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