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      首頁 > 編程開發 > c#教程 >
      • C#教程之C# 30分鐘完成百度人臉識別——進階篇(

      • 2019-04-13 21:18 來源:未知

      距離上次入門篇時隔兩個月才出這進階篇,小編慚愧,對不住關注我的卡哇伊的小伙伴們,為此小編用這篇博來謝罪。

      前面的準備工作我就不說了,注冊百度賬號api,創建web網站項目,引入動態鏈接庫引入。

      不了解的童鞋可以花費10分鐘移步學習:https://www.cnblogs.com/xiongze520/p/10387355.html(C# 10分鐘完成百度人臉識別——入門篇)。

      如果要學習的童鞋最好下載本demo源碼,因為有信息入庫功能,BLL、DAL、數據庫就在源碼里面。


        一般情況下筆記本自帶的可見光攝像頭就可以進行人臉識別,但是這種攝像頭不能很好的進行活體檢測,可能會被照片和視頻騙過,

      而且受到光線影響,太暗或者太亮都不行。如果要實現更好的人臉識別效果和更高的安全性,

      就需要特殊的人臉識別攝像頭或者配套寬動態和近紅外雙攝像頭,既能確保活體,又能使用光線,我們這里就使用簡單的筆記本自帶的攝像頭進行講解,

      后續有相關需要的可以討論討論。


      提示:下載源碼對比觀看效果更佳

      百度網盤源碼下載鏈接:https://pan.baidu.com/s/1IzJCeF8uTKjZ882BTxI4bw 
      提取碼:p92w

      復制這段內容后打開百度網盤手機App,操作更方便哦。

      我的百度人臉庫一直開啟,需要使用的小伙伴們自行在下面代碼里面提取api_key和secret_key

      操作的步驟(我使用的編輯器是visual studio 2013):

      • 效果圖查看;
      • 人臉注冊:開啟攝像頭,填入當前人臉注冊的相關信息進行注冊;
      • 人臉識別:開啟攝像頭,將人臉移入攝像頭指定區域進行識別;
      • 總結:

       效果圖查看:


       人臉注冊——效果圖:

      百度人臉識別控制臺查看人臉——效果圖

       

       

       數據庫查看數據——效果圖

       

       

       人臉識別成功——效果圖

       

       

      活體檢測——效果圖

       

      控制關鍵代碼預覽——截圖

       

       

       


       人臉注冊:


        (文末附帶源碼)新建一個ASP.NET Web應用程序網站項目,命名為WebApplication1,添加百度SDK引用,不知道怎么引用的童鞋看這兒:https://www.cnblogs.com/xiongze520/p/10387355.html。

      添加簡單的類庫充當三層架構,分別命名為:FaceBLL、FaceDAL、FaceModel,引入自己擅長的ORM框架(SQLSugar、Dapper、EF等,小編引入的SQLSugar)。

      編寫映射實體Face_UserInfo,字段和數據庫一樣,編寫相關的bll、dal、增刪查改。

      接下來就是控制器編寫,我們把代碼粘貼出來看一下(單獨粘貼這個代碼是會報錯的,因為沒有bll、dal等內容):

      提示:下載源碼對比觀看效果更佳

      百度網盤源碼下載鏈接:https://pan.baidu.com/s/1IzJCeF8uTKjZ882BTxI4bw 
      提取碼:p92w

      復制代碼
       //人臉注冊
              public JsonResult Face_Registration()
              {
                  // 設置APPID/AK/SK
                  var API_KEY = "XFPA49myCG7S37XP1DxjLbXF";                   //你的 Api Key
                  var SECRET_KEY = "ZvZKigrixMLXNZOLmkrG6iDx9QprlGuT";        //你的 Secret Key
                  var client = new Baidu.Aip.Face.Face(API_KEY, SECRET_KEY);
                  client.Timeout = 60000;  // 修改超時時間
      
                  var imageType = "BASE64";  //BASE64   URL
                  string imgData64 = Request["imgData64"];
                  imgData64 = imgData64.Substring(imgData64.IndexOf(",") + 1);      //將‘,’以前的多余字符串刪除
      
                  ResultInfo result = new ResultInfo();
                  try
                  {
                      //注冊人臉
                      var groupId = "group1";
                      var userId = "user1";
                      //首先查詢是否存在人臉
                      var result2 = client.Search(imgData64, imageType, userId);  //會出現222207(未找到用戶)這個錯誤
                      var strJson = Newtonsoft.Json.JsonConvert.SerializeObject(result2);
                      var o2 = Newtonsoft.Json.JsonConvert.DeserializeObject(strJson) as JObject;
      
      
                      //判斷是否存在當前人臉,相識度是否大于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分以上可以判斷為同一人,此分值對應萬分之一誤識率
                              var score = Convert.ToInt32(item["score"]);
                              if(score>80)
                              {
                                  result.info = result2.ToString();
                                  result.res = true;
                                  result.startcode = 221;
                                  return Json(result, JsonRequestBehavior.AllowGet);
                              }
                          }
                      }
      
                      var guid = Guid.NewGuid();
                      // 調用人臉注冊,可能會拋出網絡等異常,請使用try/catch捕獲
                      // 如果有可選參數
                      var options = new Dictionary<string, object>{
                                  {"user_info", guid}
                              };
                      // 帶參數調用人臉注冊
                      var resultData = client.UserAdd(imgData64, imageType, groupId, userId, options);
                      result.info = resultData.ToString();
                      result.res = true;
                      result.other = guid.ToString();
                  }
                  catch (Exception e)
                  {
                      result.info = e.Message;
                  }
                  return Json(result, JsonRequestBehavior.AllowGet);
              }
      
      //用戶信息入庫
              public JsonResult face_userInfoSace()
              {
                  ResultInfo result = new ResultInfo();
      
                  try
                  {
                      //這里就不進行非空判斷了,后期根據實際情況進行優化
                      var UserName = Request["UserName"];
                      var Month = Request["Month"];
                      var Sex = Request["Sex"];
                      var Works = Request["Works"];
                      var face_token = Request["face_token"];
                      var Guid_Id = Request["Guid_Id"];
      
                      Face_UserInfo model = new Face_UserInfo();
                      model.UserName = UserName;
                      model.Month = Month;
                      model.Sex = Sex;
                      model.Works = Works;
                      model.face_token = face_token;
                      model.Guid_Id = Guid_Id;
      
                      //根據人臉唯一標識判斷是否存在數據
                      List<Face_UserInfo> strlist = new Face_UserInfoBLL().GetfaceinfoByToken(Guid_Id);
                      if(strlist.Count>0)
                      {
                          result.res = true;
                          result.info = "當前用戶已注冊過!";
                          return Json(result, JsonRequestBehavior.AllowGet);
                      }
      
                      if(new Face_UserInfoBLL().face_userInfoSace(model)>0)
                      {
                          result.res = true;
                          result.info = "注冊成功";
                      }
                      else
                          result.info = "注冊失敗";
                  }
                  catch (Exception e)
                  {
                      result.info = e.Message;
                  }
                  return Json(result, JsonRequestBehavior.AllowGet);
              }
      
          
      復制代碼

      人臉識別:


       

       注冊完后就是識別,識別主要做一個簡單的活體檢測。識別后將人臉相關信息顯示出來。

      注意,人臉識別效果可以做出特效,本人才疏學淺,誰會canvas動畫的可以私我,有個人臉識別的動畫特效需要實現,我做了一個簡單的上下掃描動畫。

      下面就將代碼貼出來:

      復制代碼
              //人臉識別
              public JsonResult Face_Distinguish()
              {
                  // 設置APPID/AK/SK
                  var API_KEY = "XFPA49myCG7S37XP1DxjLbXF";                   //你的 Api Key
                  var SECRET_KEY = "ZvZKigrixMLXNZOLmkrG6iDx9QprlGuT";        //你的 Secret Key
                  var client = new Baidu.Aip.Face.Face(API_KEY, SECRET_KEY);
                  client.Timeout = 60000;  // 修改超時時間
      
                  var imageType = "BASE64";  //BASE64   URL
                  string imgData64 = Request["imgData64"];
                  imgData64 = imgData64.Substring(imgData64.IndexOf(",") + 1);      //將‘,’以前的多余字符串刪除
      
                  ResultInfo result = new ResultInfo();
                  try
                  {
                      var groupId = "group1";
                      var userId = "user1";
      
                      var result323 = client.Detect(imgData64, imageType);
      
                      //活體檢測閾值是多少
                      //0.05 活體誤拒率:萬分之一;拒絕率:63.9%
                      //0.3 活體誤拒率:千分之一;拒絕率:90.3%
                      //0.9 活體誤拒率:百分之一;拒絕率:97.6%
                      //1誤拒率: 把真人識別為假人的概率. 閾值越高,安全性越高, 要求也就越高, 對應的誤識率就越高
                      //2、通過率=1-誤拒率
                      //所以你thresholds參數返回 和 face_liveness 比較大于推薦值就是活體
      
                      ////活體判斷
                      var faces = new JArray
                              {
                                  new JObject
                                  {
                                      {"image", imgData64},
                                      {"image_type", "BASE64"}
                                  }
                              };
                      var Living = client.Faceverify(faces);  //活體檢測交互返回
                      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 = "識別失敗:不是活體!";
                              return Json(result, JsonRequestBehavior.AllowGet);
                          }
                      }
      
                      //首先查詢是否存在人臉
                      var result2 = client.Search(imgData64, imageType, groupId);  
                      var strJson = Newtonsoft.Json.JsonConvert.SerializeObject(result2);
                      var o2 = Newtonsoft.Json.JsonConvert.DeserializeObject(strJson) as JObject;
      
      
                      //判斷是否存在當前人臉,相識度是否大于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分以上可以判斷為同一人,此分值對應萬分之一誤識率
                              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);
              }
      
          
              //識別成功,查詢數據庫
              public JsonResult Face_UserInfoList()
              {
                  ResultInfo result = new ResultInfo();
                  //這里就不進行非空判斷了,后期根據實際情況進行優化
                  var Guid_Id = Request["Guid_Id"];
                  //根據人臉唯一標識判斷是否存在數據
                  List<Face_UserInfo> strlist = new Face_UserInfoBLL().GetfaceinfoByToken(Guid_Id);
                  var strJson = Newtonsoft.Json.JsonConvert.SerializeObject(strlist);
                  result.info = strJson;
                  result.res = true;
                  return Json(result, JsonRequestBehavior.AllowGet);
              }
      復制代碼

      總結:


       

       

      匆匆忙忙就結束了,其實學起來也簡單,大家下載demo對比學習一下,有什么疑問大家討論討論。

      刪除、更新還是一樣的操作,去直接拷貝官網的幾行代碼即可,都是需要face_token作為添加更新刪除,這個字段注冊的時候已經存到數據庫了。

      我的百度人臉庫一直開啟,需要使用的小伙伴們自行在下面代碼里面提取api_key和secret_key

      又要去開啟新項目,大家后面再見。

      關注小編不迷路!

       

      demo源碼下載:

      百度網盤源碼下載鏈接:https://pan.baidu.com/s/1IzJCeF8uTKjZ882BTxI4bw 
      提取碼:p92w

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