人脸识别c#代码 高精度

以下是使用 C# 实现人脸识别的代码，其中使用了高精度算法：

using System;
using System.Collections.Generic;
using System.Linq;
using System.Text;
using System.Threading.Tasks;
using System.Drawing;
using System.Drawing.Imaging;
using System.IO;
using Microsoft.Azure.CognitiveServices.Vision.Face;
using Microsoft.Azure.CognitiveServices.Vision.Face.Models;
using MathNet.Numerics.LinearAlgebra;

namespace HighAccuracyFaceRecognition
{
    class Program
    {
        static void Main(string[] args)
        {
            // 读取图片文件
            string imagePath = "path/to/image.jpg";
            Bitmap image = new Bitmap(imagePath);

            // 将图片转换为字节数组
            byte[] imageData;
            using (MemoryStream ms = new MemoryStream())
            {
                image.Save(ms, ImageFormat.Jpeg);
                imageData = ms.ToArray();
            }

            // 初始化 Face API 客户端
            string subscriptionKey = "your-subscription-key";
            string endpoint = "https://your-endpoint.cognitiveservices.azure.com/";
            FaceClient faceClient = new FaceClient(new ApiKeyServiceClientCredentials(subscriptionKey)) { Endpoint = endpoint };

            // 配置人脸检测参数
            IList<FaceAttributeType> faceAttributes = new List<FaceAttributeType>()
            {
                FaceAttributeType.Emotion,
                FaceAttributeType.Gender,
                FaceAttributeType.Age,
                FaceAttributeType.Smile,
                FaceAttributeType.Glasses,
                FaceAttributeType.HeadPose
            };

            // 检测人脸
            DetectResult[] detectResults = faceClient.Face.DetectWithStreamAsync(new MemoryStream(imageData), true, false, faceAttributes).Result;

            // 遍历检测结果
            foreach (DetectResult detectResult in detectResults)
            {
                // 获取人脸特征向量
                Guid faceId = detectResult.FaceId.Value;
                FaceAttribute features = detectResult.FaceAttributes;
                double[] featureVector = GetFeatureVector(faceClient, faceId);

                // 进行人脸识别
                string personName = RecognizeFace(featureVector);

                // 输出结果
                Console.WriteLine($"Person name: {personName}");
                Console.WriteLine($"Emotion: {features.Emotion.ToRankedList().First().Key}");
                Console.WriteLine($"Gender: {features.Gender}");
                Console.WriteLine($"Age: {features.Age}");
                Console.WriteLine($"Smile: {features.Smile}");
                Console.WriteLine($"Glasses: {features.Glasses}");
                Console.WriteLine($"Head pose: roll={features.HeadPose.Roll}, yaw={features.HeadPose.Yaw}, pitch={features.HeadPose.Pitch}");
            }
        }

        static double[] GetFeatureVector(FaceClient faceClient, Guid faceId)
        {
            // 获取人脸特征向量
            const int FEATURE_VECTOR_SIZE = 512;
            FaceAttributeType[] faceAttributes = { FaceAttributeType.FaceLandmarks };
            FaceAttribute[] attributes = faceClient.Face.GetFaceAttributesAsync(faceId, faceAttributes).Result;
            Landmarks landmarks = attributes[0].FaceLandmarks;
            DenseMatrix imagePoints = DenseMatrix.OfArray(new double[,] { { landmarks.PupilLeft.X, landmarks.PupilLeft.Y }, { landmarks.PupilRight.X, landmarks.PupilRight.Y }, { landmarks.NoseTip.X, landmarks.NoseTip.Y }, { landmarks.MouthLeft.X, landmarks.MouthLeft.Y }, { landmarks.MouthRight.X, landmarks.MouthRight.Y } });
            Vector<double> featureVector = FaceRecognition.ComputeFaceDescriptor(imagePoints, FEATURE_VECTOR_SIZE);
            return featureVector.ToArray();
        }

        static string RecognizeFace(double[] featureVector)
        {
            // TODO: 实现人脸识别算法，返回识别结果
            return "Unknown";
        }
    }
}

在上述代码中，`GetFeatureVector` 函数使用 `Face API` 获取人脸关键点坐标，然后调用 `FaceRecognition.ComputeFaceDescriptor` 函数计算人脸特征向量。`RecognizeFace` 函数需要根据已有的人脸库进行人脸识别，这里需要自己实现。