/*M/////////////////////////////////////////////////////////////////////////////////////// // // IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING. // // By downloading, copying, installing or using the software you agree to this license. // If you do not agree to this license, do not download, install, // copy or use the software. // // // License Agreement // For Open Source Computer Vision Library // // Copyright (C) 2010-2012, Institute Of Software Chinese Academy Of Science, all rights reserved. // Copyright (C) 2010-2012, Advanced Micro Devices, Inc., all rights reserved. // Copyright (C) 2010-2012, Multicoreware, Inc., all rights reserved. // Third party copyrights are property of their respective owners. // // @Authors // Niko Li, newlife20080214@gmail.com // Jia Haipeng, jiahaipeng95@gmail.com // Shengen Yan, yanshengen@gmail.com // Jiang Liyuan, lyuan001.good@163.com // Rock Li, Rock.Li@amd.com // Wu Zailong, bullet@yeah.net // Xu Pang, pangxu010@163.com // Sen Liu, swjtuls1987@126.com // // Redistribution and use in source and binary forms, with or without modification, // are permitted provided that the following conditions are met: // // * Redistribution's of source code must retain the above copyright notice, // this list of conditions and the following disclaimer. // // * Redistribution's in binary form must reproduce the above copyright notice, // this list of conditions and the following disclaimer in the documentation // and/or other materials provided with the distribution. // // * The name of the copyright holders may not be used to endorse or promote products // derived from this software without specific prior written permission. // // This software is provided by the copyright holders and contributors "as is" and // any express or implied warranties, including, but not limited to, the implied // warranties of merchantability and fitness for a particular purpose are disclaimed. // In no event shall the Intel Corporation or contributors be liable for any direct, // indirect, incidental, special, exemplary, or consequential damages // (including, but not limited to, procurement of substitute goods or services; // loss of use, data, or profits; or business interruption) however caused // and on any theory of liability, whether in contract, strict liability, // or tort (including negligence or otherwise) arising in any way out of // the use of this software, even if advised of the possibility of such damage. // //M*/ #include "test_precomp.hpp" #ifdef HAVE_OPENCL using namespace testing; using namespace std; using namespace cv; /////////////////////////////////////////////////////////////////////////////// PARAM_TEST_CASE(ImgprocTestBase, MatType, int, // blockSize int, // border type bool) // roi or not { int type, borderType, blockSize; bool useRoi; Mat src, dst_whole, src_roi, dst_roi; ocl::oclMat gsrc_whole, gsrc_roi, gdst_whole, gdst_roi; virtual void SetUp() { type = GET_PARAM(0); blockSize = GET_PARAM(1); borderType = GET_PARAM(2); useRoi = GET_PARAM(3); } virtual void random_roi() { Size roiSize = randomSize(1, MAX_VALUE); Border srcBorder = randomBorder(0, useRoi ? MAX_VALUE : 0); randomSubMat(src, src_roi, roiSize, srcBorder, type, 5, 256); Border dstBorder = randomBorder(0, useRoi ? MAX_VALUE : 0); randomSubMat(dst_whole, dst_roi, roiSize, dstBorder, type, 5, 16); generateOclMat(gsrc_whole, gsrc_roi, src, roiSize, srcBorder); generateOclMat(gdst_whole, gdst_roi, dst_whole, roiSize, dstBorder); } void Near(double threshold = 0.0) { Mat roi, whole; gdst_whole.download(whole); gdst_roi.download(roi); EXPECT_MAT_NEAR(dst_whole, whole, threshold); EXPECT_MAT_NEAR(dst_roi, roi, threshold); } }; ////////////////////////////////copyMakeBorder//////////////////////////////////////////// PARAM_TEST_CASE(CopyMakeBorder, MatDepth, // depth Channels, // channels bool, // isolated or not Border, // border type bool) // roi or not { int type, borderType; bool useRoi; Border border; Scalar val; Mat src, dst_whole, src_roi, dst_roi; ocl::oclMat gsrc_whole, gsrc_roi, gdst_whole, gdst_roi; virtual void SetUp() { type = CV_MAKE_TYPE(GET_PARAM(0), GET_PARAM(1)); borderType = GET_PARAM(3); if (GET_PARAM(2)) borderType |= BORDER_ISOLATED; useRoi = GET_PARAM(4); } void random_roi() { Size roiSize = randomSize(1, MAX_VALUE); Border srcBorder = randomBorder(0, useRoi ? MAX_VALUE : 0); randomSubMat(src, src_roi, roiSize, srcBorder, type, 5, 256); Border dstBorder = randomBorder(0, useRoi ? MAX_VALUE : 0); randomSubMat(dst_whole, dst_roi, roiSize, dstBorder, type, 5, 16); generateOclMat(gsrc_whole, gsrc_roi, src, roiSize, srcBorder); generateOclMat(gdst_whole, gdst_roi, dst_whole, roiSize, dstBorder); border = randomBorder(0, MAX_VALUE << 2); val = randomScalar(-MAX_VALUE, MAX_VALUE); } void Near(double threshold = 0.0) { Mat whole, roi; gdst_whole.download(whole); gdst_roi.download(roi); EXPECT_MAT_NEAR(dst_whole, whole, threshold); EXPECT_MAT_NEAR(dst_roi, roi, threshold); } }; OCL_TEST_P(CopyMakeBorder, Mat) { for (int i = 0; i < LOOP_TIMES; ++i) { random_roi(); cv::copyMakeBorder(src_roi, dst_roi, border.top, border.bot, border.lef, border.rig, borderType, val); ocl::copyMakeBorder(gsrc_roi, gdst_roi, border.top, border.bot, border.lef, border.rig, borderType, val); Near(); } } ////////////////////////////////equalizeHist////////////////////////////////////////////// typedef ImgprocTestBase EqualizeHist; OCL_TEST_P(EqualizeHist, Mat) { for (int j = 0; j < LOOP_TIMES; j++) { random_roi(); equalizeHist(src_roi, dst_roi); ocl::equalizeHist(gsrc_roi, gdst_roi); Near(1.1); } } ////////////////////////////////cornerMinEigenVal////////////////////////////////////////// struct CornerTestBase : public ImgprocTestBase { virtual void random_roi() { Mat image = readImageType("gpu/stereobm/aloe-L.png", type); ASSERT_FALSE(image.empty()); bool isFP = CV_MAT_DEPTH(type) >= CV_32F; float val = 255.0f; if (isFP) { image.convertTo(image, -1, 1.0 / 255); val /= 255.0f; } Size roiSize = image.size(); Border srcBorder = randomBorder(0, useRoi ? MAX_VALUE : 0); Size wholeSize = Size(roiSize.width + srcBorder.lef + srcBorder.rig, roiSize.height + srcBorder.top + srcBorder.bot); src = randomMat(wholeSize, type, -val, val, false); src_roi = src(Rect(srcBorder.lef, srcBorder.top, roiSize.width, roiSize.height)); image.copyTo(src_roi); Border dstBorder = randomBorder(0, useRoi ? MAX_VALUE : 0); randomSubMat(dst_whole, dst_roi, roiSize, dstBorder, CV_32FC1, 5, 16); generateOclMat(gsrc_whole, gsrc_roi, src, roiSize, srcBorder); generateOclMat(gdst_whole, gdst_roi, dst_whole, roiSize, dstBorder); } }; typedef CornerTestBase CornerMinEigenVal; OCL_TEST_P(CornerMinEigenVal, Mat) { for (int j = 0; j < LOOP_TIMES; j++) { random_roi(); int apertureSize = 3; cornerMinEigenVal(src_roi, dst_roi, blockSize, apertureSize, borderType); ocl::cornerMinEigenVal(gsrc_roi, gdst_roi, blockSize, apertureSize, borderType); Near(1e-6); } } ////////////////////////////////cornerHarris////////////////////////////////////////// typedef CornerTestBase CornerHarris; OCL_TEST_P(CornerHarris, Mat) { for (int j = 0; j < LOOP_TIMES; j++) { random_roi(); int apertureSize = 3; double k = randomDouble(0.01, 0.9); cornerHarris(src_roi, dst_roi, blockSize, apertureSize, k, borderType); ocl::cornerHarris(gsrc_roi, gdst_roi, blockSize, apertureSize, k, borderType); Near(1e-6); } } //////////////////////////////////integral///////////////////////////////////////////////// typedef ImgprocTestBase Integral; OCL_TEST_P(Integral, Mat1) { for (int j = 0; j < LOOP_TIMES; j++) { random_roi(); ocl::integral(gsrc_roi, gdst_roi); integral(src_roi, dst_roi); Near(); } } // TODO wrong output type OCL_TEST_P(Integral, DISABLED_Mat2) { Mat dst1; ocl::oclMat gdst1; for (int j = 0; j < LOOP_TIMES; j++) { random_roi(); integral(src_roi, dst1, dst_roi); ocl::integral(gsrc_roi, gdst1, gdst_roi); Near(); } } /////////////////////////////////////////////////////////////////////////////////////////////////// //// threshold struct Threshold : public ImgprocTestBase { int thresholdType; virtual void SetUp() { type = GET_PARAM(0); blockSize = GET_PARAM(1); thresholdType = GET_PARAM(2); useRoi = GET_PARAM(3); } }; OCL_TEST_P(Threshold, Mat) { for (int j = 0; j < LOOP_TIMES; j++) { random_roi(); double maxVal = randomDouble(20.0, 127.0); double thresh = randomDouble(0.0, maxVal); threshold(src_roi, dst_roi, thresh, maxVal, thresholdType); ocl::threshold(gsrc_roi, gdst_roi, thresh, maxVal, thresholdType); Near(1); } } ///////////////////////////////////////////////////////////////////////////////////////// // calcHist static void calcHistGold(const Mat &src, Mat &hist) { hist = Mat(1, 256, CV_32SC1, Scalar::all(0)); int * const hist_row = hist.ptr(); for (int y = 0; y < src.rows; ++y) { const uchar * const src_row = src.ptr(y); for (int x = 0; x < src.cols; ++x) ++hist_row[src_row[x]]; } } typedef ImgprocTestBase CalcHist; OCL_TEST_P(CalcHist, Mat) { for (int j = 0; j < LOOP_TIMES; j++) { random_roi(); calcHistGold(src_roi, dst_roi); ocl::calcHist(gsrc_roi, gdst_roi); Near(); } } ///////////////////////////////////////////////////////////////////////////////////////////////////////// //// CLAHE PARAM_TEST_CASE(CLAHETest, Size, double, bool) { Size gridSize; double clipLimit; bool useRoi; Mat src, dst_whole, src_roi, dst_roi; ocl::oclMat gsrc_whole, gsrc_roi, gdst_whole, gdst_roi; virtual void SetUp() { gridSize = GET_PARAM(0); clipLimit = GET_PARAM(1); useRoi = GET_PARAM(2); } void random_roi() { Size roiSize = randomSize(std::max(gridSize.height, gridSize.width), MAX_VALUE); Border srcBorder = randomBorder(0, useRoi ? MAX_VALUE : 0); randomSubMat(src, src_roi, roiSize, srcBorder, CV_8UC1, 5, 256); Border dstBorder = randomBorder(0, useRoi ? MAX_VALUE : 0); randomSubMat(dst_whole, dst_roi, roiSize, dstBorder, CV_8UC1, 5, 16); generateOclMat(gsrc_whole, gsrc_roi, src, roiSize, srcBorder); generateOclMat(gdst_whole, gdst_roi, dst_whole, roiSize, dstBorder); } void Near(double threshold = 0.0) { Mat whole, roi; gdst_whole.download(whole); gdst_roi.download(roi); EXPECT_MAT_NEAR(dst_whole, whole, threshold); EXPECT_MAT_NEAR(dst_roi, roi, threshold); } }; OCL_TEST_P(CLAHETest, Accuracy) { for (int i = 0; i < LOOP_TIMES; ++i) { random_roi(); Ptr clahe = ocl::createCLAHE(clipLimit, gridSize); clahe->apply(gsrc_roi, gdst_roi); Ptr clahe_gold = createCLAHE(clipLimit, gridSize); clahe_gold->apply(src_roi, dst_roi); Near(1.0); } } /////////////////////////////Convolve////////////////////////////////// static void convolve_gold(const Mat & src, const Mat & kernel, Mat & dst) { for (int i = 0; i < src.rows; i++) { float * const dstptr = dst.ptr(i); for (int j = 0; j < src.cols; j++) { float temp = 0; for (int m = 0; m < kernel.rows; m++) { const float * const kptr = kernel.ptr(m); for (int n = 0; n < kernel.cols; n++) { int r = clipInt(i - kernel.rows / 2 + m, 0, src.rows - 1); int c = clipInt(j - kernel.cols / 2 + n, 0, src.cols - 1); temp += src.ptr(r)[c] * kptr[n]; } } dstptr[j] = temp; } } } typedef ImgprocTestBase Convolve; OCL_TEST_P(Convolve, Mat) { Mat kernel, kernel_roi; ocl::oclMat gkernel, gkernel_roi; const Size roiSize(7, 7); for (int j = 0; j < LOOP_TIMES; j++) { random_roi(); Border kernelBorder = randomBorder(0, useRoi ? MAX_VALUE : 0); randomSubMat(kernel, kernel_roi, roiSize, kernelBorder, type, 5, 16); generateOclMat(gkernel, gkernel_roi, kernel, roiSize, kernelBorder); convolve_gold(src_roi, kernel_roi, dst_roi); ocl::convolve(gsrc_roi, gkernel_roi, gdst_roi); Near(1); } } ////////////////////////////////// ColumnSum ////////////////////////////////////// static void columnSum_gold(const Mat & src, Mat & dst) { float * prevdptr = dst.ptr(0); const float * sptr = src.ptr(0); for (int x = 0; x < src.cols; ++x) prevdptr[x] = sptr[x]; for (int y = 1; y < src.rows; ++y) { sptr = src.ptr(y); float * const dptr = dst.ptr(y); for (int x = 0; x < src.cols; ++x) dptr[x] = prevdptr[x] + sptr[x]; prevdptr = dptr; } } typedef ImgprocTestBase ColumnSum; OCL_TEST_P(ColumnSum, Accuracy) { for (int i = 0; i < LOOP_TIMES; ++i) { random_roi(); columnSum_gold(src_roi, dst_roi); ocl::columnSum(gsrc_roi, gdst_roi); Near(1e-5); } } ///////////////////////////////////////////////////////////////////////////////////// INSTANTIATE_TEST_CASE_P(Imgproc, EqualizeHist, Combine( Values((MatType)CV_8UC1), Values(0), // not used Values(0), // not used Bool())); INSTANTIATE_TEST_CASE_P(Imgproc, CornerMinEigenVal, Combine( Values((MatType)CV_8UC1, (MatType)CV_32FC1), Values(3, 5), Values((int)BORDER_CONSTANT, (int)BORDER_REPLICATE, (int)BORDER_REFLECT, (int)BORDER_REFLECT101), Bool())); INSTANTIATE_TEST_CASE_P(Imgproc, CornerHarris, Combine( Values((MatType)CV_8UC1, CV_32FC1), Values(3, 5), Values( (int)BORDER_CONSTANT, (int)BORDER_REPLICATE, (int)BORDER_REFLECT, (int)BORDER_REFLECT_101), Bool())); INSTANTIATE_TEST_CASE_P(Imgproc, Integral, Combine( Values((MatType)CV_8UC1), // TODO does not work with CV_32F, CV_64F Values(0), // not used Values(0), // not used Bool())); INSTANTIATE_TEST_CASE_P(Imgproc, Threshold, Combine( Values(CV_8UC1, CV_8UC2, CV_8UC3, CV_8UC4, CV_16SC1, CV_16SC2, CV_16SC3, CV_16SC4, CV_32FC1, CV_32FC2, CV_32FC3, CV_32FC4), Values(0), Values(ThreshOp(THRESH_BINARY), ThreshOp(THRESH_BINARY_INV), ThreshOp(THRESH_TRUNC), ThreshOp(THRESH_TOZERO), ThreshOp(THRESH_TOZERO_INV)), Bool())); INSTANTIATE_TEST_CASE_P(Imgproc, CalcHist, Combine( Values((MatType)CV_8UC1), Values(0), // not used Values(0), // not used Bool())); INSTANTIATE_TEST_CASE_P(Imgproc, CLAHETest, Combine( Values(Size(4, 4), Size(32, 8), Size(8, 64)), Values(0.0, 10.0, 62.0, 300.0), Bool())); INSTANTIATE_TEST_CASE_P(Imgproc, Convolve, Combine( Values((MatType)CV_32FC1), Values(0), // not used Values(0), // not used Bool())); INSTANTIATE_TEST_CASE_P(Imgproc, ColumnSum, Combine( Values(MatType(CV_32FC1)), Values(0), // not used Values(0), // not used Bool())); INSTANTIATE_TEST_CASE_P(ImgprocTestBase, CopyMakeBorder, Combine( testing::Range((MatDepth)CV_8U, (MatDepth)CV_USRTYPE1), testing::Values((Channels)1, (Channels)4), Bool(), // border isolated or not Values((Border)BORDER_CONSTANT, (Border)BORDER_REPLICATE, (Border)BORDER_REFLECT, (Border)BORDER_WRAP, (Border)BORDER_REFLECT_101), Bool())); #endif // HAVE_OPENCL