虹软开放人脸识别SDK以来，成功把人脸识别技术拉下神台，几乎所有开发者可以“0成本”使用到人脸（证）到其项目。但在官方论坛，QQ群，微信群等平台，很多初学者对如何在多线程下使用产生疑惑，掉入坑中（尤其是没有C++的基础的C#开发）。今天，分享两种.net (core)下的多线程使用方式，贡大家探讨。大家有更好的方式，也可以积极留言交流。
先分析问题来源，为什么C#的一般多线程调用方式容易产生错误，尤其是“尝试写保护内存”的错误。原因是C#开发使用的虹软的算法SDK均为C++版本（Windows/Linux），C++作为线程不安全的程序，可以直接操作内存。多个线程同时调用一个引擎，就是同时对一段内存操作，产生内存错误，程序崩溃。
解决方案一：基于 ThreadLocal 强制一个线程捆绑一个引擎。
ThreadLocal的主要作用是让各个线程维持自己的变量。ThreadLocal 是 线程的局部变量， 是每一个线程所单独持有的 ，其他线程不能对其进行访问， 通常是类中的 private static 字段。当使用ThreadLocal维护变量的时候 为每一个使用该变量的线程提供一个独立的变量副本，即每个线程内部都会有一个该变量，这样同时多个线程访问该变量并不会彼此相互影响，因此他们使用的都是自己从内存中拷贝过来的变量的副本， 这样就不存在线程安全问题，也不会影响程序的执行性能。 在虹软人脸的具体应用中，毫无疑问，把初始化好的引擎指针（C#中的Intptr类型）赋值给线程的Threadlocal，就可以开心的玩耍了。找个网上的code演示下：（本人基于ThreadLocal 的工程找不到了）
static void Main()
{
var local = new ThreadLocal<IntPtr>();
//修改TLS的线程
Thread th = new Thread(() =>
{
local.Value = intptr; //虹软引擎指针
DoSomething(); //虹软人脸对比具体流程
})
th.Start();
th.Join();
}
解决方案二：基于“引擎池”实现多线程与高并发。
相比于方案一，我更喜欢“引擎池”，应为它更方便灵活，还更适合.net core Web Api这样的后端框架。废话不说，代码伺候：
1. 定义"引擎池"接口 （由于我方业务需要，初始化了3个不同的引擎池，相关的引擎参数不相同）
public interface IEnginePoor
{
public ConcurrentQueue<IntPtr> FaceEnginePoor { get; set; }
public ConcurrentQueue<IntPtr> IDEnginePoor { get; set; }
public ConcurrentQueue<IntPtr> AIEnginePoor { get; set; }
public IntPtr GetEngine(ConcurrentQueue<IntPtr> queue);
public void PutEngine(ConcurrentQueue<IntPtr> queue, IntPtr item);
}
2. 实现相关接口 （Arcsoft_Face_3_0 为虹软dll的C#封装）
public class Arcsoft_Face_Action : Arcsoft_Face_3_0, IEnginePoor
{
public string AppID { get; }
public string AppKey { get; }
public int FaceEngineNums { get; set; }
public int IDEngineNums { get; set; }
public int AIEngineNums { get; set; }
public ConcurrentQueue<IntPtr> FaceEnginePoor { get; set; }
public ConcurrentQueue<IntPtr> IDEnginePoor { get; set; }
public ConcurrentQueue<IntPtr> AIEnginePoor { get; set; }
private int InitEnginePool()
{
try
{
for (int index = 0; index < FaceEngineNums; index++)
{
IntPtr enginePtr = IntPtr.Zero;
Arcsoft_Face_Action faceAction = new Arcsoft_Face_Action(AppID, AppKey);
enginePtr = faceAction.InitASFEnginePtr(ParmsBestPractice.faceBaseMask);
PutEngine(FaceEnginePoor, enginePtr);
Console.WriteLine($"FaceEnginePoor add {enginePtr}");
}
for (int index = 0; index < IDEngineNums; index++)
{
IntPtr enginePtr = IntPtr.Zero;
Arcsoft_Face_Action faceAction = new Arcsoft_Face_Action(AppID, AppKey);
enginePtr = faceAction.InitASFEnginePtr(ParmsBestPractice.faceBaseMask);
PutEngine(IDEnginePoor, enginePtr);
Console.WriteLine($"IDEnginePoor add {enginePtr}");
}
for (int index = 0; index < AIEngineNums; index++)
{
IntPtr enginePtr = IntPtr.Zero;
int aiMask = FaceEngineMask.ASF_AGE | FaceEngineMask.ASF_GENDER | FaceEngineMask.ASF_FACE3DANGLE | FaceEngineMask.ASF_LIVENESS;
Arcsoft_Face_Action faceAction = new Arcsoft_Face_Action(AppID, AppKey);
enginePtr = faceAction.InitASFEnginePtr(ParmsBestPractice.faceBaseMask | aiMask);
PutEngine(AIEnginePoor, enginePtr);
Console.WriteLine($"AIEnginePoor add {enginePtr}");
}
return 0;
}
catch (Exception ex)
{
throw new Exception($"InitEnginePool--> exception {ex}");
}
}
public IntPtr GetEngine(ConcurrentQueue<IntPtr> queue)
{
IntPtr item = IntPtr.Zero;
if (queue.TryDequeue(out item))
{
return item;
}
else
{
return IntPtr.Zero;
}
}
public void PutEngine(ConcurrentQueue<IntPtr> queue, IntPtr item)
{
if (item != IntPtr.Zero)
{
queue.Enqueue(item);
}
}
public void Arcsoft_EnginePool(int faceEngineNums , int idEngineNums , int aiEngineNums)
{
FaceEnginePoor = new ConcurrentQueue<IntPtr>();
IDEnginePoor = new ConcurrentQueue<IntPtr>();
AIEnginePoor = new ConcurrentQueue<IntPtr>();
try
{
FaceEngineNums = faceEngineNums;
IDEngineNums = idEngineNums;
AIEngineNums = aiEngineNums;
int status = InitEnginePool();
if (status != 0)
{
throw new Exception("引擎池初始化失败！");
}
}
catch (Exception ex)
{
throw new Exception($"ArcSoft_EnginePool-->ArcSoft_EnginePool exception as: {ex}");
}
}
private int InitEnginePool()
{
try
{
for (int index = 0; index < FaceEngineNums; index++)
{
IntPtr enginePtr = IntPtr.Zero;
Arcsoft_Face_Action faceAction = new Arcsoft_Face_Action(AppID, AppKey);
enginePtr = faceAction.InitASFEnginePtr(ParmsBestPractice.faceBaseMask);
PutEngine(FaceEnginePoor, enginePtr);
Console.WriteLine($"FaceEnginePoor add {enginePtr}");
}
for (int index = 0; index < IDEngineNums; index++)
{
IntPtr enginePtr = IntPtr.Zero;
Arcsoft_Face_Action faceAction = new Arcsoft_Face_Action(AppID, AppKey);
enginePtr = faceAction.InitASFEnginePtr(ParmsBestPractice.faceBaseMask);
PutEngine(IDEnginePoor, enginePtr);
Console.WriteLine($"IDEnginePoor add {enginePtr}");
}
for (int index = 0; index < AIEngineNums; index++)
{
IntPtr enginePtr = IntPtr.Zero;
int aiMask = FaceEngineMask.ASF_AGE | FaceEngineMask.ASF_GENDER | FaceEngineMask.ASF_FACE3DANGLE | FaceEngineMask.ASF_LIVENESS;
Arcsoft_Face_Action faceAction = new Arcsoft_Face_Action(AppID, AppKey);
enginePtr = faceAction.InitASFEnginePtr(ParmsBestPractice.faceBaseMask | aiMask);
PutEngine(AIEnginePoor, enginePtr);
Console.WriteLine($"AIEnginePoor add {enginePtr}");
}
return 0;
}
catch (Exception ex)
{
throw new Exception($"InitEnginePool--> exception {ex}");
}
}
}
3. 实现CustomServiceCollection 方便依赖注入
public static class CustomServiceCollection
{
public static IServiceCollection AddArcSoftFaceService(this IServiceCollection services, Arcsoft_Face_Action enginePool)
{
services.AddSingleton<IEnginePoor, Arcsoft_Face_Action>(x => enginePool);
return services;
}
}
4. 在Startup里面添加“虹软”Service。（同时推荐搭配Microsoft.AspNetCore.ConcurrencyLimiter中间件，限制并发量，以免内存不足）
public void ConfigureServices(IServiceCollection services)
{
services.AddMvc();
services.AddControllers();
//用于传入的请求进行排队处理,避免线程池的不足.
services.AddQueuePolicy(options =>
{
//最大并发请求数 (建议与引擎数保持一直，虹软官方的说法是的最大引擎数不超过电脑的核数，我反正是不信的，难道志强和奔腾一样？内存足够大，我一般是和虚拟线程数一致，比如6核12线程，我就开12个引擎。)
options.MaxConcurrentRequests = faceEngineNums;
//请求队列长度限制
options.RequestQueueLimit = requestQueueLimit;
});
//添加虹软“引擎池”服务
Arcsoft_Face_Action enginePool = new Arcsoft_Face_Action(appID, faceKey);
enginePool.Arcsoft_EnginePool(faceEngineNums, 0, 0);
services.AddArcSoftFaceService(enginePool);
}
5. 在Controller里面实际使用。
public class FaceController : ControllerBase
{
public FaceController(IConfiguration configuration, IEnginePoor process)
{
Configuration = configuration;
FaceProcess = process;
float.TryParse(Configuration.GetSection("AppSettings:FaceMixLevel").Value, out faceMix);
int.TryParse(Configuration.GetSection("AppSettings:MaxProcessTime").Value, out maxProcessTime);
}
[HttpPost]
[Route("CompareTwoFaces")]
[DisableRequestSizeLimit]
public IActionResult CompareTwoFaces(IFormFile faceA, IFormFile faceB)
{
IntPtr engine = FaceProcess.GetEngine(FaceProcess.FaceEnginePoor);
CancellationTokenSource tokenSource = new CancellationTokenSource();
CustomResult faceResult = new CustomResult();
Tuple<bool, IntPtr, string> faceAResult = new Tuple<bool, IntPtr, string>(false, IntPtr.Zero, null);
Tuple<bool, IntPtr, string> faceBResult = new Tuple<bool, IntPtr, string>(false, IntPtr.Zero, null);
//调用引擎池逻辑！
var task = Task.Run(() =>
{
while (engine == IntPtr.Zero)
{
Task.Delay(10);
if (tokenSource.Token.IsCancellationRequested)
{
throw new Exception("等待引擎超时！");
}
engine = FaceProcess.GetEngine(FaceProcess.FaceEnginePoor);
}
using (var ms = new MemoryStream())
{
faceA.CopyTo(ms);
faceAResult = Arcsoft_Face_Action.TryExtractSingleFaceFeature(ms, 10, engine);
if (!faceAResult.Item1)
{
faceResult.Success = false;
faceResult.msg = faceAResult.Item3;
return;
}
}
using (var ms = new MemoryStream())
{
faceB.CopyTo(ms);
faceBResult = Arcsoft_Face_Action.TryExtractSingleFaceFeature(ms, 10, engine);
if (!faceBResult.Item1)
{
faceResult.Success = false;
faceResult.msg = faceBResult.Item3;
return;
}
}
float result = 0;
int compareStatus = Arcsoft_Face_3_0.ASFFaceFeatureCompare(engine, faceAResult.Item2, faceBResult.Item2, ref result, ASF_CompareModel.ASF_LIFE_PHOTO);
if (compareStatus == 0)
{
faceResult.Success = true;
faceResult.msg = $"相似度: {result} 接客引擎：{engine}";
}
else
{
faceResult.Success = false;
faceResult.msg = $"compareStatus error code = {compareStatus} 接客引擎：{engine}";
}
}, tokenSource.Token);
//响应时间控制
try
{
int timeLast = maxProcessTime * 1000;
while (timeLast > 0)
{
Task.Delay(100).Wait();
timeLast = timeLast - 100;
if (task.IsCompletedSuccessfully)
{
return Ok(JsonConvert.SerializeObject(faceResult));
}
}
tokenSource.Cancel();
return Ok(JsonConvert.SerializeObject(faceResult));
}
catch (Exception ex)
{
faceResult.Success = false;
faceResult.msg = ex.Message;
return Ok(JsonConvert.SerializeObject(faceResult));
}
finally
{
FaceProcess.PutEngine(FaceProcess.FaceEnginePoor, engine);
Marshal.FreeHGlobal(faceAResult.Item2);
Marshal.FreeHGlobal(faceBResult.Item2);
tokenSource.Dispose();
GC.Collect();
}
}
}
6. 结果演示：