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vendor: OpenCV 5.0.0 snapshot at 40738fb16ceddb5fb3fea747585f7ce6abb0605b

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/*M///////////////////////////////////////////////////////////////////////////////////////
//
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//
// By downloading, copying, installing or using the software you agree to this license.
// If you do not agree to this license, do not download, install,
// copy or use the software.
//
//
// Intel License Agreement
// For Open Source Computer Vision Library
//
// Copyright (C) 2000, Intel Corporation, all rights reserved.
// Third party copyrights are property of their respective owners.
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// Redistribution and use in source and binary forms, with or without modification,
// are permitted provided that the following conditions are met:
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// this list of conditions and the following disclaimer.
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// derived from this software without specific prior written permission.
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//M*/
#include "test_precomp.hpp"
namespace opencv_test { namespace {
TEST(Imgproc_Hist_Calc, calcHist_regression_11544)
{
cv::Mat1w m = cv::Mat1w::zeros(10, 10);
int n_images = 1;
int channels[] = { 0 };
cv::Mat mask;
cv::MatND hist1, hist2;
cv::MatND hist1_opt, hist2_opt;
int dims = 1;
int hist_size[] = { 1000 };
float range1[] = { 0, 900 };
float range2[] = { 0, 1000 };
const float* ranges1[] = { range1 };
const float* ranges2[] = { range2 };
setUseOptimized(false);
cv::calcHist(&m, n_images, channels, mask, hist1, dims, hist_size, ranges1);
cv::calcHist(&m, n_images, channels, mask, hist2, dims, hist_size, ranges2);
setUseOptimized(true);
cv::calcHist(&m, n_images, channels, mask, hist1_opt, dims, hist_size, ranges1);
cv::calcHist(&m, n_images, channels, mask, hist2_opt, dims, hist_size, ranges2);
for(int i = 0; i < 1000; i++)
{
EXPECT_EQ(hist1.at<float>(i), hist1_opt.at<float>(i)) << i;
EXPECT_EQ(hist2.at<float>(i), hist2_opt.at<float>(i)) << i;
}
}
TEST(Imgproc_Hist_Calc, badarg)
{
const int channels[] = {0};
float range1[] = {0, 10};
float range2[] = {10, 20};
const float * ranges[] = {range1, range2};
Mat img = cv::Mat::zeros(10, 10, CV_8UC1);
Mat imgInt = cv::Mat::zeros(10, 10, CV_32SC1);
Mat hist;
const int hist_size[] = { 100, 100 };
// base run
EXPECT_NO_THROW(cv::calcHist(&img, 1, channels, noArray(), hist, 1, hist_size, ranges, true));
// bad parameters
EXPECT_THROW(cv::calcHist(NULL, 1, channels, noArray(), hist, 1, hist_size, ranges, true), cv::Exception);
EXPECT_THROW(cv::calcHist(&img, 0, channels, noArray(), hist, 1, hist_size, ranges, true), cv::Exception);
EXPECT_THROW(cv::calcHist(&img, 1, NULL, noArray(), hist, 2, hist_size, ranges, true), cv::Exception);
EXPECT_THROW(cv::calcHist(&img, 1, channels, noArray(), noArray(), 1, hist_size, ranges, true), cv::Exception);
EXPECT_THROW(cv::calcHist(&img, 1, channels, noArray(), hist, -1, hist_size, ranges, true), cv::Exception);
EXPECT_THROW(cv::calcHist(&img, 1, channels, noArray(), hist, 1, NULL, ranges, true), cv::Exception);
EXPECT_THROW(cv::calcHist(&imgInt, 1, channels, noArray(), hist, 1, hist_size, NULL, true), cv::Exception);
// special case
EXPECT_NO_THROW(cv::calcHist(&img, 1, channels, noArray(), hist, 1, hist_size, NULL, true));
Mat backProj;
// base run
EXPECT_NO_THROW(cv::calcBackProject(&img, 1, channels, hist, backProj, ranges, 1, true));
// bad parameters
EXPECT_THROW(cv::calcBackProject(NULL, 1, channels, hist, backProj, ranges, 1, true), cv::Exception);
EXPECT_THROW(cv::calcBackProject(&img, 0, channels, hist, backProj, ranges, 1, true), cv::Exception);
EXPECT_THROW(cv::calcBackProject(&img, 1, channels, noArray(), backProj, ranges, 1, true), cv::Exception);
EXPECT_THROW(cv::calcBackProject(&img, 1, channels, hist, noArray(), ranges, 1, true), cv::Exception);
EXPECT_THROW(cv::calcBackProject(&imgInt, 1, channels, hist, backProj, NULL, 1, true), cv::Exception);
// special case
EXPECT_NO_THROW(cv::calcBackProject(&img, 1, channels, hist, backProj, NULL, 1, true));
}
TEST(Imgproc_Hist_Calc, IPP_ranges_with_equal_exponent_21595)
{
const int channels[] = { 0 };
float range1[] = { -0.5f, 1.5f };
const float* ranges[] = { range1 };
const int hist_size[] = { 2 };
uint8_t m[1][6] = { { 0, 1, 0, 1 , 1, 1 } };
cv::Mat images_u = Mat(1, 6, CV_8UC1, m);
cv::Mat histogram_u;
cv::calcHist(&images_u, 1, channels, noArray(), histogram_u, 1, hist_size, ranges);
ASSERT_EQ(histogram_u.at<float>(0), 2.f) << "0 not counts correctly, res: " << histogram_u.at<float>(0);
ASSERT_EQ(histogram_u.at<float>(1), 4.f) << "1 not counts correctly, res: " << histogram_u.at<float>(0);
}
TEST(Imgproc_Hist_Calc, IPP_ranges_with_nonequal_exponent_21595)
{
const int channels[] = { 0 };
float range1[] = { -1.3f, 1.5f };
const float* ranges[] = { range1 };
const int hist_size[] = { 3 };
uint8_t m[1][6] = { { 0, 1, 0, 1 , 1, 1 } };
cv::Mat images_u = Mat(1, 6, CV_8UC1, m);
cv::Mat histogram_u;
cv::calcHist(&images_u, 1, channels, noArray(), histogram_u, 1, hist_size, ranges);
ASSERT_EQ(histogram_u.at<float>(0), 0.f) << "not equal to zero, res: " << histogram_u.at<float>(0);
ASSERT_EQ(histogram_u.at<float>(1), 2.f) << "0 not counts correctly, res: " << histogram_u.at<float>(1);
ASSERT_EQ(histogram_u.at<float>(2), 4.f) << "1 not counts correctly, res: " << histogram_u.at<float>(2);
}
////////////////////////////////////////// equalizeHist() /////////////////////////////////////////
void equalizeHistReference(const Mat& src, Mat& dst)
{
std::vector<int> hist(256, 0);
for (int y = 0; y < src.rows; y++)
{
const uchar* srow = src.ptr(y);
for (int x = 0; x < src.cols; x++)
{
hist[srow[x]]++;
}
}
int first = 0;
while (!hist[first]) ++first;
int total = (int)src.total();
if (hist[first] == total)
{
dst.setTo(first);
return;
}
std::vector<uchar> lut(256);
lut[first] = 0;
float scale = (255.f)/(total - hist[first]);
int sum = 0;
for (int i = first + 1; i < 256; ++i)
{
sum += hist[i];
lut[i] = saturate_cast<uchar>(sum * scale);
}
cv::LUT(src, lut, dst);
}
typedef ::testing::TestWithParam<std::tuple<cv::Size, int>> Imgproc_Equalize_Hist;
TEST_P(Imgproc_Equalize_Hist, accuracy)
{
auto p = GetParam();
cv::Size size = std::get<0>(p);
int idx = std::get<1>(p);
RNG &rng = cvtest::TS::ptr()->get_rng();
rng.state += idx;
cv::Mat src(size, CV_8U);
cvtest::randUni(rng, src, Scalar::all(0), Scalar::all(255));
cv::Mat dst, gold;
equalizeHistReference(src, gold);
cv::equalizeHist(src, dst);
ASSERT_EQ(CV_8UC1, dst.type());
ASSERT_EQ(gold.size(), dst.size());
EXPECT_MAT_NEAR(dst, gold, 1);
EXPECT_MAT_N_DIFF(dst, gold, 0.05 * size.area()); // The 5% range could be accomodated to HAL
}
INSTANTIATE_TEST_CASE_P(Imgproc_Hist, Imgproc_Equalize_Hist, ::testing::Combine(
::testing::Values(cv::Size(123, 321), cv::Size(256, 256), cv::Size(1024, 768)),
::testing::Range(0, 10)));
// See https://github.com/opencv/opencv/issues/24757
TEST(Imgproc_Hist_Compare, intersect_regression_24757)
{
cv::Mat src1 = cv::Mat::zeros(128,1, CV_32FC1);
cv::Mat src2 = cv::Mat(128,1, CV_32FC1, cv::Scalar(std::numeric_limits<double>::max()));
// Ideal result Wrong result
src1.at<float>(32 * 0,0) = +1.0f; // work = +1.0 +1.0
src1.at<float>(32 * 1,0) = +55555555.5f; // work = +55555556.5 +55555555.5
src1.at<float>(32 * 2,0) = -55555555.5f; // work = +1.0 0.0
src1.at<float>(32 * 3,0) = -1.0f; // work = 0.0 -1.0
EXPECT_DOUBLE_EQ(compareHist(src1, src2, cv::HISTCMP_INTERSECT), 0.0);
}
}} // namespace
/* End Of File */