mirror of https://github.com/opencv/opencv.git
Open Source Computer Vision Library
https://opencv.org/
You can not select more than 25 topics
Topics must start with a letter or number, can include dashes ('-') and can be up to 35 characters long.
179 lines
4.7 KiB
179 lines
4.7 KiB
#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); |
|
} |
|
|
|
virtual 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)); |
|
} |
|
|
|
virtual 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 |