renlian
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@ -7,6 +7,6 @@ namespace Common
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public static class AppSettings
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{
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public static string SchoolCode = "202501060001";
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public static string BackendUrl = "http://localhost:9992/api/StudentFace";
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public static string BackendUrl = "http://localhost:9991/api/StudentFace";
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}
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}
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@ -5,7 +5,7 @@ namespace Wpf_AiSportsMicrospace.Common
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{
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public class HttpManager
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{
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public static async Task<string> HttpPostAsync(string url, string postData = null, string contentType = "application/json", int timeOut = 30, Dictionary<string, string> headers = null)
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public static string HttpPost(string url, string postData = null, string contentType = "application/json", int timeOut = 30, Dictionary<string, string> headers = null)
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{
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using (var client = new HttpClient())
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{
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@ -27,9 +27,10 @@ namespace Wpf_AiSportsMicrospace.Common
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try
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{
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var response = await client.PostAsync(url, content);
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// 注意：要调用 PostAsync 而不是 po()
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var response = client.PostAsync(url, content).Result; // 同步等待
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response.EnsureSuccessStatusCode();
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return await response.Content.ReadAsStringAsync();
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return response.Content.ReadAsStringAsync().Result;
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}
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catch (Exception ex)
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{
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@ -37,6 +38,7 @@ namespace Wpf_AiSportsMicrospace.Common
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}
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}
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}
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public static async Task<string> HttpGetAsync(string url, Dictionary<string, string> headers = null)
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{
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using (var client = new HttpClient())
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@ -214,10 +214,10 @@ namespace Wpf_AiSportsMicrospace.Common
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return _cache.GetValueOrDefault(relativePath);
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}
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public static async Task<List<StudentInfoDto>> FacialRecognition(byte[] buffer, double[] xNorms)
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public static List<StudentInfoDto> FacialRecognition(byte[] buffer, double[] xNorms)
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{
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if (xNorms == null || xNorms.Length < 2)
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throw new ArgumentException("xNorms 至少需要两个元素");
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if (xNorms == null || xNorms.Length == 0)
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throw new ArgumentException("xNorms 不能为空");
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using var image = SharpImage.Image.Load<Rgba32>(buffer);
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@ -225,43 +225,66 @@ namespace Wpf_AiSportsMicrospace.Common
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int imgHeight = image.Height;
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int rectHeight = imgHeight / 2;
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// 计算分割边界
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// 1. 排序中心点
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var sortedX = xNorms.OrderBy(x => x).ToList();
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int faceCount = sortedX.Count;
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// 2. 计算分割边界
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var splitXs = new List<double>();
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for (int i = 0; i < sortedX.Count - 1; i++)
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splitXs.Add((sortedX[i] + sortedX[i + 1]) / 2.0);
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// 3. 起止边界
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splitXs.Insert(0, 0.0);
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splitXs.Add(1.0);
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// 4. 输出目录
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string imgDir = Path.Combine(AppContext.BaseDirectory, "img");
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Directory.CreateDirectory(imgDir);
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var studentInfos = new List<StudentInfoDto>();
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for (int i = 0; i < 6 && i < splitXs.Count - 1; i++)
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// 5. 循环裁剪 + 同步识别
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for (int i = 0; i < faceCount; i++)
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{
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int x1 = (int)(splitXs[i] * imgWidth);
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int x2 = (int)(splitXs[i + 1] * imgWidth);
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int w = x2 - x1;
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double xStart = splitXs[i];
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double xEnd = splitXs[i + 1];
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int x1 = (int)(xStart * imgWidth);
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int x2 = (int)(xEnd * imgWidth);
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int w = Math.Max(1, x2 - x1);
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var cropRect = new Rectangle(x1, 0, w, rectHeight);
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using var cropped = image.Clone(ctx => ctx.Crop(cropRect));
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// 转为 Base64
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using var ms = new MemoryStream();
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cropped.Save(ms, new JpegEncoder());
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ms.Position = 0;
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string imgPath = Path.Combine(imgDir, $"crop_{i + 1}_{DateTime.Now:HHmmssfff}.jpg");
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File.WriteAllBytes(imgPath, ms.ToArray());
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string base64 = Convert.ToBase64String(ms.ToArray());
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// 调用人脸识别方法（假设返回姓名+头像Base64）
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StudentInfoDto studentInfo = await FaceRecognitionAsync(base64);
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studentInfos.Add(studentInfo);
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Console.WriteLine($"[{i + 1}] 范围: {xStart:0.00}-{xEnd:0.00}, 宽: {w}");
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// === 同步调用人脸识别接口 ===
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var result = FaceRecognitionAsync(base64);
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if (result != null)
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studentInfos.Add(result);
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}
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return studentInfos;
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}
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/// <summary>
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/// 调用人脸识别接口，返回学生信息
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/// </summary>
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public static async Task<StudentInfoDto> FaceRecognitionAsync(string base64Image)
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public static StudentInfoDto FaceRecognitionAsync(string base64Image)
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{
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var param = new
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{
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@ -272,23 +295,26 @@ namespace Wpf_AiSportsMicrospace.Common
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string json = JsonSerializer.Serialize(param);
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// 调用 HttpPostAsync
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string response = await HttpManager.HttpPostAsync(AppSettings.BackendUrl, json);
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string response = HttpManager.HttpPost(AppSettings.BackendUrl, json);
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if (string.IsNullOrEmpty(response))
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return null;
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try
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{
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// 反序列化为接口返回对象
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var faceInfo = JsonSerializer.Deserialize<StudentInfoDto>(response, new JsonSerializerOptions
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// 假设 response 是 JSON 字符串
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var apiResponse = JsonSerializer.Deserialize<ApiResponse<StudentInfoDto>>(response, new JsonSerializerOptions
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{
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PropertyNameCaseInsensitive = true
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});
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if (faceInfo == null)
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// 取 data
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var studentInfo = apiResponse.Data;
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if (studentInfo == null)
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return null;
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return faceInfo;
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return studentInfo;
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}
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catch
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{
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12
Wpf_AiSportsMicrospace/Dto/ApiResponse.cs
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12
Wpf_AiSportsMicrospace/Dto/ApiResponse.cs
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@ -0,0 +1,12 @@
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namespace Dto
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{
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public class ApiResponse<T>
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{
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public bool Status { get; set; }
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public int Code { get; set; }
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public string Message { get; set; }
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public T Data { get; set; }
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}
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}
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@ -9,13 +9,14 @@ namespace Dto
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/// </summary>
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public class StudentInfoDto
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{
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public string Name { get; set; }
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public string StudentName { get; set; }
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public string Photo { get; set; }
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public string StudentNo { get; set; }
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public string SchoolCode { get; set; }
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public string StudentCode { get; set; }
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public int GradeId { get; set; }
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public int ClassId { get; set; }
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public string GradeName { get; set; }
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public string ClassName { get; set; }
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public int Age { get; set; }
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public string Sex { get; set; }
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public int Sex { get; set; }
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}
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}
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@ -70,12 +70,25 @@ namespace Wpf_AiSportsMicrospace.Views
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}
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private async void UserControl_Loaded(object sender, RoutedEventArgs e)
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{
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// 绑定人脸识别事件
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_mainWin.FacialRecognitionEvent += async (sender, buffer) =>
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// 使用局部变量保存事件处理方法，以便解绑
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EventHandler<byte[]> handler = null;
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handler = async (sender, buffer) =>
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{
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var studentList = await Utils.FacialRecognition(buffer, new double[] { 0.50, 0.78 });
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var studentList = Utils.FacialRecognition(buffer, new double[] { 0.21, 0.36, 0.50, 0.64, 0.78, 0.92 });
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if (studentList != null && studentList.Count > 0)
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{
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// 解绑事件
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_mainWin.FacialRecognitionEvent -= handler;
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}
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// 这里可以继续处理 studentList
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};
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// 绑定事件
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_mainWin.FacialRecognitionEvent += handler;
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DrawCirclesWithText();
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// 播放音乐
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