OpenCV  3.2.0
Open Source Computer Vision
Intel® IPP Asynchronous C/C++ library in OpenCV

.2.0+dfsg_doc_tutorials_core_how_to_use_ippa_conversion_how_to_use_ippa_conversion

Goal

The tutorial demonstrates the Intel® IPP Asynchronous C/C++ library usage with OpenCV. The code example below illustrates implementation of the Sobel operation, accelerated with Intel® IPP Asynchronous C/C++ functions. In this code example, cv::hpp::getMat and cv::hpp::getHpp functions are used for data conversion between hppiMatrix and Mat matrices.

Code

You may also find the source code in the samples/cpp/tutorial_code/core/ippasync/ippasync_sample.cpp file of the OpenCV source library or download it from here.

#include <stdio.h>
#include "cvconfig.h"
using namespace std;
using namespace cv;
#ifdef HAVE_IPP_A
#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();
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;
}

Explanation

  1. Create parameters for OpenCV:
    VideoCapture cap;
    Mat image, gray, result;
    and IPP Async:
    hppiMatrix* src,* dst;
    hppAccel accel = 0;
    hppAccelType accelType;
    hppStatus sts;
    hppiVirtualMatrix * virtMatrix;
  2. Load input image or video. How to open and read video stream you can see in the Video Input with OpenCV and similarity measurement tutorial.
    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;
    }
  3. Create accelerator instance using hppCreateInstance:
    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");
  4. Create an array of virtual matrices using hppiCreateVirtualMatrices function.
    virtMatrix = hppiCreateVirtualMatrices(accel, 1);
  5. Prepare a matrix for input and output data:
    cap >> image;
    if(image.empty())
    break;
    cvtColor( image, gray, COLOR_BGR2GRAY );
    result.create( image.rows, image.cols, CV_8U);
  6. Convert Mat to hppiMatrix using cv::hpp::getHpp and call hppiSobel function.
    //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");
    We use hppiConvert because hppiSobel returns destination matrix with HPP_DATA_TYPE_16S data type for source matrix with HPP_DATA_TYPE_8U type. You should check hppStatus after each call IPP Async function.
  7. Create windows and show the images, the usual way.
    imshow("image", image);
    imshow("rez", result);
    waitKey(15);
  8. Delete hpp matrices.
    sts = hppiFreeMatrix(src);
    CHECK_DEL_STATUS(sts,"hppiFreeMatrix");
    sts = hppiFreeMatrix(dst);
    CHECK_DEL_STATUS(sts,"hppiFreeMatrix");
  9. Delete virtual matrices and accelerator instance.
    if (virtMatrix)
    {
    sts = hppiDeleteVirtualMatrices(accel, virtMatrix);
    CHECK_DEL_STATUS(sts,"hppiDeleteVirtualMatrices");
    }
    if (accel)
    {
    sts = hppDeleteInstance(accel);
    CHECK_DEL_STATUS(sts, "hppDeleteInstance");
    }

Result

After compiling the code above we can execute it giving an image or video path and accelerator type as an argument. For this tutorial we use baboon.png image as input. The result is below.

imgproc.hpp
cv::hpp::getHpp
hppiMatrix * getHpp(const Mat &src, hppAccel accel)
Create hppiMatrix from Mat.
Definition: ippasync.hpp:168
cv::cvtColor
void cvtColor(InputArray src, OutputArray dst, int code, int dstCn=0)
Converts an image from one color space to another.
cv::VideoCapture
Class for video capturing from video files, image sequences or cameras.
Definition: videoio.hpp:597
cv::waitKey
int waitKey(int delay=0)
Waits for a pressed key.
CV_8U
#define CV_8U
Definition: interface.h:67
highgui.hpp
cv::COLOR_BGR2GRAY
@ COLOR_BGR2GRAY
convert between RGB/BGR and grayscale, color conversions
Definition: imgproc.hpp:538
cv::getTickCount
int64 getTickCount()
Returns the number of ticks.
cv::VideoCapture::isOpened
virtual bool isOpened() const
Returns true if video capturing has been initialized already.
ippasync.hpp
cv::VideoCapture::open
virtual bool open(const String &filename)
Open video file or a capturing device or a IP video stream for video capturing.
cv::imshow
void imshow(const String &winname, InputArray mat)
Displays an image in the specified window.
cv::getTickFrequency
double getTickFrequency()
Returns the number of ticks per second.
cv::Mat
n-dimensional dense array class
Definition: mat.hpp:741
cv::CommandLineParser
Designed for command line parsing.
Definition: utility.hpp:735
cv
Definition: affine.hpp:52
cv::Mat::create
void create(int rows, int cols, int type)
Allocates new array data if needed.
utility.hpp