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216 lines
8.3 KiB
C++
216 lines
8.3 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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// 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 "test_precomp.hpp"
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namespace opencv_test { namespace {
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TEST(Imgproc_Hist_Calc, calcHist_regression_11544)
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{
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cv::Mat1w m = cv::Mat1w::zeros(10, 10);
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int n_images = 1;
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int channels[] = { 0 };
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cv::Mat mask;
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cv::MatND hist1, hist2;
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cv::MatND hist1_opt, hist2_opt;
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int dims = 1;
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int hist_size[] = { 1000 };
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float range1[] = { 0, 900 };
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float range2[] = { 0, 1000 };
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const float* ranges1[] = { range1 };
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const float* ranges2[] = { range2 };
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setUseOptimized(false);
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cv::calcHist(&m, n_images, channels, mask, hist1, dims, hist_size, ranges1);
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cv::calcHist(&m, n_images, channels, mask, hist2, dims, hist_size, ranges2);
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setUseOptimized(true);
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cv::calcHist(&m, n_images, channels, mask, hist1_opt, dims, hist_size, ranges1);
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cv::calcHist(&m, n_images, channels, mask, hist2_opt, dims, hist_size, ranges2);
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for(int i = 0; i < 1000; i++)
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{
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EXPECT_EQ(hist1.at<float>(i), hist1_opt.at<float>(i)) << i;
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EXPECT_EQ(hist2.at<float>(i), hist2_opt.at<float>(i)) << i;
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}
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}
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TEST(Imgproc_Hist_Calc, badarg)
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{
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const int channels[] = {0};
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float range1[] = {0, 10};
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float range2[] = {10, 20};
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const float * ranges[] = {range1, range2};
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Mat img = cv::Mat::zeros(10, 10, CV_8UC1);
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Mat imgInt = cv::Mat::zeros(10, 10, CV_32SC1);
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Mat hist;
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const int hist_size[] = { 100, 100 };
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// base run
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EXPECT_NO_THROW(cv::calcHist(&img, 1, channels, noArray(), hist, 1, hist_size, ranges, true));
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// bad parameters
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EXPECT_THROW(cv::calcHist(NULL, 1, channels, noArray(), hist, 1, hist_size, ranges, true), cv::Exception);
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EXPECT_THROW(cv::calcHist(&img, 0, channels, noArray(), hist, 1, hist_size, ranges, true), cv::Exception);
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EXPECT_THROW(cv::calcHist(&img, 1, NULL, noArray(), hist, 2, hist_size, ranges, true), cv::Exception);
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EXPECT_THROW(cv::calcHist(&img, 1, channels, noArray(), noArray(), 1, hist_size, ranges, true), cv::Exception);
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EXPECT_THROW(cv::calcHist(&img, 1, channels, noArray(), hist, -1, hist_size, ranges, true), cv::Exception);
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EXPECT_THROW(cv::calcHist(&img, 1, channels, noArray(), hist, 1, NULL, ranges, true), cv::Exception);
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EXPECT_THROW(cv::calcHist(&imgInt, 1, channels, noArray(), hist, 1, hist_size, NULL, true), cv::Exception);
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// special case
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EXPECT_NO_THROW(cv::calcHist(&img, 1, channels, noArray(), hist, 1, hist_size, NULL, true));
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Mat backProj;
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// base run
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EXPECT_NO_THROW(cv::calcBackProject(&img, 1, channels, hist, backProj, ranges, 1, true));
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// bad parameters
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EXPECT_THROW(cv::calcBackProject(NULL, 1, channels, hist, backProj, ranges, 1, true), cv::Exception);
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EXPECT_THROW(cv::calcBackProject(&img, 0, channels, hist, backProj, ranges, 1, true), cv::Exception);
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EXPECT_THROW(cv::calcBackProject(&img, 1, channels, noArray(), backProj, ranges, 1, true), cv::Exception);
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EXPECT_THROW(cv::calcBackProject(&img, 1, channels, hist, noArray(), ranges, 1, true), cv::Exception);
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EXPECT_THROW(cv::calcBackProject(&imgInt, 1, channels, hist, backProj, NULL, 1, true), cv::Exception);
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// special case
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EXPECT_NO_THROW(cv::calcBackProject(&img, 1, channels, hist, backProj, NULL, 1, true));
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}
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TEST(Imgproc_Hist_Calc, IPP_ranges_with_equal_exponent_21595)
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{
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const int channels[] = { 0 };
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float range1[] = { -0.5f, 1.5f };
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const float* ranges[] = { range1 };
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const int hist_size[] = { 2 };
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uint8_t m[1][6] = { { 0, 1, 0, 1 , 1, 1 } };
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cv::Mat images_u = Mat(1, 6, CV_8UC1, m);
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cv::Mat histogram_u;
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cv::calcHist(&images_u, 1, channels, noArray(), histogram_u, 1, hist_size, ranges);
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ASSERT_EQ(histogram_u.at<float>(0), 2.f) << "0 not counts correctly, res: " << histogram_u.at<float>(0);
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ASSERT_EQ(histogram_u.at<float>(1), 4.f) << "1 not counts correctly, res: " << histogram_u.at<float>(0);
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}
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TEST(Imgproc_Hist_Calc, IPP_ranges_with_nonequal_exponent_21595)
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{
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const int channels[] = { 0 };
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float range1[] = { -1.3f, 1.5f };
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const float* ranges[] = { range1 };
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const int hist_size[] = { 3 };
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uint8_t m[1][6] = { { 0, 1, 0, 1 , 1, 1 } };
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cv::Mat images_u = Mat(1, 6, CV_8UC1, m);
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cv::Mat histogram_u;
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cv::calcHist(&images_u, 1, channels, noArray(), histogram_u, 1, hist_size, ranges);
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ASSERT_EQ(histogram_u.at<float>(0), 0.f) << "not equal to zero, res: " << histogram_u.at<float>(0);
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ASSERT_EQ(histogram_u.at<float>(1), 2.f) << "0 not counts correctly, res: " << histogram_u.at<float>(1);
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ASSERT_EQ(histogram_u.at<float>(2), 4.f) << "1 not counts correctly, res: " << histogram_u.at<float>(2);
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}
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////////////////////////////////////////// equalizeHist() /////////////////////////////////////////
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void equalizeHistReference(const Mat& src, Mat& dst)
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{
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std::vector<int> hist(256, 0);
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for (int y = 0; y < src.rows; y++)
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{
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const uchar* srow = src.ptr(y);
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for (int x = 0; x < src.cols; x++)
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{
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hist[srow[x]]++;
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}
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}
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int first = 0;
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while (!hist[first]) ++first;
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int total = (int)src.total();
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if (hist[first] == total)
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{
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dst.setTo(first);
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return;
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}
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std::vector<uchar> lut(256);
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lut[first] = 0;
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float scale = (255.f)/(total - hist[first]);
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int sum = 0;
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for (int i = first + 1; i < 256; ++i)
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{
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sum += hist[i];
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lut[i] = saturate_cast<uchar>(sum * scale);
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}
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cv::LUT(src, lut, dst);
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}
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typedef ::testing::TestWithParam<std::tuple<cv::Size, int>> Imgproc_Equalize_Hist;
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TEST_P(Imgproc_Equalize_Hist, accuracy)
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{
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auto p = GetParam();
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cv::Size size = std::get<0>(p);
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int idx = std::get<1>(p);
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RNG &rng = cvtest::TS::ptr()->get_rng();
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rng.state += idx;
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cv::Mat src(size, CV_8U);
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cvtest::randUni(rng, src, Scalar::all(0), Scalar::all(255));
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cv::Mat dst, gold;
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equalizeHistReference(src, gold);
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cv::equalizeHist(src, dst);
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ASSERT_EQ(CV_8UC1, dst.type());
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ASSERT_EQ(gold.size(), dst.size());
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EXPECT_MAT_NEAR(dst, gold, 1);
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EXPECT_MAT_N_DIFF(dst, gold, 0.05 * size.area()); // The 5% range could be accomodated to HAL
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}
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INSTANTIATE_TEST_CASE_P(Imgproc_Hist, Imgproc_Equalize_Hist, ::testing::Combine(
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::testing::Values(cv::Size(123, 321), cv::Size(256, 256), cv::Size(1024, 768)),
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::testing::Range(0, 10)));
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}} // namespace
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/* End Of File */
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