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Open Source Computer Vision Library
https://opencv.org/
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236 lines
10 KiB
236 lines
10 KiB
14 years ago
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/*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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// Intel License Agreement
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// For Open Source Computer Vision Library
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//
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// Copyright (C) 2000, Intel Corporation, 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 Intel Corporation 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 <iostream>
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#include <limits>
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#include "test_precomp.hpp"
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#define CHECK(pred, err) if (!(pred)) { \
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ts->printf(cvtest::TS::CONSOLE, "Fail: \"%s\" at line: %d\n", #pred, __LINE__); \
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ts->set_failed_test_info(err); \
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return; }
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using namespace cv;
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using namespace std;
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struct CV_GpuBitwiseTest: public cvtest::BaseTest
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{
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CV_GpuBitwiseTest() {}
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void run(int)
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{
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int rows, cols;
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bool double_ok = gpu::TargetArchs::builtWith(gpu::NATIVE_DOUBLE) &&
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gpu::DeviceInfo().supports(gpu::NATIVE_DOUBLE);
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int depth_end = double_ok ? CV_64F : CV_32F;
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for (int depth = CV_8U; depth <= depth_end; ++depth)
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for (int cn = 1; cn <= 4; ++cn)
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for (int attempt = 0; attempt < 3; ++attempt)
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{
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rows = 1 + rand() % 100;
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cols = 1 + rand() % 100;
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test_bitwise_not(rows, cols, CV_MAKETYPE(depth, cn));
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test_bitwise_or(rows, cols, CV_MAKETYPE(depth, cn));
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test_bitwise_and(rows, cols, CV_MAKETYPE(depth, cn));
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test_bitwise_xor(rows, cols, CV_MAKETYPE(depth, cn));
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}
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}
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void test_bitwise_not(int rows, int cols, int type)
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{
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Mat src(rows, cols, type);
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RNG rng;
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for (int i = 0; i < src.rows; ++i)
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{
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Mat row(1, src.cols * src.elemSize(), CV_8U, src.ptr(i));
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rng.fill(row, RNG::UNIFORM, Scalar(0), Scalar(255));
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}
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Mat dst_gold = ~src;
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gpu::GpuMat mask(src.size(), CV_8U);
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mask.setTo(Scalar(1));
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gpu::GpuMat dst;
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gpu::bitwise_not(gpu::GpuMat(src), dst);
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CHECK(dst_gold.size() == dst.size(), cvtest::TS::FAIL_INVALID_OUTPUT);
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CHECK(dst_gold.type() == dst.type(), cvtest::TS::FAIL_INVALID_OUTPUT);
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Mat dsth(dst);
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for (int i = 0; i < dst_gold.rows; ++i)
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CHECK(memcmp(dst_gold.ptr(i), dsth.ptr(i), dst_gold.cols * dst_gold.elemSize()) == 0, cvtest::TS::FAIL_INVALID_OUTPUT);
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dst.setTo(Scalar::all(0));
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gpu::bitwise_not(gpu::GpuMat(src), dst, mask);
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CHECK(dst_gold.size() == dst.size(), cvtest::TS::FAIL_INVALID_OUTPUT);
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CHECK(dst_gold.type() == dst.type(), cvtest::TS::FAIL_INVALID_OUTPUT);
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dsth = dst;
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for (int i = 0; i < dst_gold.rows; ++i)
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CHECK(memcmp(dst_gold.ptr(i), dsth.ptr(i), dst_gold.cols * dst_gold.elemSize()) == 0, cvtest::TS::FAIL_INVALID_OUTPUT)
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}
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void test_bitwise_or(int rows, int cols, int type)
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{
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Mat src1(rows, cols, type);
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Mat src2(rows, cols, type);
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RNG rng;
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for (int i = 0; i < src1.rows; ++i)
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{
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Mat row1(1, src1.cols * src1.elemSize(), CV_8U, src1.ptr(i));
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rng.fill(row1, RNG::UNIFORM, Scalar(0), Scalar(255));
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Mat row2(1, src2.cols * src2.elemSize(), CV_8U, src2.ptr(i));
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rng.fill(row2, RNG::UNIFORM, Scalar(0), Scalar(255));
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}
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Mat dst_gold = src1 | src2;
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gpu::GpuMat dst = gpu::GpuMat(src1) | gpu::GpuMat(src2);
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CHECK(dst_gold.size() == dst.size(), cvtest::TS::FAIL_INVALID_OUTPUT);
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CHECK(dst_gold.type() == dst.type(), cvtest::TS::FAIL_INVALID_OUTPUT);
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Mat dsth(dst);
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for (int i = 0; i < dst_gold.rows; ++i)
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CHECK(memcmp(dst_gold.ptr(i), dsth.ptr(i), dst_gold.cols * dst_gold.elemSize()) == 0, cvtest::TS::FAIL_INVALID_OUTPUT)
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Mat mask(src1.size(), CV_8U);
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randu(mask, Scalar(0), Scalar(255));
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Mat dst_gold2(dst_gold.size(), dst_gold.type()); dst_gold2.setTo(Scalar::all(0));
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gpu::GpuMat dst2(dst.size(), dst.type()); dst2.setTo(Scalar::all(0));
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bitwise_or(src1, src2, dst_gold2, mask);
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gpu::bitwise_or(gpu::GpuMat(src1), gpu::GpuMat(src2), dst2, gpu::GpuMat(mask));
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CHECK(dst_gold2.size() == dst2.size(), cvtest::TS::FAIL_INVALID_OUTPUT);
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CHECK(dst_gold2.type() == dst2.type(), cvtest::TS::FAIL_INVALID_OUTPUT);
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dsth = dst2;
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for (int i = 0; i < dst_gold.rows; ++i)
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CHECK(memcmp(dst_gold2.ptr(i), dsth.ptr(i), dst_gold2.cols * dst_gold2.elemSize()) == 0, cvtest::TS::FAIL_INVALID_OUTPUT)
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}
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void test_bitwise_and(int rows, int cols, int type)
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{
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Mat src1(rows, cols, type);
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Mat src2(rows, cols, type);
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RNG rng;
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for (int i = 0; i < src1.rows; ++i)
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{
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Mat row1(1, src1.cols * src1.elemSize(), CV_8U, src1.ptr(i));
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rng.fill(row1, RNG::UNIFORM, Scalar(0), Scalar(255));
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Mat row2(1, src2.cols * src2.elemSize(), CV_8U, src2.ptr(i));
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rng.fill(row2, RNG::UNIFORM, Scalar(0), Scalar(255));
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}
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Mat dst_gold = src1 & src2;
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gpu::GpuMat dst = gpu::GpuMat(src1) & gpu::GpuMat(src2);
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CHECK(dst_gold.size() == dst.size(), cvtest::TS::FAIL_INVALID_OUTPUT);
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CHECK(dst_gold.type() == dst.type(), cvtest::TS::FAIL_INVALID_OUTPUT);
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Mat dsth(dst);
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for (int i = 0; i < dst_gold.rows; ++i)
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CHECK(memcmp(dst_gold.ptr(i), dsth.ptr(i), dst_gold.cols * dst_gold.elemSize()) == 0, cvtest::TS::FAIL_INVALID_OUTPUT)
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Mat mask(src1.size(), CV_8U);
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randu(mask, Scalar(0), Scalar(255));
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Mat dst_gold2(dst_gold.size(), dst_gold.type()); dst_gold2.setTo(Scalar::all(0));
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gpu::GpuMat dst2(dst.size(), dst.type()); dst2.setTo(Scalar::all(0));
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bitwise_and(src1, src2, dst_gold2, mask);
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gpu::bitwise_and(gpu::GpuMat(src1), gpu::GpuMat(src2), dst2, gpu::GpuMat(mask));
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CHECK(dst_gold2.size() == dst2.size(), cvtest::TS::FAIL_INVALID_OUTPUT);
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CHECK(dst_gold2.type() == dst2.type(), cvtest::TS::FAIL_INVALID_OUTPUT);
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dsth = dst2;
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for (int i = 0; i < dst_gold.rows; ++i)
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CHECK(memcmp(dst_gold2.ptr(i), dsth.ptr(i), dst_gold2.cols * dst_gold2.elemSize()) == 0, cvtest::TS::FAIL_INVALID_OUTPUT)
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}
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void test_bitwise_xor(int rows, int cols, int type)
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{
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Mat src1(rows, cols, type);
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Mat src2(rows, cols, type);
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RNG rng;
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for (int i = 0; i < src1.rows; ++i)
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{
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Mat row1(1, src1.cols * src1.elemSize(), CV_8U, src1.ptr(i));
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rng.fill(row1, RNG::UNIFORM, Scalar(0), Scalar(255));
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Mat row2(1, src2.cols * src2.elemSize(), CV_8U, src2.ptr(i));
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rng.fill(row2, RNG::UNIFORM, Scalar(0), Scalar(255));
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}
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Mat dst_gold = src1 ^ src2;
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gpu::GpuMat dst = gpu::GpuMat(src1) ^ gpu::GpuMat(src2);
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CHECK(dst_gold.size() == dst.size(), cvtest::TS::FAIL_INVALID_OUTPUT);
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CHECK(dst_gold.type() == dst.type(), cvtest::TS::FAIL_INVALID_OUTPUT);
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Mat dsth(dst);
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for (int i = 0; i < dst_gold.rows; ++i)
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CHECK(memcmp(dst_gold.ptr(i), dsth.ptr(i), dst_gold.cols * dst_gold.elemSize()) == 0, cvtest::TS::FAIL_INVALID_OUTPUT)
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Mat mask(src1.size(), CV_8U);
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randu(mask, Scalar(0), Scalar(255));
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Mat dst_gold2(dst_gold.size(), dst_gold.type()); dst_gold2.setTo(Scalar::all(0));
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gpu::GpuMat dst2(dst.size(), dst.type()); dst2.setTo(Scalar::all(0));
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bitwise_xor(src1, src2, dst_gold2, mask);
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gpu::bitwise_xor(gpu::GpuMat(src1), gpu::GpuMat(src2), dst2, gpu::GpuMat(mask));
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CHECK(dst_gold2.size() == dst2.size(), cvtest::TS::FAIL_INVALID_OUTPUT);
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CHECK(dst_gold2.type() == dst2.type(), cvtest::TS::FAIL_INVALID_OUTPUT);
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dsth = dst2;
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for (int i = 0; i < dst_gold.rows; ++i)
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CHECK(memcmp(dst_gold2.ptr(i), dsth.ptr(i), dst_gold2.cols * dst_gold2.elemSize()) == 0, cvtest::TS::FAIL_INVALID_OUTPUT)
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}
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};
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TEST(BitwiseOperations, accuracy) { CV_GpuBitwiseTest test; test; }
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