/// <summary>
/// 人脸识别
/// </summary>
/// <returns></returns>
public JsonResult FaceDistinguish()
{
// 设置APPID/AK/SK
var API_KEY = "mxzzu1vLxca9KjnLwBCgOZs5"; //你的 Api Key
var SECRET_KEY = "D9CkVbdziW9GrHiAZDENt8rOf0tVw9im"; //你的 Secret Key
var client = new Baidu.Aip.Face.Face(API_KEY, SECRET_KEY);
client.Timeout = 60000; // 修改超时时间
var imageType = "BASE64"; //BASE64 URL
string imgData64 = Request["imgData64"];
imgData64 = imgData64.Substring(imgData64.IndexOf(",") + 1); //将‘，’以前的多余字符串删除
ResultInfo result = new ResultInfo();
try
{
var groupId = "TestGroupA";
var userId = "TestUserA";
var result323 = client.Detect(imgData64, imageType);
//活体检测阈值是多少
//0.05 活体误拒率：万分之一；拒绝率：63.9%
//0.3 活体误拒率：千分之一；拒绝率：90.3%
//0.9 活体误拒率：百分之一；拒绝率：97.6%
//1误拒率: 把真人识别为假人的概率. 阈值越高，安全性越高, 要求也就越高, 对应的误识率就越高
//2、通过率=1-误拒率
//所以你thresholds参数返回 和 face_liveness 比较大于推荐值就是活体
////活体判断
var faces = new JArray
{
new JObject
{
{ "image", imgData64 },
{ "image_type", "BASE64" }
}
};
var Living = client.Faceverify(faces); //活体检测交互返回
var LivingJson = Newtonsoft.Json.JsonConvert.SerializeObject(Living);
var LivingObj = Newtonsoft.Json.JsonConvert.DeserializeObject(LivingJson) as JObject;
if (LivingObj["error_code"].ToString() == "0" && LivingObj["error_msg"].ToString() == "SUCCESS")
{
var Living_result = Newtonsoft.Json.JsonConvert.DeserializeObject(LivingObj["result"].ToString()) as JObject;
var Living_list = Living_result["thresholds"];
double face_liveness = Convert.ToDouble(Living_result["face_liveness"]);
var frr = Newtonsoft.Json.JsonConvert.SerializeObject(Living_list.ToString());
var frr_1eObj = Newtonsoft.Json.JsonConvert.DeserializeObject(Living_list.ToString()) as JObject;
double frr_1e4 = Convert.ToDouble(frr_1eObj["frr_1e-4"]);
if (face_liveness < frr_1e4)
{
result.info = "识别失败：这是相片之类的非活体！";
return(Json(result, JsonRequestBehavior.AllowGet));
}
}
//首先查询是否存在人脸
var result2 = client.Search(imgData64, imageType, groupId);
var strJson = Newtonsoft.Json.JsonConvert.SerializeObject(result2);
var o2 = Newtonsoft.Json.JsonConvert.DeserializeObject(strJson) as JObject;
//判断是否存在当前人脸，相识度是否大于80
if (o2["error_code"].ToString() == "0" && o2["error_msg"].ToString() == "SUCCESS")
{
var result_list = Newtonsoft.Json.JsonConvert.DeserializeObject(o2["result"].ToString()) as JObject;
var user_list = result_list["user_list"];
var Obj = JArray.Parse(user_list.ToString());
foreach (var item in Obj)
{
//80分以上可以判断为同一人，此分值对应万分之一误识率
var score = Convert.ToInt32(item["score"]);
if (score > 80)
{
result.info = result2.ToString();
result.res = true;
result.startcode = 221;
return(Json(result, JsonRequestBehavior.AllowGet));
}
}
}
else
{
result.info = strJson.ToString();
result.res = false;
return(Json(result, JsonRequestBehavior.AllowGet));
}
}
catch (Exception e)
{
result.info = e.Message;
}
return(Json(result, JsonRequestBehavior.AllowGet));
}