请允许我大言不惭，叫做教程，特希望各位能指正。哦，我用的是vs2017。
一、准备工作
1.创建项目
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2.添加EMGU.CV包
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，并设属性“复制到输出目录”为“如果较新则复制”
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3.添加程序集System.ServiceModel的引用（Emgu视频捕捉需要）
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准备工作到此结束，按F7切换到代码，然后进入第二步。
using Emgu.CV;
using System;
using System.Collections.Concurrent;
using System.Collections.Generic;
using System.Diagnostics;
using System.Drawing;
using System.IO;
using System.Runtime.InteropServices;
using System.Threading;
using System.Threading.Tasks;
using System.Windows.Forms;
namespace ArcFace2Demo
{
public partial class Form1 : Form
{
#region ArcFaceConst
const uint ASF_DETECT_MODE_VIDEO = 0x00000000; //Video模式，一般用于多帧连续检测
const uint ASF_DETECT_MODE_IMAGE = 0xFFFFFFFF; //Image模式，一般用于静态图的单次检测
const uint ASF_NONE = 0x00000000;
const uint ASF_FACE_DETECT = 0x00000001; //此处detect可以是tracking或者detection两个引擎之一，具体的选择由detect mode 确定
const uint ASF_FACERECOGNITION = 0x00000004;
const uint ASF_AGE = 0x00000008;
const uint ASF_GENDER = 0x00000010;
const uint ASF_FACE3DANGLE = 0x00000020;
///
/// 结构ASF_FaceRect的长度
/// 32位程序是16,64位程序需要改为32
///
const int SizeOfASF_FaceRect = 16;
#endregion
#region ArceDataStructure
///
/// 人脸在图片中的位置
///
[StructLayout(LayoutKind.Sequential)]
internal struct ASF_FaceRect
{
public int Left;
public int Top;
public int Right;
public int Bottom;
public Rectangle GetRectangle()
{
return new Rectangle(Left, Top, Right - Left, Bottom - Top);
}
}
///
/// 多人脸信息
///
[StructLayout(LayoutKind.Sequential)]
internal struct ASF_MultiFaceInfo
{
public IntPtr PFaceRect;
public IntPtr PFaceOrient;
[MarshalAs(UnmanagedType.I4)]
public int FaceNum;
}
///
/// 单人脸信息
///
[StructLayout(LayoutKind.Sequential)]
internal struct ASF_SingleFaceInfo
{
public ASF_FaceRect FaceRect;
public int FaceOrient;
}
///
/// 人脸特征
///
[StructLayout(LayoutKind.Sequential)]
internal struct ASF_FaceFeature
{
public IntPtr PFeature;
[MarshalAs(UnmanagedType.I4)]
public int FeatureSize;
}
#endregion
#region ArcWrapper
///
/// 激活SDK
///
///
///
/// 0:激活成功，0x16002表示已经激活
[DllImport("libarcsoft_face_engine.dll", EntryPoint = "ASFActivation", CallingConvention = CallingConvention.Cdecl, CharSet = CharSet.Ansi)]
private static extern int ASFActivation(string appId, string sdkKey);
///
/// 初始化引擎
///
/// long会返回scale错误0x16004
///
///
///
///
///
///
/// 人脸检测
///
///
///
///
///
///
///
///
/// 单人脸特征提取
///
///
///
///
///
///
///
///
/// 脸特征比对
///
///
///
///
///
///
/// 销毁引擎
///
///
///
/// 特征库
///
IntPtr _PFeatureLib;
///
/// 特征库人脸数量
///
int _FeatureLibFaceCount = 0;
///
/// 特征库人脸ID列表
///
List _FeatureLibIDList = new List();
///
/// 人脸特征结构
///
ASF_FaceFeature _FaceFeature = new ASF_FaceFeature { FeatureSize = 1032 };
///
/// 人脸识别的结果
///
class FaceResult
{
///
/// 人脸框矩形
///
public Rectangle Rectangle { get; set; }
///
/// 人脸ID
///
public string ID { get; set; }
///
/// 比对结果
///
public float Score { get; set; }
public override string ToString()
{
return [ DISCUZ_CODE_0 ]quot;ID:{ID}\r\n结果：{Score}";
}
}
///
/// 多人脸识别结果集
///
ConcurrentDictionary _FaceResults = new ConcurrentDictionary();
///
/// 检测到的人脸数量
///
int _DetectedFaceCount = 0;
///
/// 视频捕获
///
VideoCapture _VideoCapture;
Mat _Frame = new Mat();
///
/// 虹软人脸引擎
///
IntPtr _PEngine = IntPtr.Zero;
///
/// 比对一次总耗时
///
long _TotalElapsedMilliseconds = 0;
///
/// 识别任务
///
Task _TaskMatch;
///
/// 向识别任务发送取消指令的东东
///
CancellationTokenSource _CTS = new CancellationTokenSource();
///
/// 图像数据
///
IntPtr _PImageData;
///
/// 宽、高、图像数据长度
///
int _ImageWidth, _ImageHeight, _ImageSize;
///
/// 是否要保存当前人脸特征
///
bool _SaveFlag = false;
PictureBox _PictureBox;
public Form1()
{
InitializeComponent();
_PictureBox = new PictureBox();
_PictureBox.SizeMode = PictureBoxSizeMode.StretchImage;
_PictureBox.Dock = DockStyle.Fill;
this.Controls.Add(_PictureBox);
this.Load += Form1_Load;
this.FormClosing += Form1_FormClosing;
}
private void Form1_FormClosing(object sender, FormClosingEventArgs e)
{
if (_TaskMatch != null)
{
_CTS.Cancel();
while (_TaskMatch.Status == TaskStatus.Running)
Task.Delay(1000).Wait();
}
_VideoCapture.Stop();
if (_PEngine != IntPtr.Zero)
ASFUninitEngine(_PEngine);
if (_PFeatureLib != IntPtr.Zero)
Marshal.FreeCoTaskMem(_PFeatureLib);
if (_PImageData != IntPtr.Zero)
Marshal.FreeCoTaskMem(_PImageData);
}
private unsafe void Form1_Load(object sender, EventArgs e)
{
var ret = ASFActivation("BKgqTWQPQQbomfqvyd2VJzTUqPp3JD8zjAzDcqsL1jLa", "2nkDTmnkpS53cpSY42fFS9nEUzg8x4MDGkAubSsebtm1");
if (ret != 0 && ret != 0x16002)
{
MessageBox.Show("SDK激活失败：0x" + ret.ToString("x2"));
return;
}
ret = ASFInitEngine(ASF_DETECT_MODE_IMAGE, 1, 32, 10, ASF_FACE_DETECT | ASF_FACERECOGNITION, out _PEngine);
if (ret != 0)
{
MessageBox.Show([ DISCUZ_CODE_0 ]quot;人脸识别引擎初始化失败:" + ret.ToString("x2"));
return;
}
//初始化识别结果集
for (int i = 0; i < 10; i++)
_FaceResults[i] = new FaceResult();
//初始化特征库
_PFeatureLib = Marshal.AllocCoTaskMem(1032 * 1000 + 1032 * 10000 * 20);
var bytes = File.ReadAllBytes("Feature.dat");
var ids = File.ReadAllLines("Id.txt");
for (int i = 0; i < 20 * 20; i++)
{
Marshal.Copy(bytes, 0, IntPtr.Add(_PFeatureLib, _FeatureLibFaceCount * 1032), bytes.Length);
_FeatureLibIDList.AddRange(ids);
_FeatureLibFaceCount += ids.Length;
}
_VideoCapture = new VideoCapture();
//_VideoCapture.SetCaptureProperty(Emgu.CV.CvEnum.CapProp.FrameWidth, 1024);
//_VideoCapture.SetCaptureProperty(Emgu.CV.CvEnum.CapProp.FrameHeight, 768);
_VideoCapture.SetCaptureProperty(Emgu.CV.CvEnum.CapProp.Fps, 10);
_VideoCapture.Start();
_VideoCapture.ImageGrabbed += (object oo, EventArgs es) =>
{
_VideoCapture.Retrieve(_Frame, 1);
using (Graphics g = Graphics.FromImage(_Frame.Bitmap))
{
g.DrawString([ DISCUZ_CODE_0 ]quot;比对总耗时{_TotalElapsedMilliseconds}毫秒", this.Font, Brushes.White, 0, 0);
for (int i = 0; i < _DetectedFaceCount; i++)
{
if (_FaceResults.TryGetValue(i, out var faceResult))
{
g.DrawRectangle(Pens.Red, faceResult.Rectangle);
g.DrawString(faceResult.ToString(), this.Font, Brushes.White, faceResult.Rectangle.Location);
}
}
}
this._PictureBox.Image = _Frame.Bitmap;
};
_PictureBox.Click += (object oo, EventArgs es) =>
{
if (MessageBox.Show("您确定要保存人脸特征数据吗？", "确认信息", MessageBoxButtons.YesNo, MessageBoxIcon.Question, MessageBoxDefaultButton.Button2) == DialogResult.Yes)
_SaveFlag = true;
};
_ImageSize = _VideoCapture.Width * _VideoCapture.Height * 3;
_PImageData = Marshal.AllocCoTaskMem(_ImageSize);
_ImageWidth = _VideoCapture.Width;
_ImageHeight = _VideoCapture.Height;
_TaskMatch = Task.Run(() =>
{
Task.Delay(1000).Wait();
while (!_CTS.IsCancellationRequested)
{
try
{
Stopwatch sw = new Stopwatch();
sw.Restart();
Marshal.Copy(_Frame.GetData(), 0, _PImageData, _ImageSize);
ret = ASFDetectFaces(_PEngine, _ImageWidth, _ImageHeight, 513, _PImageData, out var faceInfo);
if (ret != 0 || faceInfo.FaceNum == 0)
{
_DetectedFaceCount = 0;
continue;
}
for (int detectedFaceIndex = 0; detectedFaceIndex < faceInfo.FaceNum; detectedFaceIndex++)
{
float score = 0;
string id = "";
ASF_SingleFaceInfo singleFaceInfo = new ASF_SingleFaceInfo
{
FaceRect = Marshal.PtrToStructure(IntPtr.Add(faceInfo.PFaceRect, SizeOfASF_FaceRect * detectedFaceIndex)),
FaceOrient = 1// Marshal.ReadInt32(IntPtr.Add(faceInfo.PFaceOrient, i * 4))
};
ret = ASFFaceFeatureExtract(_PEngine, _ImageWidth, _ImageHeight, 513, _PImageData, ref singleFaceInfo, out var faceFeature);
if (ret != 0)
continue;
_FaceResults[detectedFaceIndex].Rectangle = singleFaceInfo.FaceRect.GetRectangle();
if (_SaveFlag)
{
byte[] bufferSave = new byte[1032];
Marshal.Copy(faceFeature.PFeature, bufferSave, 0, 1032);
var newId = DateTime.Now.Ticks.ToString();
FileStream fs = new FileStream("Feature.dat", FileMode.Append);
fs.Write(bufferSave, 0, 1032);
fs.Close();
var streamWriter = File.AppendText("Id.txt");
streamWriter.Write("\r\n" + newId);
streamWriter.Close();
Marshal.Copy(bufferSave, 0, IntPtr.Add(_PFeatureLib, 1032 * _FeatureLibFaceCount), 1032);
_FeatureLibIDList.Add(newId);
_FeatureLibFaceCount++;
if (detectedFaceIndex == faceInfo.FaceNum - 1)
{
MessageBox.Show("保存特征数据成功！");
_SaveFlag = false;
}
continue;
}
ConcurrentBag needCompareFaceIndexs = new ConcurrentBag();
Parallel.For(0, _FeatureLibFaceCount, faceIndex =>
{
byte* pLib = ((byte*)_PFeatureLib) + 1032 * faceIndex + 8;
byte* pCurrent = ((byte*)faceFeature.PFeature) + 8;
int count = 0;
for (int j = 0; j < 1024; j++)
{
if (*pLib++ == *pCurrent++)
count++;
}
if (count > 80)
needCompareFaceIndexs.Add(faceIndex);
});
foreach (var index in needCompareFaceIndexs)//650ms
{
_FaceFeature.PFeature = IntPtr.Add(_PFeatureLib, index * 1032);
ASFFaceFeatureCompare(_PEngine, ref faceFeature, ref _FaceFeature, out var r);
if (r > 0.8 && r > score)
{
score = r;
id = _FeatureLibIDList[index];
}
}
_FaceResults[detectedFaceIndex].Score = score;
_FaceResults[detectedFaceIndex].ID = id;
}
_DetectedFaceCount = faceInfo.FaceNum;
sw.Stop();
_TotalElapsedMilliseconds = sw.ElapsedMilliseconds;
}
catch (Exception ex)
{
}
}
}, _CTS.Token);
}
}
}
三、下载测试用特征数据（500张人脸）并解压到运行目录
image
ArcFaceData.zip
四、按F5运行
点击视频增加当前人脸的特征数据，基本上800毫秒可以从20万人脸中找到你。