/*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" #include "cvconfig.h" #include "opencv2/ts/ocl_test.hpp" #ifdef HAVE_OPENCL namespace cvtest { namespace ocl { /////////////////////////////////////////////////////////////////////////////// PARAM_TEST_CASE(ImgprocTestBase, MatType, int, // blockSize int, // border type bool) // roi or not { int type, borderType, blockSize; bool useRoi; TEST_DECLARE_INPUT_PARAMETER(src) TEST_DECLARE_OUTPUT_PARAMETER(dst) 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, dst_roi, roiSize, dstBorder, type, 5, 16); UMAT_UPLOAD_INPUT_PARAMETER(src) UMAT_UPLOAD_OUTPUT_PARAMETER(dst) } void Near(double threshold = 0.0, bool relative = false) { if (relative) { EXPECT_MAT_NEAR_RELATIVE(dst, udst, threshold); EXPECT_MAT_NEAR_RELATIVE(dst_roi, udst_roi, threshold); } else { EXPECT_MAT_NEAR(dst, udst, threshold); EXPECT_MAT_NEAR(dst_roi, udst_roi, threshold); } } }; ////////////////////////////////copyMakeBorder//////////////////////////////////////////// PARAM_TEST_CASE(CopyMakeBorder, MatDepth, // depth Channels, // channels bool, // isolated or not BorderType, // border type bool) // roi or not { int type, borderType; bool useRoi; TestUtils::Border border; Scalar val; TEST_DECLARE_INPUT_PARAMETER(src) TEST_DECLARE_OUTPUT_PARAMETER(dst) 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() { border = randomBorder(0, MAX_VALUE << 2); val = randomScalar(-MAX_VALUE, MAX_VALUE); Size roiSize = randomSize(1, MAX_VALUE); Border srcBorder = randomBorder(0, useRoi ? MAX_VALUE : 0); randomSubMat(src, src_roi, roiSize, srcBorder, type, -MAX_VALUE, MAX_VALUE); Border dstBorder = randomBorder(0, useRoi ? MAX_VALUE : 0); dstBorder.top += border.top; dstBorder.lef += border.lef; dstBorder.rig += border.rig; dstBorder.bot += border.bot; randomSubMat(dst, dst_roi, roiSize, dstBorder, type, -MAX_VALUE, MAX_VALUE); UMAT_UPLOAD_INPUT_PARAMETER(src) UMAT_UPLOAD_OUTPUT_PARAMETER(dst) } void Near(double threshold = 0.0) { EXPECT_MAT_NEAR(dst, udst, threshold); EXPECT_MAT_NEAR(dst_roi, udst_roi, threshold); } }; OCL_TEST_P(CopyMakeBorder, Mat) { for (int i = 0; i < test_loop_times; ++i) { random_roi(); OCL_OFF(cv::copyMakeBorder(src_roi, dst_roi, border.top, border.bot, border.lef, border.rig, borderType, val)); OCL_ON(cv::copyMakeBorder(usrc_roi, udst_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 < test_loop_times; j++) { random_roi(); OCL_OFF(cv::equalizeHist(src_roi, dst_roi)); OCL_ON(cv::equalizeHist(usrc_roi, udst_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, dst_roi, roiSize, dstBorder, CV_32FC1, 5, 16); UMAT_UPLOAD_INPUT_PARAMETER(src) UMAT_UPLOAD_OUTPUT_PARAMETER(dst) } }; typedef CornerTestBase CornerMinEigenVal; OCL_TEST_P(CornerMinEigenVal, DISABLED_Mat) { for (int j = 0; j < test_loop_times; j++) { random_roi(); int apertureSize = 3; OCL_OFF(cv::cornerMinEigenVal(src_roi, dst_roi, blockSize, apertureSize, borderType)); OCL_ON(cv::cornerMinEigenVal(usrc_roi, udst_roi, blockSize, apertureSize, borderType)); Near(1e-5, true); } } ////////////////////////////////cornerHarris////////////////////////////////////////// typedef CornerTestBase CornerHarris; OCL_TEST_P(CornerHarris, DISABLED_Mat) { for (int j = 0; j < test_loop_times; j++) { random_roi(); int apertureSize = 3; double k = randomDouble(0.01, 0.9); OCL_OFF(cv::cornerHarris(src_roi, dst_roi, blockSize, apertureSize, k, borderType)); OCL_ON(cv::cornerHarris(usrc_roi, udst_roi, blockSize, apertureSize, k, borderType)); Near(1e-5, true); } } //////////////////////////////////integral///////////////////////////////////////////////// struct Integral : public ImgprocTestBase { int sdepth; virtual void SetUp() { type = GET_PARAM(0); blockSize = GET_PARAM(1); sdepth = GET_PARAM(2); useRoi = GET_PARAM(3); } }; OCL_TEST_P(Integral, Mat1) { for (int j = 0; j < test_loop_times; j++) { random_roi(); OCL_OFF(cv::integral(src_roi, dst_roi, sdepth)); OCL_ON(cv::integral(usrc_roi, udst_roi, sdepth)); Near(); } } OCL_TEST_P(Integral, Mat2) { Mat dst1; UMat udst1; for (int j = 0; j < test_loop_times; j++) { random_roi(); OCL_OFF(cv::integral(src_roi, dst_roi, dst1, sdepth)); OCL_ON(cv::integral(usrc_roi, udst_roi, udst1, sdepth)); Near(); if (cv::ocl::Device::getDefault().doubleFPConfig() > 0) EXPECT_MAT_NEAR(dst1, udst1, 0.); } } /////////////////////////////////////////////////////////////////////////////////////////////////// //// 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 < test_loop_times; j++) { random_roi(); double maxVal = randomDouble(20.0, 127.0); double thresh = randomDouble(0.0, maxVal); OCL_OFF(cv::threshold(src_roi, dst_roi, thresh, maxVal, thresholdType)); OCL_ON(cv::threshold(usrc_roi, udst_roi, thresh, maxVal, thresholdType)); Near(1); } } ///////////////////////////////////////////////////////////////////////////////////////////////////////// //// CLAHE PARAM_TEST_CASE(CLAHETest, Size, double, bool) { Size gridSize; double clipLimit; bool useRoi; TEST_DECLARE_INPUT_PARAMETER(src) TEST_DECLARE_OUTPUT_PARAMETER(dst) 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, dst_roi, roiSize, dstBorder, CV_8UC1, 5, 16); UMAT_UPLOAD_INPUT_PARAMETER(src) UMAT_UPLOAD_OUTPUT_PARAMETER(dst) } void Near(double threshold = 0.0) { EXPECT_MAT_NEAR(dst, udst, threshold); EXPECT_MAT_NEAR(dst_roi, udst_roi, threshold); } }; OCL_TEST_P(CLAHETest, Accuracy) { for (int i = 0; i < test_loop_times; ++i) { random_roi(); Ptr clahe = cv::createCLAHE(clipLimit, gridSize); OCL_OFF(clahe->apply(src_roi, dst_roi)); OCL_ON(clahe->apply(usrc_roi, udst_roi)); Near(1.0); } } ///////////////////////////////////////////////////////////////////////////////////// OCL_INSTANTIATE_TEST_CASE_P(Imgproc, EqualizeHist, Combine( Values((MatType)CV_8UC1), Values(0), // not used Values(0), // not used Bool())); OCL_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())); OCL_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())); OCL_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((MatType)CV_32SC1, (MatType)CV_32FC1), Bool())); OCL_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())); OCL_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())); OCL_INSTANTIATE_TEST_CASE_P(ImgprocTestBase, CopyMakeBorder, Combine( testing::Values((MatDepth)CV_8U, (MatDepth)CV_16S, (MatDepth)CV_32S, (MatDepth)CV_32F), testing::Values(Channels(1), Channels(3), (Channels)4), Bool(), // border isolated or not Values((BorderType)BORDER_CONSTANT, (BorderType)BORDER_REPLICATE, (BorderType)BORDER_REFLECT, (BorderType)BORDER_WRAP, (BorderType)BORDER_REFLECT_101), Bool())); } } // namespace cvtest::ocl #endif // HAVE_OPENCL