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目前在人脸识别领域中，网络摄像头的使用很普遍，但接入网络摄像头和人脸识别 SDK 有一定门槛，在此篇中介绍过虹软人脸识别 SDK 的接入流程，本文着重介绍网络摄像头获取视频流并处理的流程(红色框内)，以下内容仅供参考。
市面上目前有很多款网络摄像头，以海康摄像头为例。海康 SDK 包含很多接口，接入有一定难度，这里只介绍获取视频帧相关的接口。
1. 海康 SDK 接入基本流程
a. 初始化并登录验证
NET_DVR_Init();
NET_DVR_DEVICEINFO_V30 struDeviceInfo = {0};
long lUserID = NET_DVR_Login_V30(m_cameraIp, m_cameraPort,
m_cameraUser, m_cameraPwd, &struDeviceInfo);
if (lUserID < 0)
{NET_DVR_Cleanup();
return false;
}
b. 创建线程并注册回调函数
thread videoThread(&HCNetCamera::getCameraPreview, this);
videoThread.detach();
bool HCNetCamera::getCameraPreview()
{
NET_DVR_CLIENTINFO ClientInfo;
ClientInfo.lChannel = 1; //Channel number 设备通道号
ClientInfo.hPlayWnd = NULL; // 窗口为空，设备 SDK 不解码只取流
ClientInfo.lLinkMode = 0; //Main Stream
ClientInfo.sMultiCastIP = NULL;
// 预览取流
g_realHandle = NET_DVR_RealPlay_V30(g_cameraUserId, &ClientInfo, fRealDataCallBack, NULL, TRUE);
if (g_realHandle < 0)
{qDebug() << "NET_DVR_RealPlay_V30 failed! Error number:" << NET_DVR_GetLastError();
return false;
}
return true;
}
c. 使用回调接口，获取实时的视频帧数据
void CALLBACK fRealDataCallBack(LONG lRealHandle, DWORD dwDataType, BYTE *pBuffer, DWORD dwBufSize, void *pUser)
{UNREFERENCED_PARAMETER(lRealHandle);
UNREFERENCED_PARAMETER(pUser);
DWORD dRet = 0;
BOOL inData = FALSE;
switch (dwDataType)
{
case NET_DVR_SYSHEAD:
if (g_cameraPort >= 0)
{break; // 同一路码流不需要多次调用开流接口}
if (!PlayM4_GetPort(&g_cameraPort))
{break;}
if (!PlayM4_OpenStream(g_cameraPort, pBuffer, dwBufSize, 1024 * 1024))
{dRet = PlayM4_GetLastError(g_cameraPort);
break;
}
// 设置解码回调函数
if (!PlayM4_SetDecCallBack(g_cameraPort, DecCBFun))
{dRet = PlayM4_GetLastError(g_cameraPort);
break;
}
// 打开视频解码
if (!PlayM4_Play(g_cameraPort, NULL))
{dRet = PlayM4_GetLastError(g_cameraPort);
break;
}
dRet = PlayM4_GetLastError(g_cameraPort);
break;
case NET_DVR_STREAMDATA: // 视频流数据
default:
inData = PlayM4_InputData(g_cameraPort, pBuffer, dwBufSize);
while (!inData)
{Sleep(10);
inData = PlayM4_InputData(g_cameraPort, pBuffer, dwBufSize);
dRet = PlayM4_GetLastError(g_cameraPort);
OutputDebugString(L"PlayM4_InputData failed \n");
}
break;
}
}
// 解码回调 视频为 YUV 数据(YV12)
void CALLBACK DecCBFun(long port, char * pBuf, long nSize, FRAME_INFO * pFrameInfo, long nReserved1, long nReserved2)
{UNREFERENCED_PARAMETER(nReserved1);
UNREFERENCED_PARAMETER(nReserved2);
UNREFERENCED_PARAMETER(nSize);
UNREFERENCED_PARAMETER(port);
// 图像格式转换
if (pFrameInfo->nType == T_YV12)
{
{lock_guard<mutex> locker(g_CameraMutex);
Utils_ns::ImageUtils_ns::YV12ToBGR24_FFMPEG((unsigned char*)pBuf, (unsigned char*)g_curRGBImage->imageData,
pFrameInfo->nWidth, pFrameInfo->nHeight);// 得到全部 RGB 图像
}
}
}
d. 应用层获取视频帧，这里为了简化操作，只获取了当前帧；大家也可以使用线程安全队列来处理
int HCNetCamera::getFrame(Mat& image)
{lock_guard<mutex> locker(g_CameraMutex);
if (g_curRGBImage && g_curRGBImage->imageData)
{
image = g_curRGBImage;
return 0;
}
return -1;
}
// 以下是线程函数的一部分，主要是取帧，然后进行人脸检测
{lock_guard<std::mutex> locker(g_CameraMutex);
int ret = m_camera->getFrame(curFrame);
if (ret == -1)
{continue;}
}
ftProcessor->faceDetect(curFrame);
2. 基本图像格式转换
目前虹软 SDK 支持以下几种图像数据格式：
在实际开发过程中一般使用 opencv，opencv 默认的图像数据格式是 BGR24，而我使用的海康摄像头视频编码格式是 H264，视频帧数据格式是 YV12，因此需要将 YV12 转换为 BGR24，同时也会说明下怎么转换为虹软 SDK 支持的其它格式，主要参考了[2]，以下的代码仅供参考。
a.YV12 To BGR24
void yv12ToBGR24(unsigned char* yv12, unsigned char* bgr24, int width, int height)
{
unsigned char* y_yv12 = yv12;
unsigned char* v_yv12 = yv12 + width*height;
unsigned char* u_yv12 = yv12 + width*height + width*height / 4;
unsigned char* b = bgr24;
unsigned char* g = bgr24 + 1;
unsigned char* r = bgr24 + 2;
int yIndex, uIndex, vIndex;
for (int i = 0; i < height; ++i)
{for (int j = 0; j < width; ++j)
{
yIndex = i * width + j;
vIndex = (i / 2) * (width / 2) + (j / 2);
uIndex = vIndex;
*b = (unsigned char)(y_yv12[yIndex] + 1.732446 * (u_yv12[vIndex] - 128));
*g = (unsigned char)(y_yv12[yIndex] - 0.698001 * (u_yv12[uIndex] - 128) - 0.703125 * (v_yv12[vIndex] - 128));
*r = (unsigned char)(y_yv12[yIndex] + 1.370705 * (v_yv12[uIndex] - 128));
b += 3;
g += 3;
r += 3;
}
}}
b.YV12 To I420
void yv12ToI420(unsigned char yv12, unsigned char i420, int width, int height)
{
unsigned char* y_yv12 = yv12;
unsigned char* v_yv12 = yv12 + width*height;
unsigned char* u_yv12 = yv12 + width*height + width*height / 4;
unsigned char* y_i420 = i420;
unsigned char* u_i420 = i420 + width*height;
unsigned char* v_i420 = i420 + width*height + width*height / 4;
memcpy(i420, yv12, width*height);
memcpy(v_i420, v_yv12, width*height / 4);
memcpy(u_i420, u_yv12, width*height / 4);
}
c.YV12 To NV21
void yv12ToNV21(unsigned char yv12, unsigned char nv21, int width, int height)
{
unsigned char* y_yv12 = yv12;
unsigned char* v_yv12 = yv12 + width*height;
unsigned char* u_yv12 = yv12 + width*height + width*height / 4;
unsigned char* y_nv21 = nv21;
unsigned char* v_nv21 = nv21 + width*height;
unsigned char* u_nv21 = nv21 + width*height + 1;
memcpy(nv21, yv12, width*height);
for (int i = 0; i < width*height / 4; ++i)
{
*v_nv21 = *v_yv12;
*u_nv21 = *u_yv12;
v_nv21 += 2;
u_nv21 += 2;
++v_yv12;
++u_yv12;
}}
d.YV12 To NV12
void yv12ToNV12(unsigned char yv12, unsigned char nv12, int width, int height)
{
unsigned char* y_yv12 = yv12;
unsigned char* v_yv12 = yv12 + width*height;
unsigned char* u_yv12 = yv12 + width*height + width*height / 4;
unsigned char* y_nv12 = nv12;
unsigned char* u_nv12 = nv12 + width*height;
unsigned char* v_nv12 = nv12 + width*height + 1;
memcpy(nv12, yv12, width*height);
for (int i = 0; i < width*height / 4; ++i)
{
*v_nv12 = *v_yv12;
*u_nv12 = *u_yv12;
v_nv12 += 2;
u_nv12 += 2;
++v_yv12;
++u_yv12;
}}
e.YV12 To YUYV
void yv12ToYUYV(unsigned char yv12, unsigned char yuyv, int width, int height)
{
unsigned char* y_yv12 = yv12;
unsigned char* v_yv12 = yv12 + width*height;
unsigned char* u_yv12 = yv12 + width*height + width*height / 4;
unsigned char* y_yuyv = yuyv;
unsigned char* u_yuyv = yuyv + 1;
unsigned char* v_yuyv = yuyv + 3;
for (int i = 0; i < width; ++i)
{for (int j = 0; j < height; ++j)
{
*y_yuyv = *y_yv12;
y_yuyv += 2;
++y_yv12;
}
}
for (int j = 0; j < height / 2; ++j)
{for (int i = 0; i < width / 2; ++i)
{
*u_yuyv = *u_yv12;
*(u_yuyv + width * 2) = *u_yv12;
u_yuyv += 4;
++u_yv12;
*v_yuyv = *v_yv12;
*(v_yuyv + width * 2) = *v_yv12;
v_yuyv += 4;
++v_yv12;
}
u_yuyv += width * 2;
v_yuyv += width * 2;
}}
参考：
[1] 虹软 AI 人脸识别 SDK 接入 — 性能优化篇（多线程）
[2] 图像实战 – 图像格式转换
[3] 微软官方解析图像格式
[4] 一文读懂 YUV 的采样与格式
正文完
