120 lines
4.5 KiB
C++
120 lines
4.5 KiB
C++
/*M///////////////////////////////////////////////////////////////////////////////////////
|
|
//
|
|
// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
|
|
//
|
|
// 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.
|
|
//
|
|
//
|
|
// License Agreement
|
|
// For Open Source Computer Vision Library
|
|
//
|
|
// Copyright (C) 2000-2008, Intel Corporation, all rights reserved.
|
|
// Copyright (C) 2009, Willow Garage Inc., all rights reserved.
|
|
// Third party copyrights are property of their respective owners.
|
|
//
|
|
// Redistribution and use in source and binary forms, with or without modification,
|
|
// are permitted provided that the following conditions are met:
|
|
//
|
|
// * Redistribution's of source code must retain the above copyright notice,
|
|
// this list of conditions and the following disclaimer.
|
|
//
|
|
// * Redistribution's in binary form must reproduce the above copyright notice,
|
|
// this list of conditions and the following disclaimer in the documentation
|
|
// and/or other materials provided with the distribution.
|
|
//
|
|
// * The name of the copyright holders may not be used to endorse or promote products
|
|
// derived from this software without specific prior written permission.
|
|
//
|
|
// This software is provided by the copyright holders and contributors "as is" and
|
|
// any express or implied warranties, including, but not limited to, the implied
|
|
// warranties of merchantability and fitness for a particular purpose are disclaimed.
|
|
// In no event shall the Intel Corporation or contributors be liable for any direct,
|
|
// indirect, incidental, special, exemplary, or consequential damages
|
|
// (including, but not limited to, procurement of substitute goods or services;
|
|
// loss of use, data, or profits; or business interruption) however caused
|
|
// and on any theory of liability, whether in contract, strict liability,
|
|
// or tort (including negligence or otherwise) arising in any way out of
|
|
// the use of this software, even if advised of the possibility of such damage.
|
|
//
|
|
//M*/
|
|
|
|
#include "test_precomp.hpp"
|
|
#include <string>
|
|
#include <algorithm>
|
|
|
|
using namespace cv;
|
|
using namespace std;
|
|
|
|
TEST(Photo_HdrFusion, regression)
|
|
{
|
|
string folder = string(cvtest::TS::ptr()->get_data_path()) + "hdr/";
|
|
|
|
vector<string>file_names(3);
|
|
file_names[0] = folder + "grand_canal_1_45.jpg";
|
|
file_names[1] = folder + "grand_canal_1_180.jpg";
|
|
file_names[2] = folder + "grand_canal_1_750.jpg";
|
|
vector<Mat>images(3);
|
|
for(int i = 0; i < 3; i++) {
|
|
images[i] = imread(file_names[i]);
|
|
ASSERT_FALSE(images[i].empty()) << "Could not load input image " << file_names[i];
|
|
}
|
|
|
|
string expected_path = folder + "grand_canal_rle.hdr";
|
|
Mat expected = imread(expected_path, -1);
|
|
ASSERT_FALSE(expected.empty()) << "Could not load input image " << expected_path;
|
|
|
|
vector<float>times(3);
|
|
times[0] = 1.0f/45.0f;
|
|
times[1] = 1.0f/180.0f;
|
|
times[2] = 1.0f/750.0f;
|
|
|
|
Mat result;
|
|
makeHDR(images, times, result);
|
|
double max = 1.0;
|
|
minMaxLoc(abs(result - expected), NULL, &max);
|
|
ASSERT_TRUE(max < 0.01);
|
|
|
|
expected_path = folder + "grand_canal_exp_fusion.png";
|
|
expected = imread(expected_path);
|
|
ASSERT_FALSE(expected.empty()) << "Could not load input image " << expected_path;
|
|
exposureFusion(images, result);
|
|
result.convertTo(result, CV_8UC3, 255);
|
|
minMaxLoc(abs(result - expected), NULL, &max);
|
|
ASSERT_FALSE(max > 0);
|
|
}
|
|
|
|
TEST(Photo_Tonemap, regression)
|
|
{
|
|
string folder = string(cvtest::TS::ptr()->get_data_path()) + "hdr/";
|
|
|
|
vector<string>file_names(TONEMAP_COUNT);
|
|
file_names[TONEMAP_DRAGO] = folder + "grand_canal_drago_2.2.png";
|
|
file_names[TONEMAP_REINHARD] = folder + "grand_canal_reinhard_2.2.png";
|
|
file_names[TONEMAP_DURAND] = folder + "grand_canal_durand_2.2.png";
|
|
file_names[TONEMAP_LINEAR] = folder + "grand_canal_linear_map_2.2.png";
|
|
|
|
vector<Mat>images(TONEMAP_COUNT);
|
|
for(int i = 0; i < TONEMAP_COUNT; i++) {
|
|
images[i] = imread(file_names[i]);
|
|
ASSERT_FALSE(images[i].empty()) << "Could not load input image " << file_names[i];
|
|
}
|
|
|
|
string hdr_file_name = folder + "grand_canal_rle.hdr";
|
|
Mat img = imread(hdr_file_name, -1);
|
|
ASSERT_FALSE(img.empty()) << "Could not load input image " << hdr_file_name;
|
|
|
|
vector<float> param(1);
|
|
param[0] = 2.2f;
|
|
|
|
for(int i = TONEMAP_DURAND; i < TONEMAP_COUNT; i++) {
|
|
|
|
Mat result;
|
|
tonemap(img, result, static_cast<tonemap_algorithms>(i), param);
|
|
result.convertTo(result, CV_8UC3, 255);
|
|
double max = 1.0;
|
|
minMaxLoc(abs(result - images[i]), NULL, &max);
|
|
ASSERT_FALSE(max > 0);
|
|
}
|
|
} |