OpenCV中的英特尔®IPP异步C / C ++库

2018-08-31 10:49 更新

目标

本教程演示了使用OpenCV 的英特尔®IPP异步C / C ++库使用。下面的代码示例说明了使用英特尔®IPP异步C / C ++功能加速的Sobel操作的实现。在这个代码示例中，cv :: hpp :: getMat和cv :: hpp :: getHpp函数用于hppiMatrix和Mat矩阵之间的数据转换。

Code

您还可以在samples/cpp/tutorial_code/core/ippasync/ippasync_sample.cppOpenCV源文件的文件中找到源代码，或从这里下载。

#include <stdio.h>
#include "opencv2/core/utility.hpp"
#include "opencv2/imgproc.hpp"
#include "opencv2/highgui.hpp"
#include "cvconfig.h"
using namespace std;
using namespace cv;
#ifdef HAVE_IPP_A
#include "opencv2/core/ippasync.hpp"
#define CHECK_STATUS(STATUS, NAME)\
    if(STATUS!=HPP_STATUS_NO_ERROR){ printf("%s error %d\n", NAME, STATUS);\
    if (virtMatrix) {hppStatus delSts = hppiDeleteVirtualMatrices(accel, virtMatrix); CHECK_DEL_STATUS(delSts,"hppiDeleteVirtualMatrices");}\
    if (accel)      {hppStatus delSts = hppDeleteInstance(accel); CHECK_DEL_STATUS(delSts, "hppDeleteInstance");}\
    return -1;}
#define CHECK_DEL_STATUS(STATUS, NAME)\
    if(STATUS!=HPP_STATUS_NO_ERROR){ printf("%s error %d\n", NAME, STATUS); return -1;}
#endif
static void help()
{
 printf("\nThis program shows how to use the conversion for IPP Async.\n"
"This example uses the Sobel filter.\n"
"You can use cv::Sobel or hppiSobel.\n"
"Usage: \n"
"./ipp_async_sobel [--camera]=<use camera,if this key is present>, \n"
"                  [--file_name]=<path to movie or image file>\n"
"                  [--accel]=<accelerator type: auto (default), cpu, gpu>\n\n");
}
const char* keys =
{
    "{c  camera   |           | use camera or not}"
    "{fn file_name|../data/baboon.jpg | image file       }"
    "{a accel     |auto       | accelerator type: auto (default), cpu, gpu}"
};
//this is a sample for hppiSobel functions
int main(int argc, const char** argv)
{
    help();
    VideoCapture cap;
    CommandLineParser parser(argc, argv, keys);
    Mat image, gray, result;
#ifdef HAVE_IPP_A
    hppiMatrix* src,* dst;
    hppAccel accel = 0;
    hppAccelType accelType;
    hppStatus sts;
    hppiVirtualMatrix * virtMatrix;
    bool useCamera = parser.has("camera");
    string file = parser.get<string>("file_name");
    string sAccel = parser.get<string>("accel");
    parser.printMessage();
    if( useCamera )
    {
        printf("used camera\n");
        cap.open(0);
    }
    else
    {
        printf("used image %s\n", file.c_str());
        cap.open(file.c_str());
    }
    if( !cap.isOpened() )
    {
        printf("can not open camera or video file\n");
        return -1;
    }
    accelType = sAccel == "cpu" ? HPP_ACCEL_TYPE_CPU:
                sAccel == "gpu" ? HPP_ACCEL_TYPE_GPU:
                                  HPP_ACCEL_TYPE_ANY;
    //Create accelerator instance
    sts = hppCreateInstance(accelType, 0, &accel);
    CHECK_STATUS(sts, "hppCreateInstance");
    accelType = hppQueryAccelType(accel);
    sAccel = accelType == HPP_ACCEL_TYPE_CPU ? "cpu":
             accelType == HPP_ACCEL_TYPE_GPU ? "gpu":
             accelType == HPP_ACCEL_TYPE_GPU_VIA_DX9 ? "gpu dx9": "?";
    printf("accelType %s\n", sAccel.c_str());
    virtMatrix = hppiCreateVirtualMatrices(accel, 1);
    for(;;)
    {
        cap >> image;
        if(image.empty())
            break;
        cvtColor( image, gray, COLOR_BGR2GRAY );
        result.create( image.rows, image.cols, CV_8U);
        double execTime = (double)getTickCount();
        //convert Mat to hppiMatrix
        src = hpp::getHpp(gray,accel);
        dst = hpp::getHpp(result,accel);
        sts = hppiSobel(accel,src, HPP_MASK_SIZE_3X3,HPP_NORM_L1,virtMatrix[0]);
        CHECK_STATUS(sts,"hppiSobel");
        sts = hppiConvert(accel, virtMatrix[0], 0, HPP_RND_MODE_NEAR, dst, HPP_DATA_TYPE_8U);
        CHECK_STATUS(sts,"hppiConvert");
        // Wait for tasks to complete
        sts = hppWait(accel, HPP_TIME_OUT_INFINITE);
        CHECK_STATUS(sts, "hppWait");
        execTime = ((double)getTickCount() - execTime)*1000./getTickFrequency();
        printf("Time : %0.3fms\n", execTime);
        imshow("image", image);
        imshow("rez", result);
        waitKey(15);
        sts =  hppiFreeMatrix(src);
        CHECK_DEL_STATUS(sts,"hppiFreeMatrix");
        sts =  hppiFreeMatrix(dst);
        CHECK_DEL_STATUS(sts,"hppiFreeMatrix");
    }
    if (!useCamera)
        waitKey(0);
    if (virtMatrix)
    {
        sts = hppiDeleteVirtualMatrices(accel, virtMatrix);
        CHECK_DEL_STATUS(sts,"hppiDeleteVirtualMatrices");
    }
    if (accel)
    {
        sts = hppDeleteInstance(accel);
        CHECK_DEL_STATUS(sts, "hppDeleteInstance");
    }
    printf("SUCCESS\n");
#else
    printf("IPP Async not supported\n");
#endif
    return 0;
}

说明

为OpenCV创建参数：

VideoCapture cap;
Mat image, gray, result;

和IPP异步：

hppiMatrix* src,* dst;
hppAccel accel = 0;
hppAccelType accelType;
hppStatus sts;
hppiVirtualMatrix * virtMatrix;

加载输入图像或视频。如何打开和读取视频流，您可以在视频输入中使用OpenCV和相似度测量教程。

if( useCamera )
{
   printf("used camera\n");
   cap.open(0);
}
else
{
   printf("used image %s\n", file.c_str());
   cap.open(file.c_str());
}
if( !cap.isOpened() )
{
   printf("can not open camera or video file\n");
   return -1;
}

使用hppCreateInstance创建加速器实例：

accelType = sAccel == "cpu" ? HPP_ACCEL_TYPE_CPU:
            sAccel == "gpu" ? HPP_ACCEL_TYPE_GPU:
                              HPP_ACCEL_TYPE_ANY;
//Create accelerator instance
sts = hppCreateInstance(accelType, 0, &accel);
CHECK_STATUS(sts, "hppCreateInstance");

使用hppiCreateVirtualMatrices函数创建一个虚拟矩阵数组。

virtMatrix = hppiCreateVirtualMatrices（accel，1）;

为输入和输出数据准备一个矩阵：

cap >> image;
if(image.empty())
   break;
cvtColor( image, gray, COLOR_BGR2GRAY );
result.create( image.rows, image.cols, CV_8U);

使用cv :: hpp :: getHpp将Mat转换为hppiMatrix并调用hppiSobel函数。

//convert Mat to hppiMatrix
src = getHpp(gray, accel);
dst = getHpp(result, accel);
sts = hppiSobel(accel,src, HPP_MASK_SIZE_3X3,HPP_NORM_L1,virtMatrix[0]);
CHECK_STATUS(sts,"hppiSobel");
sts = hppiConvert(accel, virtMatrix[0], 0, HPP_RND_MODE_NEAR, dst, HPP_DATA_TYPE_8U);
CHECK_STATUS(sts,"hppiConvert");
// Wait for tasks to complete
sts = hppWait(accel, HPP_TIME_OUT_INFINITE);
CHECK_STATUS(sts, "hppWait");

我们使用hppiConvert，因为hppiSobel返回具有HPP_DATA_TYPE_8U类型的源矩阵的HPP_DATA_TYPE_16S数据类型的目标矩阵。每次调用IPP异步函数后，应该检查hppStatus。

创建窗口并显示图像，通常的方式。

imshow("image", image);
imshow("rez", result);
waitKey(15);

删除hpp矩阵。

sts = hppiFreeMatrix（src）;
CHECK_DEL_STATUS（sts，“hppiFreeMatrix”）;
sts = hppiFreeMatrix（dst）;
CHECK_DEL_STATUS（sts，“hppiFreeMatrix”）;

删除虚拟矩阵和加速器实例。

if (virtMatrix)
{
   sts = hppiDeleteVirtualMatrices(accel, virtMatrix);
   CHECK_DEL_STATUS(sts,"hppiDeleteVirtualMatrices");
}
if (accel)
{
   sts = hppDeleteInstance(accel);
   CHECK_DEL_STATUS(sts, "hppDeleteInstance");
}

结果

在编译上面的代码之后，我们可以执行它，给出图像或视频路径和加速器类型作为参数。对于本教程，我们使用baboon.png图像作为输入。结果如下。

OpenCV中的英特尔®IPP异步C / C ++库

以上内容是否对您有帮助：

← 与OpenCV 1的互操作性

如何使用OpenCV parallel_for_来并行化代码 →

写笔记

我要补充