#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); 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