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#include "test_precomp.hpp"
#include "opencv2/ts/ocl_test.hpp"
#ifdef HAVE_IPP_A
#include "opencv2/core/ippasync.hpp"
using namespace cv;
using namespace std;
using namespace cvtest;
namespace cvtest {
namespace ocl {
PARAM_TEST_CASE(IPPAsync, MatDepth, Channels, hppAccelType)
{
int type;
int cn;
int depth;
hppAccelType accelType;
Mat matrix, result;
hppiMatrix * hppMat;
hppAccel accel;
hppiVirtualMatrix * virtMatrix;
hppStatus sts;
virtual void SetUp()
{
type = CV_MAKE_TYPE(GET_PARAM(0), GET_PARAM(1));
depth = GET_PARAM(0);
cn = GET_PARAM(1);
accelType = GET_PARAM(2);
}
void generateTestData()
{
Size matrix_Size = randomSize(2, 100);
const double upValue = 100;
matrix = randomMat(matrix_Size, type, -upValue, upValue);
}
void Near(double threshold = 0.0)
{
EXPECT_MAT_NEAR(matrix, result, threshold);
}
};
TEST_P(IPPAsync, accuracy)
{
sts = hppCreateInstance(accelType, 0, &accel);
if (sts!=HPP_STATUS_NO_ERROR) printf("hppStatus = %d\n",sts);
CV_Assert(sts==HPP_STATUS_NO_ERROR);
virtMatrix = hppiCreateVirtualMatrices(accel, 2);
for (int j = 0; j < test_loop_times; j++)
{
generateTestData();
hppMat = hpp::getHpp(matrix,accel);
hppScalar a = 3;
sts = hppiAddC(accel, hppMat, a, 0, virtMatrix[0]);
CV_Assert(sts==HPP_STATUS_NO_ERROR);
sts = hppiSubC(accel, virtMatrix[0], a, 0, virtMatrix[1]);
CV_Assert(sts==HPP_STATUS_NO_ERROR);
sts = hppWait(accel, HPP_TIME_OUT_INFINITE);
CV_Assert(sts==HPP_STATUS_NO_ERROR);
result = hpp::getMat(virtMatrix[1], accel, cn);
Near(5.0e-6);
sts = hppiFreeMatrix(hppMat);
CV_Assert(sts==HPP_STATUS_NO_ERROR);
}
sts = hppiDeleteVirtualMatrices(accel, virtMatrix);
CV_Assert(sts==HPP_STATUS_NO_ERROR);
sts = hppDeleteInstance(accel);
CV_Assert(sts==HPP_STATUS_NO_ERROR);
}
PARAM_TEST_CASE(IPPAsyncShared, Channels, hppAccelType)
{
int cn;
int type;
hppAccelType accelType;
Mat matrix, result;
hppiMatrix* hppMat;
hppAccel accel;
hppiVirtualMatrix * virtMatrix;
hppStatus sts;
virtual void SetUp()
{
cn = GET_PARAM(0);
accelType = GET_PARAM(1);
type=CV_MAKE_TYPE(CV_8U, GET_PARAM(0));
}
void generateTestData()
{
Size matrix_Size = randomSize(2, 100);
hpp32u pitch, size;
const int upValue = 100;
sts = hppQueryMatrixAllocParams(accel, (hpp32u)(matrix_Size.width*cn), (hpp32u)matrix_Size.height, HPP_DATA_TYPE_8U, &pitch, &size);
if (pitch!=0 && size!=0)
{
uchar *pData = (uchar*)_aligned_malloc(size, 4096);
for (int j=0; j<matrix_Size.height; j++)
for(int i=0; i<matrix_Size.width*cn; i++)
pData[i+j*pitch] = rand()%upValue;
matrix = Mat(matrix_Size.height, matrix_Size.width, type, pData, pitch);
}
matrix = randomMat(matrix_Size, type, 0, upValue);
}
void Near(double threshold = 0.0)
{
EXPECT_MAT_NEAR(matrix, result, threshold);
}
};
TEST_P(IPPAsyncShared, accuracy)
{
sts = hppCreateInstance(accelType, 0, &accel);
if (sts!=HPP_STATUS_NO_ERROR) printf("hppStatus = %d\n",sts);
CV_Assert(sts==HPP_STATUS_NO_ERROR);
virtMatrix = hppiCreateVirtualMatrices(accel, 2);
for (int j = 0; j < test_loop_times; j++)
{
generateTestData();
hppMat = hpp::getHpp(matrix,accel);
hppScalar a = 3;
sts = hppiAddC(accel, hppMat, a, 0, virtMatrix[0]);
CV_Assert(sts==HPP_STATUS_NO_ERROR);
sts = hppiSubC(accel, virtMatrix[0], a, 0, virtMatrix[1]);
CV_Assert(sts==HPP_STATUS_NO_ERROR);
sts = hppWait(accel, HPP_TIME_OUT_INFINITE);
CV_Assert(sts==HPP_STATUS_NO_ERROR);
result = hpp::getMat(virtMatrix[1], accel, cn);
Near(0);
sts = hppiFreeMatrix(hppMat);
CV_Assert(sts==HPP_STATUS_NO_ERROR);
}
sts = hppiDeleteVirtualMatrices(accel, virtMatrix);
CV_Assert(sts==HPP_STATUS_NO_ERROR);
sts = hppDeleteInstance(accel);
CV_Assert(sts==HPP_STATUS_NO_ERROR);
}
INSTANTIATE_TEST_CASE_P(IppATest, IPPAsyncShared, Combine(Values(1, 2, 3, 4),
Values( HPP_ACCEL_TYPE_CPU, HPP_ACCEL_TYPE_GPU)));
INSTANTIATE_TEST_CASE_P(IppATest, IPPAsync, Combine(Values(CV_8U, CV_16U, CV_16S, CV_32F),
Values(1, 2, 3, 4),
Values( HPP_ACCEL_TYPE_CPU, HPP_ACCEL_TYPE_GPU)));
}
}
#endif
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