static void Main() { // 老图片路径 string oldImgPath = @"C:/Project/View.local.Packages/Images/Image.ViewFace.Test/5.jpg"; string newImgPath = @"C:/Project/View.local.Packages/Images/Image.ViewFace.Test/1.jpg"; ViewFace viewFace = new ViewFace((str) => { Debug.WriteLine(str); }); // 初始化人脸识别类,并设置 日志回调函数 // 系统默认使用的轻量级识别模型。如果对精度有要求,请切换到 Normal 模式;并下载需要模型文件 放入生成目录的 model 文件夹中 viewFace.FaceType = FaceType.Normal; // 系统默认使用5个人脸关键点。//不建议改动,除非是使用口罩模型。 viewFace.MarkType = MarkType.Light; #region 识别老照片 float[] oldEigenValues; Bitmap oldImg = (Bitmap)Image.FromFile(oldImgPath); // 从文件中加载照片 // 或者视频帧等 var oldFaceInfos = viewFace.FaceDetector(oldImg); // 检测图片中包含的人脸信息。(置信度、位置、大小) oldFaceInfos = viewFace.FaceDetectorAsync(oldImg).GetAwaiter().GetResult(); // 异步检测图片中的人脸信息 if (oldFaceInfos.Length > 0) //识别到人脸 { { // 打印人脸信息 Console.WriteLine($"识别到的人脸数量:{oldFaceInfos.Length} 。人脸信息:\n"); Console.WriteLine($"序号\t人脸置信度\t位置X\t位置Y\t宽度\t高度"); for (int i = 0; i < oldFaceInfos.Length; i++) { Console.WriteLine($"{i + 1}\t{oldFaceInfos[i].Score:f8}\t{oldFaceInfos[i].Location.X}\t{oldFaceInfos[i].Location.Y}\t{oldFaceInfos[i].Location.Width}\t{oldFaceInfos[i].Location.Height}"); } Console.WriteLine(); } var oldPoints = viewFace.FaceMark(oldImg, oldFaceInfos[0]); // 获取 第一个人脸 的识别关键点。(人脸识别的关键点数据) oldEigenValues = viewFace.Extract(oldImg, oldPoints); // 获取 指定的关键点 的特征值。 var state = viewFace.AntiSpoofing(oldImg, oldFaceInfos[0], oldPoints); Console.WriteLine($"单帧 活体检测结果:{state}"); state = viewFace.AntiSpoofingVideo(oldImg, oldFaceInfos[0], oldPoints); Console.WriteLine($"视频 活体检测结果:{state}"); Console.WriteLine(); #region 质量评估 var qualityBrightness = viewFace.FaceQuality(oldImg, oldFaceInfos[0], oldPoints, QualityType.Brightness); Console.WriteLine($"亮度:Level [{qualityBrightness.Level}] - Score [{qualityBrightness.Score}]"); var qualityClarity = viewFace.FaceQuality(oldImg, oldFaceInfos[0], oldPoints, QualityType.Clarity); Console.WriteLine($"清晰度:Level [{qualityClarity.Level}] - Score [{qualityClarity.Score}]"); var qualityIntegrity = viewFace.FaceQuality(oldImg, oldFaceInfos[0], oldPoints, QualityType.Integrity); Console.WriteLine($"完整度:Level [{qualityIntegrity.Level}] - Score [{qualityIntegrity.Score}]"); var qualityPose = viewFace.FaceQuality(oldImg, oldFaceInfos[0], oldPoints, QualityType.Pose); Console.WriteLine($"姿态:Level [{qualityPose.Level}] - Score [{qualityPose.Score}]"); var qualityPoseEx = viewFace.FaceQuality(oldImg, oldFaceInfos[0], oldPoints, QualityType.PoseEx); Console.WriteLine($"姿态 (深度):Level [{qualityPoseEx.Level}] - Score [{qualityPoseEx.Score}]"); var qualityResolution = viewFace.FaceQuality(oldImg, oldFaceInfos[0], oldPoints, QualityType.Resolution); Console.WriteLine($"分辨率:Level [{qualityResolution.Level}] - Score [{qualityResolution.Score}]"); var qualityStructure = viewFace.FaceQuality(oldImg, oldFaceInfos[0], oldPoints, QualityType.Structure); Console.WriteLine($"遮挡:Level [{qualityStructure.Level}] - Score [{qualityStructure.Score}]"); var qualityClarityEx = viewFace.FaceQuality(oldImg, oldFaceInfos[0], oldPoints, QualityType.ClarityEx); Console.WriteLine($"清晰度 (深度):Level [{qualityClarityEx.Level}] - Score [{qualityClarityEx.Score}]"); #endregion Console.WriteLine(); #region 人脸属性 var age = viewFace.FaceAgePredictor(oldImg, oldPoints); Console.WriteLine($"人脸预测年龄:{age}"); var gender = viewFace.FaceGenderPredictor(oldImg, oldPoints); Console.WriteLine($"人脸预测性别:{gender.ToDescription()}"); var eyeStateResult = viewFace.FaceEyeStateDetector(oldImg, oldPoints); Console.WriteLine($"左眼状态:{eyeStateResult.LeftEyeState.ToDescription()}"); Console.WriteLine($"右眼状态:{eyeStateResult.RightEyeState.ToDescription()}"); #endregion } else { oldEigenValues = new float[0]; /*未识别到人脸*/ } #endregion Console.WriteLine(); #region 人脸追踪 var trackFaceInfos = viewFace.FaceTrack(oldImg); // 人脸追踪 if (trackFaceInfos.Length > 0) { { // 打印人脸信息 Console.WriteLine($"\r\n跟踪到的人脸数量:{trackFaceInfos.Length} 。人脸信息:\n"); Console.WriteLine($"PID\t人脸置信度\t位置X\t位置Y\t宽度\t高度"); for (int i = 0; i < trackFaceInfos.Length; i++) { Console.WriteLine($"{trackFaceInfos[i].Pid}\t{trackFaceInfos[i].Score:f8}\t{trackFaceInfos[i].Location.X}\t{trackFaceInfos[i].Location.Y}\t{trackFaceInfos[i].Location.Width}\t{trackFaceInfos[i].Location.Height}"); } } } #endregion Console.WriteLine(); #region 识别新照片 float[] newEigenValues; Bitmap newImg = (Bitmap)Image.FromFile(newImgPath /*新图片路径*/); // 从文件中加载照片 // 或者视频帧等 newImg = (Bitmap)newImg.ChangeSize(new Size(1024, 768)); var newFaces = viewFace.FaceDetector(newImg); // 检测图片中包含的人脸信息。(置信度、位置、大小) if (newFaces.Length > 0) //识别到人脸 { { // 打印人脸信息 Console.WriteLine($"识别到的人脸数量:{newFaces.Length} 。人脸信息:\n"); Console.WriteLine($"序号\t人脸置信度\t位置X\t位置Y\t宽度\t高度"); for (int i = 0; i < newFaces.Length; i++) { Console.WriteLine($"{i + 1}\t{newFaces[i].Score:f8}\t{newFaces[i].Location.X}\t{newFaces[i].Location.Y}\t{newFaces[i].Location.Width}\t{newFaces[i].Location.Height}"); } } var newPoints = viewFace.FaceMark(newImg, newFaces[0]); // 获取 第一个人脸 的识别关键点。(人脸识别的关键点数据) newEigenValues = viewFace.Extract(newImg, newPoints); // 获取 指定的关键点 的特征值。 } else { newEigenValues = new float[0]; /*未识别到人脸*/ } #endregion Console.WriteLine(); try { float similarity = viewFace.Similarity(oldEigenValues, newEigenValues); // 对比两张照片上的数据,确认是否是同一个人。 Console.WriteLine($"阈值 = {FaceCompareConfig.GetThreshold(viewFace.FaceType)}\t相似度 = {similarity}"); Console.WriteLine($"是否是同一个人:{viewFace.IsSelf(similarity)}"); } catch (Exception e) { Console.WriteLine(e.Message); } Console.ReadKey(); }