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Open Source Computer Vision Library
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168 lines
4.3 KiB
168 lines
4.3 KiB
#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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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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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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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 |