)
s = "%s&%s&%s" % (app_key, t, app_secret)
sign = md5(s)
headers = {'x-ca-key': app_key,
'x-ca-timestamp': t,
'x-ca-signature': sign,
"Content-Type": "application/json"}
# 请求体
b64 = get_base64(file_path)
data = {"image_base64": b64}
# 请求
response = requests.post(url=URL, headers=headers, json=data)
content = json.loads(response.content)
print(content)
if __name__=="__main__":
app_key = "你的APP_KEY"
app_secret = "你的APP_SECRET"
file_path = "本地图片路径"
demo(app_key, app_secret, file_path)
53 lines
function get_base64($path){
if($fp = fopen($path, "rb", 0)) {
$binary = fread($fp, filesize($path)); // 文件读取
fclose($fp);
$b64 = base64_encode($binary); // 转base64
}else{
$b64="";
printf("%s 文件不存在", $path);
}
return $b64;
}
$url = "https://face-api.shiliuai.com/api/face_liveness/v1";
$img_path = "图片路径";
$method = "POST";
//请求头
$app_key = "你的app_key";
$app_secret = "你的app_secret";
$sign_string = $app_key . "&" . $timestamp . "&" . $app_secret;
$sign = md5($sign_string);
$headers = array();
array_push($headers, "Content-Type:application/json");
array_push($headers, "x-ca-key:" . $app_key);
array_push($headers, "x-ca-timestamp:" . $timestamp);
array_push($headers, "x-ca-signature:" . $sign);
//请求体
$b64 = get_base64($img_path);
$data = array(
"image_base64" => $b64
);
$post_data = json_encode($data);
//请求
$curl = curl_init();
curl_setopt($curl, CURLOPT_CUSTOMREQUEST, $method);
curl_setopt($curl, CURLOPT_URL, $url);
curl_setopt($curl, CURLOPT_HTTPHEADER, $headers);
curl_setopt($curl, CURLOPT_FAILONERROR, false);
curl_setopt($curl, CURLOPT_RETURNTRANSFER, true);
curl_setopt($curl, CURLOPT_HEADER, true);
curl_setopt($curl, CURLOPT_SSL_VERIFYPEER, false);
curl_setopt($curl, CURLOPT_SSL_VERIFYHOST, false);
curl_setopt($curl, CURLOPT_POSTFIELDS, $post_data);
$result = curl_exec($curl);
var_dump($result);
113 lines
import com.alibaba.fastjson2.JSON;
import com.alibaba.fastjson2.JSONObject;
import org.apache.commons.io.FileUtils;
import org.apache.http.HttpResponse;
import org.apache.http.client.methods.HttpPost;
import org.apache.http.entity.StringEntity;
import org.apache.http.impl.client.CloseableHttpClient;
import org.apache.http.impl.client.HttpClients;
import org.apache.http.util.EntityUtils;
import java.io.File;
import java.io.IOException;
import java.util.HashMap;
import java.util.Map;
import java.util.Base64;
import java.security.MessageDigest;
import java.security.NoSuchAlgorithmException;
public class Demo {
public static String get_base64(String path) {
String b64 = "";
try {
File file = new File(path);
if (!file.exists()) {
System.err.println("文件不存在: " + path);
return b64;
}
byte[] content = FileUtils.readFileToByteArray(file);
b64 = Base64.getEncoder().encodeToString(content);
} catch (IOException e) {
System.err.println("读取文件失败: " + e.getMessage());
e.printStackTrace();
}
return b64;
}
public static String MD5(String input) {
try {
MessageDigest md = MessageDigest.getInstance("MD5");
byte[] messageDigest = md.digest(input.getBytes());
StringBuilder hexString = new StringBuilder();
for (byte b : messageDigest) {
String hex = Integer.toHexString(0xff & b);
if (hex.length() == 1)
hexString.append('0');
hexString.append(hex);
}
return hexString.toString();
} catch (NoSuchAlgorithmException e) {
e.printStackTrace();
}
return null;
}
public static void main(String[] args) {
String url = "https://face-api.shiliuai.com/api/face_liveness/v1";
String imgFile = "本地图片路径";
String app_key = "你的APPKEY";
String app_secret = "你的APPSECRET";
String timestamp = System.currentTimeMillis() + "";
String sign = MD5(app_key + "&" + timestamp + "&" + app_secret);
Map headers = new HashMap<>();
headers.put("Content-Type", "application/json");
headers.put("x-ca-key", app_key);
headers.put("x-ca-timestamp", timestamp);
headers.put("x-ca-signature", sign);
JSONObject requestObj = new JSONObject();
requestObj.put("image_base64", get_base64(imgFile));
String bodys = requestObj.toString();
try (CloseableHttpClient httpClient = HttpClients.createDefault()) {
HttpPost httpPost = new HttpPost(url);
for (Map.Entry entry : headers.entrySet()) {
httpPost.addHeader(entry.getKey(), entry.getValue());
}
StringEntity entity = new StringEntity(bodys, "UTF-8");
httpPost.setEntity(entity);
HttpResponse response = httpClient.execute(httpPost);
int stat = response.getStatusLine().getStatusCode();
if (stat != 200) {
System.out.println("Http code: " + stat);
System.out.println("Http " + EntityUtils.toString(response.getEntity()));
return;
}
String res = EntityUtils.toString(response.getEntity());
JSONObject res_obj = JSON.parseObject(res);
System.out.println(res_obj.toJSONString());
} catch (Exception e) {
e.printStackTrace();
}
}
}
111 lines
using System.Security.Cryptography;
using System.Text;
using Newtonsoft.Json;
using Newtonsoft.Json.Linq;
namespace MyCSharpApp
{
public class Program
{
public static string GetBase64(string path)
{
string b64 = "";
try
{
// 读取文件内容
byte[] content = File.ReadAllBytes(path);
// 转换为Base64
b64 = Convert.ToBase64String(content);
}
catch (Exception e)
{
Console.Error.WriteLine("读取文件失败: " + e.Message);
Console.WriteLine(e.Message);
}
return b64;
}
public static string CalculateMD5(string input)
{
try
{
// 创建MD5哈希提供程序
using (MD5 md5 = MD5.Create())
{
// 计算输入字符串的哈希值
byte[] inputBytes = Encoding.UTF8.GetBytes(input);
byte[] hashBytes = md5.ComputeHash(inputBytes);
// 将字节数组转换为十六进制字符串
StringBuilder sb = new StringBuilder();
for (int i = 0; i < hashBytes.Length; i++)
{
sb.Append(hashBytes[i].ToString("x2"));
}
return sb.ToString();
}
}
catch (Exception e)
{
Console.WriteLine(e.Message);
return string.Empty; // 返回空字符串而不是null
}
}
public static async Task Main(string[] args)
{
string url = "https://face-api.shiliuai.com/api/face_liveness/v1"; // 请求接口
string imgFile = "本地图片路径";
string app_key = "你的APPKEY";
string app_secret = "你的APPSECRET";
string timestamp = DateTimeOffset.Now.ToUnixTimeMilliseconds().ToString();
string sign = CalculateMD5(app_key + "&" + timestamp + "&" + app_secret);
// 设置请求头
Dictionary headers = new Dictionary
{
{ "x-ca-key", app_key },
{ "x-ca-timestamp", timestamp },
{ "x-ca-signature", sign }
};
// 请求体
JObject requestObj = new JObject();
requestObj["image_base64"] = GetBase64(imgFile);
string body = requestObj.ToString();
try
{
using (HttpClient client = new HttpClient())
{
// 设置请求头
foreach (var header in headers)
{
client.DefaultRequestHeaders.Add(header.Key, header.Value);
}
// 创建请求内容
StringContent content = new StringContent(body, Encoding.UTF8, "application/json");
// 发送请求并获取响应
HttpResponseMessage response = await client.PostAsync(url, content);
if (!response.IsSuccessStatusCode)
{
Console.WriteLine($"Http code: {(int)response.StatusCode}");
Console.WriteLine($"Http {await response.Content.ReadAsStringAsync()}");
return;
}
// 读取响应内容
string responseContent = await response.Content.ReadAsStringAsync();
JObject resObj = JObject.Parse(responseContent);
Console.WriteLine(resObj.ToString(Formatting.Indented));
}
}
catch (Exception e)
{
Console.WriteLine(e.Message);
}
}
}
}
返回信息
错误码说明
| 参数 | 参数类型 | 说明 |
|---|---|---|
| code | int | 错误码 |
| msg | string | 错误信息（英文） |
| msg_cn | string | 错误信息（中文） |
| success | bool | 识别是否成功 |
| image_id | string | 图片请求ID |
| request_id | string | 唯一请求ID |
| data | data | 具体看下面 |
data 成功示例：
data = {
"rotation": int,
转正角度，图片转正需要旋转的顺时针角度，可取值0，90，180，270
"faces":
[
{
"rect":
{(转正后的)
"left":
int, 人脸框与左边距离,
"top":
int, 人脸框与上边距离,
"width":
int, 人脸框宽度,
"height":
int, 人脸框高度
},
"liveness":
float, [0, 1], 活体分数
},
......
]
"face_num": int, 人脸数量
}
data 失败示例：
data = {}
| 错误码 | 说明 |
|---|---|
| 200 | 成功 |
| 400 | 错误请求，比如参数错误 |
| 401 | 未经授权 |
| 403 | 禁止访问 |
| 429 | 请求过多 |
| 500 | 内部错误 |
| 604 | 接口停用 |
| 1001 | 服务异常，返回具体的错误原因 |
商品介绍
简介
人脸活体检测，可以检测图像中的人脸是否为来自认证设备端的近距离裸拍活体人脸对象，可广泛应用在人脸实时采集场景，满足人脸注册认证的真实性和安全性要求。活体判断的前置条件是图像中有人脸。
主要功能
1. 人脸是否活体
人脸活体检测接口可以从上传的人脸照片中提取独特的面部特征点，判断是否活体。
2. 获取人脸信息
通过检测识别图像中有人脸，返回人脸框与左边距离，人脸框与上边距离，人脸框宽度、高度。
3. 多种输入格式支持
支持多种图片格式（如JPEG、PNG、BMP等）的输入，适应不同应用场景的需求。
4. 实时处理
API具有高效的处理能力，能够在毫秒级时间内完成对比，适合实时性要求高的应用场景。
商品价格
| API类型 | 价格说明 |
|---|---|
| 人脸活体检测接口API | 每次调用消耗一积分 |
| 如有问题联系右侧“客服” | |