1347 lines
		
	
	
		
			36 KiB
		
	
	
	
		
			C++
		
	
	
	
	
	
			
		
		
	
	
			1347 lines
		
	
	
		
			36 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) 2013, OpenCV Foundation, all rights reserved.
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| // Third party copyrights are property of their respective owners.
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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 OpenCV Foundation 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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| 
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| #include "test_precomp.hpp"
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| #include "opencv2/ts/ocl_test.hpp"
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| 
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| using namespace cvtest;
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| using namespace testing;
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| using namespace cv;
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| 
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| namespace cvtest {
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| namespace ocl {
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| 
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| #define UMAT_TEST_SIZES testing::Values(cv::Size(1, 1), cv::Size(1,128), cv::Size(128, 1), \
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|     cv::Size(128, 128), cv::Size(640, 480), cv::Size(751, 373), cv::Size(1200, 1200))
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| 
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| /////////////////////////////// Basic Tests ////////////////////////////////
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| 
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| PARAM_TEST_CASE(UMatBasicTests, int, int, Size, bool)
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| {
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|     Mat a;
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|     UMat ua;
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|     int type;
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|     int depth;
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|     int cn;
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|     Size size;
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|     bool useRoi;
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|     Size roi_size;
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|     Rect roi;
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| 
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|     virtual void SetUp()
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|     {
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|         depth = GET_PARAM(0);
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|         cn = GET_PARAM(1);
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|         size = GET_PARAM(2);
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|         useRoi = GET_PARAM(3);
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|         type = CV_MAKE_TYPE(depth, cn);
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|         a = randomMat(size, type, -100, 100);
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|         a.copyTo(ua);
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|         int roi_shift_x = randomInt(0, size.width-1);
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|         int roi_shift_y = randomInt(0, size.height-1);
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|         roi_size = Size(size.width - roi_shift_x, size.height - roi_shift_y);
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|         roi = Rect(roi_shift_x, roi_shift_y, roi_size.width, roi_size.height);
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|     }
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| };
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| 
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| TEST_P(UMatBasicTests, createUMat)
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| {
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|     if(useRoi)
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|     {
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|         ua = UMat(ua, roi);
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|     }
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|     int dims = randomInt(2,6);
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|     int _sz[CV_MAX_DIM];
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|     for( int i = 0; i<dims; i++)
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|     {
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|         _sz[i] = randomInt(1,50);
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|     }
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|     int *sz = _sz;
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|     int new_depth = randomInt(CV_8S, CV_64F);
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|     int new_cn = randomInt(1,4);
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|     ua.create(dims, sz, CV_MAKE_TYPE(new_depth, new_cn));
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| 
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|     for(int i = 0; i<dims; i++)
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|     {
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|         ASSERT_EQ(ua.size[i], sz[i]);
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|     }
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|     ASSERT_EQ(ua.dims, dims);
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|     ASSERT_EQ(ua.type(), CV_MAKE_TYPE(new_depth, new_cn) );
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|     Size new_size = randomSize(1, 1000);
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|     ua.create(new_size, CV_MAKE_TYPE(new_depth, new_cn) );
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|     ASSERT_EQ( ua.size(), new_size);
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|     ASSERT_EQ(ua.type(), CV_MAKE_TYPE(new_depth, new_cn) );
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|     ASSERT_EQ( ua.dims, 2);
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| }
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| 
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| TEST_P(UMatBasicTests, swap)
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| {
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|     Mat b = randomMat(size, type, -100, 100);
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|     UMat ub;
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|     b.copyTo(ub);
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|     if(useRoi)
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|     {
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|         ua = UMat(ua,roi);
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|         ub = UMat(ub,roi);
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|     }
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|     UMat uc = ua, ud = ub;
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|     swap(ua,ub);
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|     EXPECT_MAT_NEAR(ub,uc, 0);
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|     EXPECT_MAT_NEAR(ud, ua, 0);
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| }
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| 
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| TEST_P(UMatBasicTests, base)
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| {
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|     const int align_mask = 3;
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|     roi.x &= ~align_mask;
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|     roi.y &= ~align_mask;
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|     roi.width = (roi.width + align_mask) & ~align_mask;
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|     roi &= Rect(0, 0, ua.cols, ua.rows);
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| 
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|     if(useRoi)
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|     {
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|         ua = UMat(ua,roi);
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|     }
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|     UMat ub = ua.clone();
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|     EXPECT_MAT_NEAR(ub,ua,0);
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| 
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|     ASSERT_EQ(ua.channels(), cn);
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|     ASSERT_EQ(ua.depth(), depth);
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|     ASSERT_EQ(ua.type(), type);
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|     ASSERT_EQ(ua.elemSize(), a.elemSize());
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|     ASSERT_EQ(ua.elemSize1(), a.elemSize1());
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|     ASSERT_EQ(ub.empty(), ub.cols*ub.rows == 0);
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|     ub.release();
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|     ASSERT_TRUE( ub.empty() );
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|     if(useRoi && a.size() != ua.size())
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|     {
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|         ASSERT_EQ(ua.isSubmatrix(), true);
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|     }
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|     else
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|     {
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|         ASSERT_EQ(ua.isSubmatrix(), false);
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|     }
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| 
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|     int dims = randomInt(2,6);
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|     int sz[CV_MAX_DIM];
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|     size_t total = 1;
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|     for(int i = 0; i<dims; i++)
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|     {
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|         sz[i] = randomInt(1,45);
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|         total *= (size_t)sz[i];
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|     }
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|     int new_type = CV_MAKE_TYPE(randomInt(CV_8S,CV_64F),randomInt(1,4));
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|     ub = UMat(dims, sz, new_type);
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|     ASSERT_EQ(ub.total(), total);
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| }
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| 
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| TEST_P(UMatBasicTests, copyTo)
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| {
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|     int i;
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|     if(useRoi)
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|     {
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|         UMat roi_ua;
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|         Mat roi_a;
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|         roi_ua = UMat(ua, roi);
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|         roi_a = Mat(a, roi);
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|         roi_a.copyTo(roi_ua);
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|         EXPECT_MAT_NEAR(roi_a, roi_ua, 0);
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|         roi_ua.copyTo(roi_a);
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|         EXPECT_MAT_NEAR(roi_ua, roi_a, 0);
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|         roi_ua.copyTo(ua);
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|         EXPECT_MAT_NEAR(roi_ua, ua, 0);
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|         ua.copyTo(a);
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|         EXPECT_MAT_NEAR(ua, a, 0);
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|     }
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|     {
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|         UMat ub;
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|         ua.copyTo(ub);
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|         EXPECT_MAT_NEAR(ua, ub, 0);
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|     }
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|     {
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|         UMat ub;
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|         i = randomInt(0, ua.cols-1);
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|         a.col(i).copyTo(ub);
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|         EXPECT_MAT_NEAR(a.col(i), ub, 0);
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|     }
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|     {
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|         UMat ub;
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|         ua.col(i).copyTo(ub);
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|         EXPECT_MAT_NEAR(ua.col(i), ub, 0);
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|     }
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|     {
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|         Mat b;
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|         ua.col(i).copyTo(b);
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|         EXPECT_MAT_NEAR(ua.col(i), b, 0);
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|     }
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|     {
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|         UMat ub;
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|         i = randomInt(0, a.rows-1);
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|         ua.row(i).copyTo(ub);
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|         EXPECT_MAT_NEAR(ua.row(i), ub, 0);
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|     }
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|     {
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|         UMat ub;
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|         a.row(i).copyTo(ub);
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|         EXPECT_MAT_NEAR(a.row(i), ub, 0);
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|     }
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|     {
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|         Mat b;
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|         ua.row(i).copyTo(b);
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|         EXPECT_MAT_NEAR(ua.row(i), b, 0);
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|     }
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| }
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| 
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| TEST_P(UMatBasicTests, GetUMat)
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| {
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|     if(useRoi)
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|     {
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|         a = Mat(a, roi);
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|         ua = UMat(ua,roi);
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|     }
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|     {
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|         UMat ub;
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|         ub = a.getUMat(ACCESS_RW);
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|         EXPECT_MAT_NEAR(ub, ua, 0);
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|     }
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|     {
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|         UMat u = a.getUMat(ACCESS_RW);
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|         {
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|             Mat b = u.getMat(ACCESS_RW);
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|             EXPECT_MAT_NEAR(b, a, 0);
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|         }
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|     }
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|     {
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|         Mat b;
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|         b = ua.getMat(ACCESS_RW);
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|         EXPECT_MAT_NEAR(b, a, 0);
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|     }
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|     {
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|         Mat m = ua.getMat(ACCESS_RW);
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|         {
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|             UMat ub = m.getUMat(ACCESS_RW);
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|             EXPECT_MAT_NEAR(ub, ua, 0);
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|         }
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|     }
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| }
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| 
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| INSTANTIATE_TEST_CASE_P(UMat, UMatBasicTests, Combine(testing::Values(CV_8U, CV_64F), testing::Values(1, 2),
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|     testing::Values(cv::Size(1, 1), cv::Size(1, 128), cv::Size(128, 1), cv::Size(128, 128), cv::Size(640, 480)), Bool()));
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| 
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| //////////////////////////////////////////////////////////////// Reshape ////////////////////////////////////////////////////////////////////////
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| 
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| PARAM_TEST_CASE(UMatTestReshape,  int, int, Size, bool)
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| {
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|     Mat a;
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|     UMat ua, ub;
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|     int type;
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|     int depth;
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|     int cn;
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|     Size size;
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|     bool useRoi;
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|     Size roi_size;
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|     virtual void SetUp()
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|     {
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|         depth = GET_PARAM(0);
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|         cn = GET_PARAM(1);
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|         size = GET_PARAM(2);
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|         useRoi = GET_PARAM(3);
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|         type = CV_MAKE_TYPE(depth, cn);
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|     }
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| };
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| 
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| TEST_P(UMatTestReshape, reshape)
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| {
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|     a = randomMat(size,type, -100, 100);
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|     a.copyTo(ua);
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|     if(useRoi)
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|     {
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|         int roi_shift_x = randomInt(0, size.width-1);
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|         int roi_shift_y = randomInt(0, size.height-1);
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|         roi_size = Size(size.width - roi_shift_x, size.height - roi_shift_y);
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|         Rect roi(roi_shift_x, roi_shift_y, roi_size.width, roi_size.height);
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|         ua = UMat(ua, roi).clone();
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|         a = Mat(a, roi).clone();
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|     }
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| 
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|     int nChannels = randomInt(1,4);
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| 
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|     if ((ua.cols*ua.channels()*ua.rows)%nChannels != 0)
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|     {
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|         EXPECT_ANY_THROW(ua.reshape(nChannels));
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|     }
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|     else
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|     {
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|         ub = ua.reshape(nChannels);
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|         ASSERT_EQ(ub.channels(),nChannels);
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|         ASSERT_EQ(ub.channels()*ub.cols*ub.rows, ua.channels()*ua.cols*ua.rows);
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| 
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|         EXPECT_MAT_NEAR(ua.reshape(nChannels), a.reshape(nChannels), 0);
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| 
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|         int new_rows = randomInt(1, INT_MAX);
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|         if ( ((int)ua.total()*ua.channels())%(new_rows*nChannels) != 0)
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|         {
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|             EXPECT_ANY_THROW (ua.reshape(nChannels, new_rows) );
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|         }
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|         else
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|         {
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|             EXPECT_NO_THROW ( ub = ua.reshape(nChannels, new_rows) );
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|             ASSERT_EQ(ub.channels(),nChannels);
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|             ASSERT_EQ(ub.rows, new_rows);
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|             ASSERT_EQ(ub.channels()*ub.cols*ub.rows, ua.channels()*ua.cols*ua.rows);
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| 
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|             EXPECT_MAT_NEAR(ua.reshape(nChannels,new_rows), a.reshape(nChannels,new_rows), 0);
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|         }
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| 
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|         new_rows = (int)ua.total()*ua.channels()/(nChannels*randomInt(1, size.width*size.height));
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|         if (new_rows == 0) new_rows = 1;
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|         int new_cols = (int)ua.total()*ua.channels()/(new_rows*nChannels);
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|         int sz[] = {new_rows, new_cols};
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|         if( ((int)ua.total()*ua.channels()) % (new_rows*new_cols) != 0 )
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|         {
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|             EXPECT_ANY_THROW( ua.reshape(nChannels, ua.dims, sz) );
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|         }
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|         else
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|         {
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|             EXPECT_NO_THROW ( ub = ua.reshape(nChannels, ua.dims, sz) );
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|             ASSERT_EQ(ub.channels(),nChannels);
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|             ASSERT_EQ(ub.rows, new_rows);
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|             ASSERT_EQ(ub.cols, new_cols);
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|             ASSERT_EQ(ub.channels()*ub.cols*ub.rows, ua.channels()*ua.cols*ua.rows);
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| 
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|             EXPECT_MAT_NEAR(ua.reshape(nChannels, ua.dims, sz), a.reshape(nChannels, a.dims, sz), 0);
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|         }
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|     }
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| }
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| 
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| INSTANTIATE_TEST_CASE_P(UMat, UMatTestReshape, Combine(OCL_ALL_DEPTHS, OCL_ALL_CHANNELS, UMAT_TEST_SIZES, Bool() ));
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| 
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| static void check_ndim_shape(const cv::UMat &mat, int cn, int ndims, const int *sizes)
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| {
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|     EXPECT_EQ(mat.channels(), cn);
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|     EXPECT_EQ(mat.dims, ndims);
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| 
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|     if (mat.dims != ndims)
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|         return;
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| 
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|     for (int i = 0; i < ndims; i++)
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|         EXPECT_EQ(mat.size[i], sizes[i]);
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| }
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| 
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| TEST(UMatTestReshape, reshape_ndims_2)
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| {
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|     const cv::UMat A(8, 16, CV_8UC3);
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|     cv::UMat B;
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| 
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|     {
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|         int new_sizes_mask[] = { 0, 3, 4, 4 };
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|         int new_sizes_real[] = { 8, 3, 4, 4 };
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|         ASSERT_NO_THROW(B = A.reshape(1, 4, new_sizes_mask));
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|         check_ndim_shape(B, 1, 4, new_sizes_real);
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|     }
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|     {
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|         int new_sizes[] = { 16, 8 };
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|         ASSERT_NO_THROW(B = A.reshape(0, 2, new_sizes));
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|         check_ndim_shape(B, 3, 2, new_sizes);
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|         EXPECT_EQ(B.rows, new_sizes[0]);
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|         EXPECT_EQ(B.cols, new_sizes[1]);
 | |
|     }
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|     {
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|         int new_sizes[] = { 2, 5, 1, 3 };
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|         cv::UMat A_sliced = A(cv::Range::all(), cv::Range(0, 15));
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|         ASSERT_ANY_THROW(A_sliced.reshape(4, 4, new_sizes));
 | |
|     }
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| }
 | |
| 
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| TEST(UMatTestReshape, reshape_ndims_4)
 | |
| {
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|     const int sizes[] = { 2, 6, 4, 12 };
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|     const cv::UMat A(4, sizes, CV_8UC3);
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|     cv::UMat B;
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| 
 | |
|     {
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|         int new_sizes_mask[] = { 0, 864 };
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|         int new_sizes_real[] = { 2, 864 };
 | |
|         ASSERT_NO_THROW(B = A.reshape(1, 2, new_sizes_mask));
 | |
|         check_ndim_shape(B, 1, 2, new_sizes_real);
 | |
|         EXPECT_EQ(B.rows, new_sizes_real[0]);
 | |
|         EXPECT_EQ(B.cols, new_sizes_real[1]);
 | |
|     }
 | |
|     {
 | |
|         int new_sizes_mask[] = { 4, 0, 0, 2, 3 };
 | |
|         int new_sizes_real[] = { 4, 6, 4, 2, 3 };
 | |
|         ASSERT_NO_THROW(B = A.reshape(0, 5, new_sizes_mask));
 | |
|         check_ndim_shape(B, 3, 5, new_sizes_real);
 | |
|     }
 | |
|     {
 | |
|         int new_sizes_mask[] = { 1, 1 };
 | |
|         ASSERT_ANY_THROW(A.reshape(0, 2, new_sizes_mask));
 | |
|     }
 | |
|     {
 | |
|         int new_sizes_mask[] = { 4, 6, 3, 3, 0 };
 | |
|         ASSERT_ANY_THROW(A.reshape(0, 5, new_sizes_mask));
 | |
|     }
 | |
| }
 | |
| 
 | |
| ////////////////////////////////////////////////////////////////// ROI testing ///////////////////////////////////////////////////////////////
 | |
| 
 | |
| PARAM_TEST_CASE(UMatTestRoi, int, int, Size)
 | |
| {
 | |
|     Mat a, roi_a;
 | |
|     UMat ua, roi_ua;
 | |
|     int type;
 | |
|     int depth;
 | |
|     int cn;
 | |
|     Size size;
 | |
|     Size roi_size;
 | |
|     virtual void SetUp()
 | |
|     {
 | |
|         depth = GET_PARAM(0);
 | |
|         cn = GET_PARAM(1);
 | |
|         size = GET_PARAM(2);
 | |
|         type = CV_MAKE_TYPE(depth, cn);
 | |
|     }
 | |
| };
 | |
| 
 | |
| TEST_P(UMatTestRoi, createRoi)
 | |
| {
 | |
|     int roi_shift_x = randomInt(0, size.width-1);
 | |
|     int roi_shift_y = randomInt(0, size.height-1);
 | |
|     roi_size = Size(size.width - roi_shift_x, size.height - roi_shift_y);
 | |
|     a = randomMat(size, type, -100, 100);
 | |
|     Rect roi(roi_shift_x, roi_shift_y, roi_size.width, roi_size.height);
 | |
|     roi_a = Mat(a, roi);
 | |
|     a.copyTo(ua);
 | |
|     roi_ua = UMat(ua, roi);
 | |
| 
 | |
|     EXPECT_MAT_NEAR(roi_a, roi_ua, 0);
 | |
| }
 | |
| 
 | |
| TEST_P(UMatTestRoi, locateRoi)
 | |
| {
 | |
|     int roi_shift_x = randomInt(0, size.width-1);
 | |
|     int roi_shift_y = randomInt(0, size.height-1);
 | |
|     roi_size = Size(size.width - roi_shift_x, size.height - roi_shift_y);
 | |
|     a = randomMat(size, type, -100, 100);
 | |
|     Rect roi(roi_shift_x, roi_shift_y, roi_size.width, roi_size.height);
 | |
|     roi_a = Mat(a, roi);
 | |
|     a.copyTo(ua);
 | |
|     roi_ua = UMat(ua,roi);
 | |
|     Size sz, usz;
 | |
|     Point p, up;
 | |
|     roi_a.locateROI(sz, p);
 | |
|     roi_ua.locateROI(usz, up);
 | |
|     ASSERT_EQ(sz, usz);
 | |
|     ASSERT_EQ(p, up);
 | |
| }
 | |
| 
 | |
| TEST_P(UMatTestRoi, adjustRoi)
 | |
| {
 | |
|     int roi_shift_x = randomInt(0, size.width-1);
 | |
|     int roi_shift_y = randomInt(0, size.height-1);
 | |
|     roi_size = Size(size.width - roi_shift_x, size.height - roi_shift_y);
 | |
|     a = randomMat(size, type, -100, 100);
 | |
|     Rect roi(roi_shift_x, roi_shift_y, roi_size.width, roi_size.height);
 | |
|     a.copyTo(ua);
 | |
|     roi_ua = UMat( ua, roi);
 | |
|     int adjLeft = randomInt(-(roi_ua.cols/2), (size.width-1)/2);
 | |
|     int adjRight = randomInt(-(roi_ua.cols/2), (size.width-1)/2);
 | |
|     int adjTop = randomInt(-(roi_ua.rows/2), (size.height-1)/2);
 | |
|     int adjBot = randomInt(-(roi_ua.rows/2), (size.height-1)/2);
 | |
|     roi_ua.adjustROI(adjTop, adjBot, adjLeft, adjRight);
 | |
|     roi_shift_x = std::max(0, roi.x-adjLeft);
 | |
|     roi_shift_y = std::max(0, roi.y-adjTop);
 | |
|     Rect new_roi( roi_shift_x, roi_shift_y, std::min(roi.width+adjRight+adjLeft, size.width-roi_shift_x), std::min(roi.height+adjBot+adjTop, size.height-roi_shift_y) );
 | |
|     UMat test_roi = UMat(ua, new_roi);
 | |
|     EXPECT_MAT_NEAR(roi_ua, test_roi, 0);
 | |
| }
 | |
| 
 | |
| INSTANTIATE_TEST_CASE_P(UMat, UMatTestRoi, Combine(OCL_ALL_DEPTHS, OCL_ALL_CHANNELS, UMAT_TEST_SIZES ));
 | |
| 
 | |
| /////////////////////////////////////////////////////////////// Size ////////////////////////////////////////////////////////////////////
 | |
| 
 | |
| PARAM_TEST_CASE(UMatTestSizeOperations, int, int, Size, bool)
 | |
| {
 | |
|     Mat a, b, roi_a, roi_b;
 | |
|     UMat ua, ub, roi_ua, roi_ub;
 | |
|     int type;
 | |
|     int depth;
 | |
|     int cn;
 | |
|     Size size;
 | |
|     Size roi_size;
 | |
|     bool useRoi;
 | |
|     virtual void SetUp()
 | |
|     {
 | |
|         depth = GET_PARAM(0);
 | |
|         cn = GET_PARAM(1);
 | |
|         size = GET_PARAM(2);
 | |
|         useRoi = GET_PARAM(3);
 | |
|         type = CV_MAKE_TYPE(depth, cn);
 | |
|     }
 | |
| };
 | |
| 
 | |
| TEST_P(UMatTestSizeOperations, copySize)
 | |
| {
 | |
|     Size s = randomSize(1,300);
 | |
|     a = randomMat(size, type, -100, 100);
 | |
|     b = randomMat(s, type, -100, 100);
 | |
|     a.copyTo(ua);
 | |
|     b.copyTo(ub);
 | |
|     if(useRoi)
 | |
|     {
 | |
|         int roi_shift_x = randomInt(0, size.width-1);
 | |
|         int roi_shift_y = randomInt(0, size.height-1);
 | |
|         roi_size = Size(size.width - roi_shift_x, size.height - roi_shift_y);
 | |
|         Rect roi(roi_shift_x, roi_shift_y, roi_size.width, roi_size.height);
 | |
|         ua = UMat(ua,roi);
 | |
| 
 | |
|         roi_shift_x = randomInt(0, s.width-1);
 | |
|         roi_shift_y = randomInt(0, s.height-1);
 | |
|         roi_size = Size(s.width - roi_shift_x, s.height - roi_shift_y);
 | |
|         roi = Rect(roi_shift_x, roi_shift_y, roi_size.width, roi_size.height);
 | |
|         ub = UMat(ub, roi);
 | |
|     }
 | |
|     ua.copySize(ub);
 | |
|     ASSERT_EQ(ua.size, ub.size);
 | |
| }
 | |
| 
 | |
| INSTANTIATE_TEST_CASE_P(UMat, UMatTestSizeOperations, Combine(OCL_ALL_DEPTHS, OCL_ALL_CHANNELS, UMAT_TEST_SIZES, Bool() ));
 | |
| 
 | |
| ///////////////////////////////////////////////////////////////// UMat operations ////////////////////////////////////////////////////////////////////////////
 | |
| 
 | |
| PARAM_TEST_CASE(UMatTestUMatOperations, int, int, Size, bool)
 | |
| {
 | |
|     Mat a, b;
 | |
|     UMat ua, ub;
 | |
|     int type;
 | |
|     int depth;
 | |
|     int cn;
 | |
|     Size size;
 | |
|     Size roi_size;
 | |
|     bool useRoi;
 | |
|     virtual void SetUp()
 | |
|     {
 | |
|         depth = GET_PARAM(0);
 | |
|         cn = GET_PARAM(1);
 | |
|         size = GET_PARAM(2);
 | |
|         useRoi = GET_PARAM(3);
 | |
|         type = CV_MAKE_TYPE(depth, cn);
 | |
|     }
 | |
| };
 | |
| 
 | |
| TEST_P(UMatTestUMatOperations, diag)
 | |
| {
 | |
|     a = randomMat(size, type, -100, 100);
 | |
|     a.copyTo(ua);
 | |
|     Mat new_diag;
 | |
|     if(useRoi)
 | |
|     {
 | |
|         int roi_shift_x = randomInt(0, size.width-1);
 | |
|         int roi_shift_y = randomInt(0, size.height-1);
 | |
|         roi_size = Size(size.width - roi_shift_x, size.height - roi_shift_y);
 | |
|         Rect roi(roi_shift_x, roi_shift_y, roi_size.width, roi_size.height);
 | |
|         ua = UMat(ua,roi);
 | |
|         a = Mat(a, roi);
 | |
|     }
 | |
|     int n = randomInt(0, ua.cols-1);
 | |
|     ub = ua.diag(n);
 | |
|     b = a.diag(n);
 | |
|     EXPECT_MAT_NEAR(b, ub, 0);
 | |
|     new_diag = randomMat(Size(ua.rows, 1), type, -100, 100);
 | |
|     new_diag.copyTo(ub);
 | |
|     ua = cv::UMat::diag(ub);
 | |
|     EXPECT_MAT_NEAR(ua.diag(), new_diag.t(), 0);
 | |
| }
 | |
| 
 | |
| INSTANTIATE_TEST_CASE_P(UMat, UMatTestUMatOperations, Combine(OCL_ALL_DEPTHS, OCL_ALL_CHANNELS, UMAT_TEST_SIZES, Bool()));
 | |
| 
 | |
| 
 | |
| /////////////////////////////////////////////////////////////// getUMat -> GetMat ///////////////////////////////////////////////////////////////////
 | |
| 
 | |
| PARAM_TEST_CASE(getUMat, int, int, Size, bool)
 | |
| {
 | |
|     int type;
 | |
|     Size size;
 | |
| 
 | |
|     virtual void SetUp()
 | |
|     {
 | |
|         int depth = GET_PARAM(0);
 | |
|         int cn    = GET_PARAM(1);
 | |
|         size      = GET_PARAM(2);
 | |
|         useOpenCL = GET_PARAM(3);
 | |
| 
 | |
|         type = CV_MAKE_TYPE(depth, cn);
 | |
| 
 | |
|         isOpenCL_enabled = cv::ocl::useOpenCL();
 | |
|         cv::ocl::setUseOpenCL(useOpenCL);
 | |
|     }
 | |
| 
 | |
|     virtual void TearDown()
 | |
|     {
 | |
|         cv::ocl::setUseOpenCL(isOpenCL_enabled);
 | |
|     }
 | |
| 
 | |
|     // UMat created from user allocated host memory (USE_HOST_PTR)
 | |
|     void custom_ptr_test(size_t align_base, size_t align_offset)
 | |
|     {
 | |
|         void* pData_allocated = new unsigned char [size.area() * CV_ELEM_SIZE(type) + (align_base + align_offset)];
 | |
|         void* pData = (char*)alignPtr(pData_allocated, (int)align_base) + align_offset;
 | |
|         size_t step = size.width * CV_ELEM_SIZE(type);
 | |
| 
 | |
|         {
 | |
|             Mat m = Mat(size, type, pData, step);
 | |
|             m.setTo(cv::Scalar::all(2));
 | |
| 
 | |
|             UMat u = m.getUMat(ACCESS_RW);
 | |
|             cv::add(u, cv::Scalar::all(2), u);
 | |
| 
 | |
|             Mat d = u.getMat(ACCESS_READ);
 | |
| 
 | |
|             Mat expected(m.size(), m.type(), cv::Scalar::all(4));
 | |
|             double norm = cvtest::norm(d, expected, NORM_INF);
 | |
| 
 | |
|             EXPECT_EQ(0, norm);
 | |
|         }
 | |
| 
 | |
|         delete[] (unsigned char*)pData_allocated;
 | |
|     }
 | |
| 
 | |
| private:
 | |
|     bool useOpenCL;
 | |
|     bool isOpenCL_enabled;
 | |
| };
 | |
| 
 | |
| TEST_P(getUMat, custom_ptr_align_4Kb)
 | |
| {
 | |
|     custom_ptr_test(4096, 0);
 | |
| }
 | |
| 
 | |
| TEST_P(getUMat, custom_ptr_align_64b)
 | |
| {
 | |
|     custom_ptr_test(4096, 64);
 | |
| }
 | |
| 
 | |
| TEST_P(getUMat, custom_ptr_align_none)
 | |
| {
 | |
|     custom_ptr_test(4096, cv::alignSize(CV_ELEM_SIZE(type), 4));
 | |
| }
 | |
| 
 | |
| TEST_P(getUMat, self_allocated)
 | |
| {
 | |
|     Mat m = Mat(size, type);
 | |
|     m.setTo(cv::Scalar::all(2));
 | |
| 
 | |
|     UMat u = m.getUMat(ACCESS_RW);
 | |
|     cv::add(u, cv::Scalar::all(2), u);
 | |
| 
 | |
|     Mat d = u.getMat(ACCESS_READ);
 | |
| 
 | |
|     Mat expected(m.size(), m.type(), cv::Scalar::all(4));
 | |
|     double norm = cvtest::norm(d, expected, NORM_INF);
 | |
| 
 | |
|     EXPECT_EQ(0, norm);
 | |
| }
 | |
| 
 | |
| INSTANTIATE_TEST_CASE_P(UMat, getUMat, Combine(
 | |
|         Values(CV_8U, CV_64F), // depth
 | |
|         Values(1, 3), // channels
 | |
|         Values(cv::Size(1, 1), cv::Size(255, 255), cv::Size(256, 256)), // Size
 | |
|         Bool() // useOpenCL
 | |
| ));
 | |
| 
 | |
| 
 | |
| 
 | |
| ///////////////////////////////////////////////////////////////// OpenCL ////////////////////////////////////////////////////////////////////////////
 | |
| 
 | |
| #ifdef HAVE_OPENCL
 | |
| TEST(UMat, BufferPoolGrowing)
 | |
| {
 | |
| #ifdef _DEBUG
 | |
|     const int ITERATIONS = 100;
 | |
| #else
 | |
|     const int ITERATIONS = 200;
 | |
| #endif
 | |
|     const Size sz(1920, 1080);
 | |
|     BufferPoolController* c = cv::ocl::getOpenCLAllocator()->getBufferPoolController();
 | |
|     if (c)
 | |
|     {
 | |
|         size_t oldMaxReservedSize = c->getMaxReservedSize();
 | |
|         c->freeAllReservedBuffers();
 | |
|         c->setMaxReservedSize(sz.area() * 10);
 | |
|         for (int i = 0; i < ITERATIONS; i++)
 | |
|         {
 | |
|             UMat um(Size(sz.width + i, sz.height + i), CV_8UC1);
 | |
|             UMat um2(Size(sz.width + 2 * i, sz.height + 2 * i), CV_8UC1);
 | |
|         }
 | |
|         c->setMaxReservedSize(oldMaxReservedSize);
 | |
|         c->freeAllReservedBuffers();
 | |
|     }
 | |
|     else
 | |
|         std::cout << "Skipped, no OpenCL" << std::endl;
 | |
| }
 | |
| #endif
 | |
| 
 | |
| class CV_UMatTest :
 | |
|         public cvtest::BaseTest
 | |
| {
 | |
| public:
 | |
|     CV_UMatTest() {}
 | |
|     ~CV_UMatTest() {}
 | |
| protected:
 | |
|     void run(int);
 | |
| 
 | |
|     struct test_excep
 | |
|     {
 | |
|         test_excep(const string& _s=string("")) : s(_s) { }
 | |
|         string s;
 | |
|     };
 | |
| 
 | |
|     bool TestUMat();
 | |
| 
 | |
|     void checkDiff(const Mat& m1, const Mat& m2, const string& s)
 | |
|     {
 | |
|         if (cvtest::norm(m1, m2, NORM_INF) != 0)
 | |
|             throw test_excep(s);
 | |
|     }
 | |
|     void checkDiffF(const Mat& m1, const Mat& m2, const string& s)
 | |
|     {
 | |
|         if (cvtest::norm(m1, m2, NORM_INF) > 1e-5)
 | |
|             throw test_excep(s);
 | |
|     }
 | |
| };
 | |
| 
 | |
| #define STR(a) STR2(a)
 | |
| #define STR2(a) #a
 | |
| 
 | |
| #define CHECK_DIFF(a, b) checkDiff(a, b, "(" #a ")  !=  (" #b ")  at l." STR(__LINE__))
 | |
| #define CHECK_DIFF_FLT(a, b) checkDiffF(a, b, "(" #a ")  !=(eps)  (" #b ")  at l." STR(__LINE__))
 | |
| 
 | |
| 
 | |
| bool CV_UMatTest::TestUMat()
 | |
| {
 | |
|     try
 | |
|     {
 | |
|         Mat a(100, 100, CV_16SC2), b, c;
 | |
|         randu(a, Scalar::all(-100), Scalar::all(100));
 | |
|         Rect roi(1, 3, 5, 4);
 | |
|         Mat ra(a, roi), rb, rc, rc0;
 | |
|         UMat ua, ura, ub, urb, uc, urc;
 | |
|         a.copyTo(ua);
 | |
|         ua.copyTo(b);
 | |
|         CHECK_DIFF(a, b);
 | |
| 
 | |
|         ura = ua(roi);
 | |
|         ura.copyTo(rb);
 | |
| 
 | |
|         CHECK_DIFF(ra, rb);
 | |
| 
 | |
|         ra += Scalar::all(1.f);
 | |
|         {
 | |
|             Mat temp = ura.getMat(ACCESS_RW);
 | |
|             temp += Scalar::all(1.f);
 | |
|         }
 | |
|         ra.copyTo(rb);
 | |
|         CHECK_DIFF(ra, rb);
 | |
| 
 | |
|         b = a.clone();
 | |
|         ra = a(roi);
 | |
|         rb = b(roi);
 | |
|         randu(b, Scalar::all(-100), Scalar::all(100));
 | |
|         b.copyTo(ub);
 | |
|         urb = ub(roi);
 | |
| 
 | |
|         /*std::cout << "==============================================\nbefore op (CPU):\n";
 | |
|         std::cout << "ra: " << ra << std::endl;
 | |
|         std::cout << "rb: " << rb << std::endl;*/
 | |
| 
 | |
|         ra.copyTo(ura);
 | |
|         rb.copyTo(urb);
 | |
|         ra.release();
 | |
|         rb.release();
 | |
|         ura.copyTo(ra);
 | |
|         urb.copyTo(rb);
 | |
| 
 | |
|         /*std::cout << "==============================================\nbefore op (GPU):\n";
 | |
|         std::cout << "ra: " << ra << std::endl;
 | |
|         std::cout << "rb: " << rb << std::endl;*/
 | |
| 
 | |
|         cv::max(ra, rb, rc);
 | |
|         cv::max(ura, urb, urc);
 | |
|         urc.copyTo(rc0);
 | |
| 
 | |
|         /*std::cout << "==============================================\nafter op:\n";
 | |
|         std::cout << "rc: " << rc << std::endl;
 | |
|         std::cout << "rc0: " << rc0 << std::endl;*/
 | |
| 
 | |
|         CHECK_DIFF(rc0, rc);
 | |
| 
 | |
|         {
 | |
|             UMat tmp = rc0.getUMat(ACCESS_WRITE);
 | |
|             cv::max(ura, urb, tmp);
 | |
|         }
 | |
|         CHECK_DIFF(rc0, rc);
 | |
| 
 | |
|         ura.copyTo(urc);
 | |
|         cv::max(urc, urb, urc);
 | |
|         urc.copyTo(rc0);
 | |
|         CHECK_DIFF(rc0, rc);
 | |
| 
 | |
|         rc = ra ^ rb;
 | |
|         cv::bitwise_xor(ura, urb, urc);
 | |
|         urc.copyTo(rc0);
 | |
| 
 | |
|         /*std::cout << "==============================================\nafter op:\n";
 | |
|         std::cout << "ra: " << rc0 << std::endl;
 | |
|         std::cout << "rc: " << rc << std::endl;*/
 | |
| 
 | |
|         CHECK_DIFF(rc0, rc);
 | |
| 
 | |
|         rc = ra + rb;
 | |
|         cv::add(ura, urb, urc);
 | |
|         urc.copyTo(rc0);
 | |
| 
 | |
|         CHECK_DIFF(rc0, rc);
 | |
| 
 | |
|         cv::subtract(ra, Scalar::all(5), rc);
 | |
|         cv::subtract(ura, Scalar::all(5), urc);
 | |
|         urc.copyTo(rc0);
 | |
| 
 | |
|         CHECK_DIFF(rc0, rc);
 | |
|     }
 | |
|     catch (const test_excep& e)
 | |
|     {
 | |
|         ts->printf(cvtest::TS::LOG, "%s\n", e.s.c_str());
 | |
|         ts->set_failed_test_info(cvtest::TS::FAIL_MISMATCH);
 | |
|         return false;
 | |
|     }
 | |
|     return true;
 | |
| }
 | |
| 
 | |
| void CV_UMatTest::run( int /* start_from */)
 | |
| {
 | |
|     printf("Use OpenCL: %s\nHave OpenCL: %s\n",
 | |
|            cv::ocl::useOpenCL() ? "TRUE" : "FALSE",
 | |
|            cv::ocl::haveOpenCL() ? "TRUE" : "FALSE" );
 | |
| 
 | |
|     if (!TestUMat())
 | |
|         return;
 | |
| 
 | |
|     ts->set_failed_test_info(cvtest::TS::OK);
 | |
| }
 | |
| 
 | |
| TEST(Core_UMat, base) { CV_UMatTest test; test.safe_run(); }
 | |
| 
 | |
| TEST(Core_UMat, getUMat)
 | |
| {
 | |
|     {
 | |
|         int a[3] = { 1, 2, 3 };
 | |
|         Mat m = Mat(1, 1, CV_32SC3, a);
 | |
|         UMat u = m.getUMat(ACCESS_READ);
 | |
|         EXPECT_NE((void*)NULL, u.u);
 | |
|     }
 | |
| 
 | |
|     {
 | |
|         Mat m(10, 10, CV_8UC1), ref;
 | |
|         for (int y = 0; y < m.rows; ++y)
 | |
|         {
 | |
|             uchar * const ptr = m.ptr<uchar>(y);
 | |
|             for (int x = 0; x < m.cols; ++x)
 | |
|                 ptr[x] = (uchar)(x + y * 2);
 | |
|         }
 | |
| 
 | |
|         ref = m.clone();
 | |
|         Rect r(1, 1, 8, 8);
 | |
|         ref(r).setTo(17);
 | |
| 
 | |
|         {
 | |
|             UMat um = m(r).getUMat(ACCESS_WRITE);
 | |
|             um.setTo(17);
 | |
|         }
 | |
| 
 | |
|         double err = cvtest::norm(m, ref, NORM_INF);
 | |
|         if (err > 0)
 | |
|         {
 | |
|             std::cout << "m: " << std::endl << m << std::endl;
 | |
|             std::cout << "ref: " << std::endl << ref << std::endl;
 | |
|         }
 | |
|         EXPECT_EQ(0., err);
 | |
|     }
 | |
| }
 | |
| 
 | |
| TEST(UMat, Sync)
 | |
| {
 | |
|     UMat um(10, 10, CV_8UC1);
 | |
| 
 | |
|     {
 | |
|         Mat m = um.getMat(ACCESS_WRITE);
 | |
|         m.setTo(cv::Scalar::all(17));
 | |
|     }
 | |
| 
 | |
|     um.setTo(cv::Scalar::all(19));
 | |
| 
 | |
|     EXPECT_EQ(0, cvtest::norm(um.getMat(ACCESS_READ), cv::Mat(um.size(), um.type(), 19), NORM_INF));
 | |
| }
 | |
| 
 | |
| TEST(UMat, SyncTemp)
 | |
| {
 | |
|     Mat m(10, 10, CV_8UC1);
 | |
| 
 | |
|     {
 | |
|         UMat um = m.getUMat(ACCESS_WRITE);
 | |
| 
 | |
|         {
 | |
|             Mat m2 = um.getMat(ACCESS_WRITE);
 | |
|             m2.setTo(cv::Scalar::all(17));
 | |
|         }
 | |
| 
 | |
|         um.setTo(cv::Scalar::all(19));
 | |
| 
 | |
|         EXPECT_EQ(0, cvtest::norm(um.getMat(ACCESS_READ), cv::Mat(um.size(), um.type(), 19), NORM_INF));
 | |
|     }
 | |
| }
 | |
| 
 | |
| TEST(UMat, CopyToIfDeviceCopyIsObsolete)
 | |
| {
 | |
|     UMat um(7, 2, CV_8UC1);
 | |
|     Mat m(um.size(), um.type());
 | |
|     m.setTo(Scalar::all(0));
 | |
| 
 | |
|     {
 | |
|         // make obsolete device copy of UMat
 | |
|         Mat temp = um.getMat(ACCESS_WRITE);
 | |
|         temp.setTo(Scalar::all(10));
 | |
|     }
 | |
| 
 | |
|     m.copyTo(um);
 | |
|     um.setTo(Scalar::all(17));
 | |
| 
 | |
|     EXPECT_EQ(0, cvtest::norm(um.getMat(ACCESS_READ), Mat(um.size(), um.type(), 17), NORM_INF));
 | |
| }
 | |
| 
 | |
| TEST(UMat, setOpenCL)
 | |
| {
 | |
| #ifndef HAVE_OPENCL
 | |
|     return; // test skipped
 | |
| #else
 | |
|     // save the current state
 | |
|     bool useOCL = cv::ocl::useOpenCL();
 | |
| 
 | |
|     Mat m = (Mat_<uchar>(3,3)<<0,1,2,3,4,5,6,7,8);
 | |
| 
 | |
|     cv::ocl::setUseOpenCL(true);
 | |
|     UMat um1;
 | |
|     m.copyTo(um1);
 | |
| 
 | |
|     cv::ocl::setUseOpenCL(false);
 | |
|     UMat um2;
 | |
|     m.copyTo(um2);
 | |
| 
 | |
|     cv::ocl::setUseOpenCL(true);
 | |
|     countNonZero(um1);
 | |
|     countNonZero(um2);
 | |
| 
 | |
|     um1.copyTo(um2);
 | |
|     EXPECT_MAT_NEAR(um1, um2, 0);
 | |
|     EXPECT_MAT_NEAR(um1, m, 0);
 | |
|     um2.copyTo(um1);
 | |
|     EXPECT_MAT_NEAR(um1, m, 0);
 | |
|     EXPECT_MAT_NEAR(um1, um2, 0);
 | |
| 
 | |
|     cv::ocl::setUseOpenCL(false);
 | |
|     countNonZero(um1);
 | |
|     countNonZero(um2);
 | |
| 
 | |
|     um1.copyTo(um2);
 | |
|     EXPECT_MAT_NEAR(um1, um2, 0);
 | |
|     EXPECT_MAT_NEAR(um1, m, 0);
 | |
|     um2.copyTo(um1);
 | |
|     EXPECT_MAT_NEAR(um1, um2, 0);
 | |
|     EXPECT_MAT_NEAR(um1, m, 0);
 | |
| 
 | |
|     // reset state to the previous one
 | |
|     cv::ocl::setUseOpenCL(useOCL);
 | |
| #endif
 | |
| }
 | |
| 
 | |
| TEST(UMat, ReadBufferRect)
 | |
| {
 | |
|     UMat m(1, 10000, CV_32FC2, Scalar::all(-1));
 | |
|     Mat t(1, 9000, CV_32FC2, Scalar::all(-200)), t2(1, 9000, CV_32FC2, Scalar::all(-1));
 | |
|     m.colRange(0, 9000).copyTo(t);
 | |
| 
 | |
|     EXPECT_MAT_NEAR(t, t2, 0);
 | |
| }
 | |
| 
 | |
| 
 | |
| // Use iGPU or OPENCV_OPENCL_DEVICE=:CPU: to catch problem
 | |
| TEST(UMat, synchronization_map_unmap)
 | |
| {
 | |
|     class TestParallelLoopBody : public cv::ParallelLoopBody
 | |
|     {
 | |
|         UMat u_;
 | |
|     public:
 | |
|         TestParallelLoopBody(const UMat& u) : u_(u) { }
 | |
|         void operator() (const cv::Range& range) const
 | |
|         {
 | |
|             printf("range: %d, %d -- begin\n", range.start, range.end);
 | |
|             for (int i = 0; i < 10; i++)
 | |
|             {
 | |
|                 printf("%d: %d map...\n", range.start, i);
 | |
|                 Mat m = u_.getMat(cv::ACCESS_READ);
 | |
| 
 | |
|                 printf("%d: %d unmap...\n", range.start, i);
 | |
|                 m.release();
 | |
|             }
 | |
|             printf("range: %d, %d -- end\n", range.start, range.end);
 | |
|         }
 | |
|     };
 | |
|     try
 | |
|     {
 | |
|         UMat u(1000, 1000, CV_32FC1);
 | |
|         parallel_for_(cv::Range(0, 2), TestParallelLoopBody(u));
 | |
|     }
 | |
|     catch (const cv::Exception& e)
 | |
|     {
 | |
|         FAIL() << "Exception: " << e.what();
 | |
|         ADD_FAILURE();
 | |
|     }
 | |
|     catch (...)
 | |
|     {
 | |
|         FAIL() << "Exception!";
 | |
|     }
 | |
| }
 | |
| 
 | |
| 
 | |
| TEST(UMat, async_unmap)
 | |
| {
 | |
|     for (int i = 0; i < 20; i++)
 | |
|     {
 | |
|         try
 | |
|         {
 | |
|             Mat m = Mat(1000, 1000, CV_8UC1);
 | |
|             UMat u = m.getUMat(ACCESS_READ);
 | |
|             UMat dst;
 | |
|             add(u, Scalar::all(0), dst); // start async operation
 | |
|             u.release();
 | |
|             m.release();
 | |
|         }
 | |
|         catch (const cv::Exception& e)
 | |
|         {
 | |
|             printf("i = %d... %s\n", i, e.what());
 | |
|             ADD_FAILURE();
 | |
|         }
 | |
|         catch (...)
 | |
|         {
 | |
|             printf("i = %d...\n", i);
 | |
|             ADD_FAILURE();
 | |
|         }
 | |
|     }
 | |
| }
 | |
| 
 | |
| 
 | |
| TEST(UMat, unmap_in_class)
 | |
| {
 | |
|     class Logic
 | |
|     {
 | |
|     public:
 | |
|         Logic() {}
 | |
|         void processData(InputArray input)
 | |
|         {
 | |
|             Mat m = input.getMat();
 | |
|             {
 | |
|                 Mat dst;
 | |
|                 m.convertTo(dst, CV_32FC1);
 | |
|                 // some additional CPU-based per-pixel processing into dst
 | |
|                 intermediateResult = dst.getUMat(ACCESS_READ); // this violates lifetime of base(dst) / derived (intermediateResult) objects. Use copyTo?
 | |
|                 std::cout << "data processed..." << std::endl;
 | |
|             } // problem is here: dst::~Mat()
 | |
|             std::cout << "leave ProcessData()" << std::endl;
 | |
|         }
 | |
|         UMat getResult() const { return intermediateResult; }
 | |
|     protected:
 | |
|         UMat intermediateResult;
 | |
|     };
 | |
|     try
 | |
|     {
 | |
|         Mat m = Mat(1000, 1000, CV_8UC1);
 | |
|         Logic l;
 | |
|         l.processData(m);
 | |
|         UMat result = l.getResult();
 | |
|     }
 | |
|     catch (const cv::Exception& e)
 | |
|     {
 | |
|         printf("exception... %s\n", e.what());
 | |
|         ADD_FAILURE();
 | |
|     }
 | |
|     catch (...)
 | |
|     {
 | |
|         printf("exception... \n");
 | |
|         ADD_FAILURE();
 | |
|     }
 | |
| }
 | |
| 
 | |
| 
 | |
| TEST(UMat, map_unmap_counting)
 | |
| {
 | |
|     if (!cv::ocl::useOpenCL())
 | |
|     {
 | |
|         std::cout << "OpenCL is not enabled. Skip test" << std::endl;
 | |
|         return;
 | |
|     }
 | |
|     std::cout << "Host memory: " << cv::ocl::Device::getDefault().hostUnifiedMemory() << std::endl;
 | |
|     Mat m(Size(10, 10), CV_8UC1);
 | |
|     UMat um = m.getUMat(ACCESS_RW);
 | |
|     {
 | |
|         Mat d1 = um.getMat(ACCESS_RW);
 | |
|         Mat d2 = um.getMat(ACCESS_RW);
 | |
|         d1.release();
 | |
|     }
 | |
|     void* h = NULL;
 | |
|     EXPECT_NO_THROW(h = um.handle(ACCESS_RW));
 | |
|     std::cout << "Handle: " << h << std::endl;
 | |
| }
 | |
| 
 | |
| 
 | |
| ///////////// oclCleanupCallback threadsafe check (#5062) /////////////////////
 | |
| 
 | |
| // Case 1: reuse of old src Mat in OCL pipe. Hard to catch!
 | |
| OCL_TEST(UMat, DISABLED_OCL_ThreadSafe_CleanupCallback_1_VeryLongTest)
 | |
| {
 | |
|     if (!cv::ocl::useOpenCL())
 | |
|     {
 | |
|         std::cout << "OpenCL is not enabled. Skip test" << std::endl;
 | |
|         return;
 | |
|     }
 | |
|     for (int j = 0; j < 100; j++)
 | |
|     {
 | |
|         const Size srcSize(320, 240);
 | |
|         const int type = CV_8UC1;
 | |
|         const int dtype = CV_16UC1;
 | |
| 
 | |
|         Mat src(srcSize, type);
 | |
|         Mat dst_ref(srcSize, dtype);
 | |
| 
 | |
|         // Generate reference data as additional check
 | |
|         OCL_OFF(src.convertTo(dst_ref, dtype));
 | |
|         cv::ocl::setUseOpenCL(true); // restore OpenCL state
 | |
| 
 | |
|         UMat dst(srcSize, dtype);
 | |
| 
 | |
|         // Use multiple iterations to increase chance of data race catching
 | |
|         for(int k = 0; k < 10000; k++)
 | |
|         {
 | |
|             UMat tmpUMat = src.getUMat(ACCESS_RW);
 | |
|             tmpUMat.convertTo(dst, dtype);
 | |
|             ::cv::ocl::finish(); // force kernel to complete to start cleanup sooner
 | |
|         }
 | |
| 
 | |
|         EXPECT_MAT_NEAR(dst_ref, dst, 1);
 | |
|         printf(".\n"); fflush(stdout);
 | |
|     }
 | |
| }
 | |
| 
 | |
| // Case 2: concurent deallocation of UMatData between UMat and Mat deallocators. Hard to catch!
 | |
| OCL_TEST(UMat, DISABLED_OCL_ThreadSafe_CleanupCallback_2_VeryLongTest)
 | |
| {
 | |
|     if (!cv::ocl::useOpenCL())
 | |
|     {
 | |
|         std::cout << "OpenCL is not enabled. Skip test" << std::endl;
 | |
|         return;
 | |
|     }
 | |
|     for (int j = 0; j < 100; j++)
 | |
|     {
 | |
|         const Size srcSize(320, 240);
 | |
|         const int type = CV_8UC1;
 | |
|         const int dtype = CV_16UC1;
 | |
| 
 | |
|         // This test is only relevant for OCL
 | |
|         UMat dst(srcSize, dtype);
 | |
| 
 | |
|         // Use multiple iterations to increase chance of data race catching
 | |
|         for(int k = 0; k < 10000; k++)
 | |
|         {
 | |
|             Mat src(srcSize, type); // Declare src inside loop now to catch its destruction on stack
 | |
|             {
 | |
|                 UMat tmpUMat = src.getUMat(ACCESS_RW);
 | |
|                 tmpUMat.convertTo(dst, dtype);
 | |
|             }
 | |
|             ::cv::ocl::finish(); // force kernel to complete to start cleanup sooner
 | |
|         }
 | |
|         printf(".\n"); fflush(stdout);
 | |
|     }
 | |
| }
 | |
| 
 | |
| 
 | |
| 
 | |
| TEST(UMat, DISABLED_Test_same_behaviour_read_and_read)
 | |
| {
 | |
|     bool exceptionDetected = false;
 | |
|     try
 | |
|     {
 | |
|         UMat u(Size(10, 10), CV_8UC1);
 | |
|         Mat m = u.getMat(ACCESS_READ);
 | |
|         UMat dst;
 | |
|         add(u, Scalar::all(1), dst);
 | |
|     }
 | |
|     catch (...)
 | |
|     {
 | |
|         exceptionDetected = true;
 | |
|     }
 | |
|     ASSERT_FALSE(exceptionDetected); // no data race, 2+ reads are valid
 | |
| }
 | |
| 
 | |
| // VP: this test (and probably others from same_behaviour series) is not valid in my opinion.
 | |
| TEST(UMat, DISABLED_Test_same_behaviour_read_and_write)
 | |
| {
 | |
|     bool exceptionDetected = false;
 | |
|     try
 | |
|     {
 | |
|         UMat u(Size(10, 10), CV_8UC1);
 | |
|         Mat m = u.getMat(ACCESS_READ);
 | |
|         add(u, Scalar::all(1), u);
 | |
|     }
 | |
|     catch (...)
 | |
|     {
 | |
|         exceptionDetected = true;
 | |
|     }
 | |
|     ASSERT_TRUE(exceptionDetected); // data race
 | |
| }
 | |
| 
 | |
| TEST(UMat, DISABLED_Test_same_behaviour_write_and_read)
 | |
| {
 | |
|     bool exceptionDetected = false;
 | |
|     try
 | |
|     {
 | |
|         UMat u(Size(10, 10), CV_8UC1);
 | |
|         Mat m = u.getMat(ACCESS_WRITE);
 | |
|         UMat dst;
 | |
|         add(u, Scalar::all(1), dst);
 | |
|     }
 | |
|     catch (...)
 | |
|     {
 | |
|         exceptionDetected = true;
 | |
|     }
 | |
|     ASSERT_TRUE(exceptionDetected); // data race
 | |
| }
 | |
| 
 | |
| TEST(UMat, DISABLED_Test_same_behaviour_write_and_write)
 | |
| {
 | |
|     bool exceptionDetected = false;
 | |
|     try
 | |
|     {
 | |
|         UMat u(Size(10, 10), CV_8UC1);
 | |
|         Mat m = u.getMat(ACCESS_WRITE);
 | |
|         add(u, Scalar::all(1), u);
 | |
|     }
 | |
|     catch (...)
 | |
|     {
 | |
|         exceptionDetected = true;
 | |
|     }
 | |
|     ASSERT_TRUE(exceptionDetected); // data race
 | |
| }
 | |
| 
 | |
| TEST(UMat, mat_umat_sync)
 | |
| {
 | |
|     UMat u(10, 10, CV_8UC1, Scalar(1));
 | |
|     {
 | |
|         Mat m = u.getMat(ACCESS_RW).reshape(1);
 | |
|         m.setTo(Scalar(255));
 | |
|     }
 | |
| 
 | |
|     UMat uDiff;
 | |
|     compare(u, 255, uDiff, CMP_NE);
 | |
|     ASSERT_EQ(0, countNonZero(uDiff));
 | |
| }
 | |
| 
 | |
| TEST(UMat, testTempObjects_UMat)
 | |
| {
 | |
|     UMat u(10, 10, CV_8UC1, Scalar(1));
 | |
|     {
 | |
|         UMat u2 = u.getMat(ACCESS_RW).getUMat(ACCESS_RW);
 | |
|         u2.setTo(Scalar(255));
 | |
|     }
 | |
| 
 | |
|     UMat uDiff;
 | |
|     compare(u, 255, uDiff, CMP_NE);
 | |
|     ASSERT_EQ(0, countNonZero(uDiff));
 | |
| }
 | |
| 
 | |
| // Disabled due to failure in VS 2015:
 | |
| //  C++11 is enabled by default ==>
 | |
| //  destructors have implicit 'noexcept(true)' specifier ==>
 | |
| //  throwing exception from destructor is not handled correctly
 | |
| #if defined(_MSC_VER) && _MSC_VER >= 1900 /* MSVC 14 */
 | |
| TEST(UMat, DISABLED_testTempObjects_Mat)
 | |
| #else
 | |
| TEST(UMat, testTempObjects_Mat)
 | |
| #endif
 | |
| {
 | |
|     Mat m(10, 10, CV_8UC1, Scalar(1));
 | |
|     {
 | |
|         Mat m2;
 | |
|         ASSERT_ANY_THROW(m2 = m.getUMat(ACCESS_RW).getMat(ACCESS_RW));
 | |
|     }
 | |
| }
 | |
| 
 | |
| TEST(UMat, testWrongLifetime_UMat)
 | |
| {
 | |
|     UMat u(10, 10, CV_8UC1, Scalar(1));
 | |
|     {
 | |
|         UMat u2 = u.getMat(ACCESS_RW).getUMat(ACCESS_RW);
 | |
|         u.release(); // base object
 | |
|         u2.release(); // derived object, should show warning message
 | |
|     }
 | |
| }
 | |
| 
 | |
| TEST(UMat, testWrongLifetime_Mat)
 | |
| {
 | |
|     Mat m(10, 10, CV_8UC1, Scalar(1));
 | |
|     {
 | |
|         UMat u = m.getUMat(ACCESS_RW);
 | |
|         Mat m2 = u.getMat(ACCESS_RW);
 | |
|         m.release(); // base object
 | |
|         m2.release(); // map of derived object
 | |
|         u.release(); // derived object, should show warning message
 | |
|     }
 | |
| }
 | |
| 
 | |
| } } // namespace cvtest::ocl
 | 
