396 lines
14 KiB
C++
396 lines
14 KiB
C++
/*M///////////////////////////////////////////////////////////////////////////////////////
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//
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// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
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//
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// By downloading, copying, installing or using the software you agree to this license.
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// If you do not agree to this license, do not download, install,
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// copy or use the software.
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//
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//
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// License Agreement
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// For Open Source Computer Vision Library
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//
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// Copyright (C) 2010-2012, Institute Of Software Chinese Academy Of Science, all rights reserved.
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// Copyright (C) 2010-2012, Advanced Micro Devices, Inc., all rights reserved.
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// Copyright (C) 2010-2012, Multicoreware, Inc., all rights reserved.
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// Third party copyrights are property of their respective owners.
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//
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// @Authors
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// Niko Li, newlife20080214@gmail.com
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// Jia Haipeng, jiahaipeng95@gmail.com
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// Shengen Yan, yanshengen@gmail.com
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// Jiang Liyuan, lyuan001.good@163.com
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// Rock Li, Rock.Li@amd.com
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// Wu Zailong, bullet@yeah.net
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// Xu Pang, pangxu010@163.com
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// Sen Liu, swjtuls1987@126.com
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//
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// Redistribution and use in source and binary forms, with or without modification,
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// are permitted provided that the following conditions are met:
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//
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// * Redistribution's of source code must retain the above copyright notice,
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// this list of conditions and the following disclaimer.
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//
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// * Redistribution's in binary form must reproduce the above copyright notice,
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// this list of conditions and the following disclaimer in the documentation
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// and/or other materials provided with the distribution.
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//
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// * The name of the copyright holders may not be used to endorse or promote products
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// derived from this software without specific prior written permission.
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//
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// This software is provided by the copyright holders and contributors "as is" and
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// any express or implied warranties, including, but not limited to, the implied
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// warranties of merchantability and fitness for a particular purpose are disclaimed.
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// In no event shall the Intel Corporation or contributors be liable for any direct,
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// indirect, incidental, special, exemplary, or consequential damages
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// (including, but not limited to, procurement of substitute goods or services;
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// loss of use, data, or profits; or business interruption) however caused
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// and on any theory of liability, whether in contract, strict liability,
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// or tort (including negligence or otherwise) arising in any way out of
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// the use of this software, even if advised of the possibility of such damage.
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//
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//M*/
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#include "../test_precomp.hpp"
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#include "opencv2/ts/ocl_test.hpp"
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#ifdef HAVE_OPENCL
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namespace cvtest {
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namespace ocl {
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enum
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{
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noType = -1
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};
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/////////////////////////////////////////////////////////////////////////////////////////////////
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// warpAffine & warpPerspective
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PARAM_TEST_CASE(WarpTestBase, MatType, Interpolation, bool, bool)
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{
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int type, interpolation;
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Size dsize;
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bool useRoi, mapInverse;
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int depth;
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TEST_DECLARE_INPUT_PARAMETER(src);
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TEST_DECLARE_OUTPUT_PARAMETER(dst);
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virtual void SetUp()
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{
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type = GET_PARAM(0);
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interpolation = GET_PARAM(1);
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mapInverse = GET_PARAM(2);
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useRoi = GET_PARAM(3);
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depth = CV_MAT_DEPTH(type);
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if (mapInverse)
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interpolation |= WARP_INVERSE_MAP;
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}
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void random_roi()
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{
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dsize = randomSize(1, MAX_VALUE);
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Size roiSize = randomSize(1, MAX_VALUE);
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Border srcBorder = randomBorder(0, useRoi ? MAX_VALUE : 0);
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randomSubMat(src, src_roi, roiSize, srcBorder, type, -MAX_VALUE, MAX_VALUE);
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Border dstBorder = randomBorder(0, useRoi ? MAX_VALUE : 0);
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randomSubMat(dst, dst_roi, dsize, dstBorder, type, -MAX_VALUE, MAX_VALUE);
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UMAT_UPLOAD_INPUT_PARAMETER(src);
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UMAT_UPLOAD_OUTPUT_PARAMETER(dst);
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}
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void Near(double threshold = 0.0)
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{
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if (depth < CV_32F)
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EXPECT_MAT_N_DIFF(dst_roi, udst_roi, cvRound(dst_roi.total()*threshold));
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else
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OCL_EXPECT_MATS_NEAR_RELATIVE(dst, threshold);
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}
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};
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/////warpAffine
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typedef WarpTestBase WarpAffine;
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OCL_TEST_P(WarpAffine, Mat)
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{
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for (int j = 0; j < test_loop_times; j++)
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{
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double eps = depth < CV_32F ? 0.04 : 0.06;
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random_roi();
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Mat M = getRotationMatrix2D(Point2f(src_roi.cols / 2.0f, src_roi.rows / 2.0f),
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rng.uniform(-180.f, 180.f), rng.uniform(0.4f, 2.0f));
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OCL_OFF(cv::warpAffine(src_roi, dst_roi, M, dsize, interpolation));
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OCL_ON(cv::warpAffine(usrc_roi, udst_roi, M, dsize, interpolation));
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Near(eps);
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}
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}
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//// warpPerspective
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typedef WarpTestBase WarpPerspective;
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OCL_TEST_P(WarpPerspective, Mat)
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{
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for (int j = 0; j < test_loop_times; j++)
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{
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double eps = depth < CV_32F ? 0.03 : 0.06;
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random_roi();
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float cols = static_cast<float>(src_roi.cols), rows = static_cast<float>(src_roi.rows);
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float cols2 = cols / 2.0f, rows2 = rows / 2.0f;
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Point2f sp[] = { Point2f(0.0f, 0.0f), Point2f(cols, 0.0f), Point2f(0.0f, rows), Point2f(cols, rows) };
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Point2f dp[] = { Point2f(rng.uniform(0.0f, cols2), rng.uniform(0.0f, rows2)),
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Point2f(rng.uniform(cols2, cols), rng.uniform(0.0f, rows2)),
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Point2f(rng.uniform(0.0f, cols2), rng.uniform(rows2, rows)),
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Point2f(rng.uniform(cols2, cols), rng.uniform(rows2, rows)) };
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Mat M = getPerspectiveTransform(sp, dp);
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OCL_OFF(cv::warpPerspective(src_roi, dst_roi, M, dsize, interpolation));
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OCL_ON(cv::warpPerspective(usrc_roi, udst_roi, M, dsize, interpolation));
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Near(eps);
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}
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}
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/////////////////////////////////////////////////////////////////////////////////////////////////
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//// resize
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PARAM_TEST_CASE(Resize, MatType, double, double, Interpolation, bool, int)
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{
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int type, interpolation;
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int widthMultiple;
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double fx, fy;
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bool useRoi;
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TEST_DECLARE_INPUT_PARAMETER(src);
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TEST_DECLARE_OUTPUT_PARAMETER(dst);
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virtual void SetUp()
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{
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type = GET_PARAM(0);
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fx = GET_PARAM(1);
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fy = GET_PARAM(2);
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interpolation = GET_PARAM(3);
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useRoi = GET_PARAM(4);
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widthMultiple = GET_PARAM(5);
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}
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void random_roi()
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{
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CV_Assert(fx > 0 && fy > 0);
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Size srcRoiSize = randomSize(10, MAX_VALUE), dstRoiSize;
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// Make sure the width is a multiple of the requested value, and no more
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srcRoiSize.width += widthMultiple - 1 - (srcRoiSize.width - 1) % widthMultiple;
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dstRoiSize.width = cvRound(srcRoiSize.width * fx);
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dstRoiSize.height = cvRound(srcRoiSize.height * fy);
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if (dstRoiSize.area() == 0)
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{
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random_roi();
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return;
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}
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Border srcBorder = randomBorder(0, useRoi ? MAX_VALUE : 0);
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randomSubMat(src, src_roi, srcRoiSize, srcBorder, type, -MAX_VALUE, MAX_VALUE);
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Border dstBorder = randomBorder(0, useRoi ? MAX_VALUE : 0);
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randomSubMat(dst, dst_roi, dstRoiSize, dstBorder, type, -MAX_VALUE, MAX_VALUE);
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UMAT_UPLOAD_INPUT_PARAMETER(src);
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UMAT_UPLOAD_OUTPUT_PARAMETER(dst);
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}
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void Near(double threshold = 0.0)
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{
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OCL_EXPECT_MATS_NEAR(dst, threshold);
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}
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};
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OCL_TEST_P(Resize, Mat)
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{
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for (int j = 0; j < test_loop_times; j++)
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{
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int depth = CV_MAT_DEPTH(type);
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double eps = depth <= CV_32S ? 1 : 5e-2;
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random_roi();
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OCL_OFF(cv::resize(src_roi, dst_roi, Size(), fx, fy, interpolation));
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OCL_ON(cv::resize(usrc_roi, udst_roi, Size(), fx, fy, interpolation));
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Near(eps);
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}
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}
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/////////////////////////////////////////////////////////////////////////////////////////////////
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// remap
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PARAM_TEST_CASE(Remap, MatDepth, Channels, std::pair<MatType, MatType>, BorderType, bool)
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{
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int srcType, map1Type, map2Type;
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int borderType;
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bool useRoi;
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Scalar val;
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TEST_DECLARE_INPUT_PARAMETER(src);
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TEST_DECLARE_INPUT_PARAMETER(map1);
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TEST_DECLARE_INPUT_PARAMETER(map2);
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TEST_DECLARE_OUTPUT_PARAMETER(dst);
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virtual void SetUp()
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{
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srcType = CV_MAKE_TYPE(GET_PARAM(0), GET_PARAM(1));
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map1Type = GET_PARAM(2).first;
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map2Type = GET_PARAM(2).second;
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borderType = GET_PARAM(3);
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useRoi = GET_PARAM(4);
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}
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void random_roi()
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{
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val = randomScalar(-MAX_VALUE, MAX_VALUE);
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Size srcROISize = randomSize(1, MAX_VALUE);
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Size dstROISize = randomSize(1, MAX_VALUE);
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Border srcBorder = randomBorder(0, useRoi ? MAX_VALUE : 0);
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randomSubMat(src, src_roi, srcROISize, srcBorder, srcType, 5, 256);
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Border dstBorder = randomBorder(0, useRoi ? MAX_VALUE : 0);
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randomSubMat(dst, dst_roi, dstROISize, dstBorder, srcType, -MAX_VALUE, MAX_VALUE);
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int mapMaxValue = MAX_VALUE << 2;
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Border map1Border = randomBorder(0, useRoi ? MAX_VALUE : 0);
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randomSubMat(map1, map1_roi, dstROISize, map1Border, map1Type, -mapMaxValue, mapMaxValue);
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Border map2Border = randomBorder(0, useRoi ? MAX_VALUE + 1 : 0);
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if (map2Type != noType)
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{
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int mapMinValue = -mapMaxValue;
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if (map2Type == CV_16UC1 || map2Type == CV_16SC1)
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mapMinValue = 0, mapMaxValue = INTER_TAB_SIZE2;
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randomSubMat(map2, map2_roi, dstROISize, map2Border, map2Type, mapMinValue, mapMaxValue);
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}
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UMAT_UPLOAD_INPUT_PARAMETER(src);
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UMAT_UPLOAD_INPUT_PARAMETER(map1);
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UMAT_UPLOAD_OUTPUT_PARAMETER(dst);
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if (noType != map2Type)
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UMAT_UPLOAD_INPUT_PARAMETER(map2);
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}
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void Near(double threshold = 0.0)
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{
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OCL_EXPECT_MATS_NEAR(dst, threshold);
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}
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};
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typedef Remap Remap_INTER_NEAREST;
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OCL_TEST_P(Remap_INTER_NEAREST, Mat)
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{
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for (int j = 0; j < test_loop_times; j++)
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{
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random_roi();
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OCL_OFF(cv::remap(src_roi, dst_roi, map1_roi, map2_roi, INTER_NEAREST, borderType, val));
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OCL_ON(cv::remap(usrc_roi, udst_roi, umap1_roi, umap2_roi, INTER_NEAREST, borderType, val));
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Near(1.0);
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}
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}
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typedef Remap Remap_INTER_LINEAR;
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OCL_TEST_P(Remap_INTER_LINEAR, Mat)
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{
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for (int j = 0; j < test_loop_times; j++)
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{
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random_roi();
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double eps = 2.0;
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#ifdef ANDROID
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// TODO investigate accuracy
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if (cv::ocl::Device::getDefault().isNVidia())
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eps = 8.0;
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#endif
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OCL_OFF(cv::remap(src_roi, dst_roi, map1_roi, map2_roi, INTER_LINEAR, borderType, val));
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OCL_ON(cv::remap(usrc_roi, udst_roi, umap1_roi, umap2_roi, INTER_LINEAR, borderType, val));
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Near(eps);
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}
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}
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/////////////////////////////////////////////////////////////////////////////////////
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OCL_INSTANTIATE_TEST_CASE_P(ImgprocWarp, WarpAffine, Combine(
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Values(CV_8UC1, CV_8UC3, CV_8UC4, CV_32FC1, CV_32FC3, CV_32FC4),
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Values((Interpolation)INTER_NEAREST, (Interpolation)INTER_LINEAR, (Interpolation)INTER_CUBIC),
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Bool(),
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Bool()));
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OCL_INSTANTIATE_TEST_CASE_P(ImgprocWarp, WarpPerspective, Combine(
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Values(CV_8UC1, CV_8UC3, CV_8UC4, CV_32FC1, CV_32FC3, CV_32FC4),
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Values((Interpolation)INTER_NEAREST, (Interpolation)INTER_LINEAR, (Interpolation)INTER_CUBIC),
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Bool(),
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Bool()));
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OCL_INSTANTIATE_TEST_CASE_P(ImgprocWarp, Resize, Combine(
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Values(CV_8UC1, CV_8UC4, CV_16UC2, CV_32FC1, CV_32FC4),
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Values(0.5, 1.5, 2.0, 0.2),
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Values(0.5, 1.5, 2.0, 0.2),
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Values((Interpolation)INTER_NEAREST, (Interpolation)INTER_LINEAR),
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Bool(),
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Values(1, 16)));
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OCL_INSTANTIATE_TEST_CASE_P(ImgprocWarpResizeArea, Resize, Combine(
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Values((MatType)CV_8UC1, CV_8UC4, CV_32FC1, CV_32FC4),
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Values(0.7, 0.4, 0.5),
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Values(0.3, 0.6, 0.5),
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Values((Interpolation)INTER_AREA),
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Bool(),
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Values(1, 16)));
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OCL_INSTANTIATE_TEST_CASE_P(ImgprocWarp, Remap_INTER_LINEAR, Combine(
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Values(CV_8U, CV_16U, CV_32F),
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Values(1, 3, 4),
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Values(std::pair<MatType, MatType>((MatType)CV_32FC1, (MatType)CV_32FC1),
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std::pair<MatType, MatType>((MatType)CV_16SC2, (MatType)CV_16UC1),
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std::pair<MatType, MatType>((MatType)CV_32FC2, noType)),
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Values((BorderType)BORDER_CONSTANT,
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(BorderType)BORDER_REPLICATE,
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(BorderType)BORDER_WRAP,
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(BorderType)BORDER_REFLECT,
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(BorderType)BORDER_REFLECT_101),
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Bool()));
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OCL_INSTANTIATE_TEST_CASE_P(ImgprocWarp, Remap_INTER_NEAREST, Combine(
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Values(CV_8U, CV_16U, CV_32F),
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Values(1, 3, 4),
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Values(std::pair<MatType, MatType>((MatType)CV_32FC1, (MatType)CV_32FC1),
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std::pair<MatType, MatType>((MatType)CV_32FC2, noType),
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std::pair<MatType, MatType>((MatType)CV_16SC2, (MatType)CV_16UC1),
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std::pair<MatType, MatType>((MatType)CV_16SC2, noType)),
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Values((BorderType)BORDER_CONSTANT,
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(BorderType)BORDER_REPLICATE,
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(BorderType)BORDER_WRAP,
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(BorderType)BORDER_REFLECT,
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(BorderType)BORDER_REFLECT_101),
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Bool()));
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} } // namespace cvtest::ocl
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#endif // HAVE_OPENCL
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