opencv/modules/photo/test/test_hdr.cpp

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/*M///////////////////////////////////////////////////////////////////////////////////////
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#include "test_precomp.hpp"
#include <string>
#include <algorithm>
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#include <fstream>
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using namespace cv;
using namespace std;
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void loadImage(string path, Mat &img)
{
img = imread(path, -1);
ASSERT_FALSE(img.empty()) << "Could not load input image " << path;
}
void checkEqual(Mat img0, Mat img1, double threshold)
{
double max = 1.0;
minMaxLoc(abs(img0 - img1), NULL, &max);
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ASSERT_FALSE(max > threshold) << max;
}
void loadExposureSeq(String path, vector<Mat>& images, vector<float>& times = vector<float>())
{
ifstream list_file(path + "list.txt");
ASSERT_TRUE(list_file.is_open());
string name;
float val;
while(list_file >> name >> val) {
Mat img = imread(path + name);
ASSERT_FALSE(img.empty()) << "Could not load input image " << path + name;
images.push_back(img);
times.push_back(1 / val);
}
list_file.close();
}
void loadResponseCSV(String path, Mat& response)
{
response = Mat(256, 3, CV_32F);
ifstream resp_file(path);
for(int i = 0; i < 256; i++) {
for(int channel = 0; channel < 3; channel++) {
resp_file >> response.at<float>(i, channel);
resp_file.ignore(1);
}
}
resp_file.close();
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}
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TEST(Photo_Tonemap, regression)
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{
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string test_path = string(cvtest::TS::ptr()->get_data_path()) + "hdr/";
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Mat img, expected, result;
loadImage(test_path + "rle.hdr", img);
float gamma = 2.2f;
test_path += "tonemap/";
Ptr<TonemapLinear> linear = createTonemapLinear(gamma);
linear->process(img, result);
loadImage(test_path + "linear.png", expected);
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result.convertTo(result, CV_8UC3, 255);
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checkEqual(result, expected, 0);
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Ptr<TonemapDrago> drago = createTonemapDrago(gamma);
drago->process(img, result);
loadImage(test_path + "drago.png", expected);
result.convertTo(result, CV_8UC3, 255);
checkEqual(result, expected, 0);
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Ptr<TonemapDurand> durand = createTonemapDurand(gamma);
durand->process(img, result);
loadImage(test_path + "durand.png", expected);
result.convertTo(result, CV_8UC3, 255);
checkEqual(result, expected, 0);
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Ptr<TonemapReinhardDevlin> reinhard_devlin = createTonemapReinhardDevlin(gamma);
reinhard_devlin->process(img, result);
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loadImage(test_path + "reinharddevlin.png", expected);
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result.convertTo(result, CV_8UC3, 255);
checkEqual(result, expected, 0);
}
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TEST(Photo_AlignMTB, regression)
{
const int TESTS_COUNT = 100;
string folder = string(cvtest::TS::ptr()->get_data_path()) + "shared/";
string file_name = folder + "lena.png";
Mat img;
loadImage(file_name, img);
cvtColor(img, img, COLOR_RGB2GRAY);
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int max_bits = 5;
int max_shift = 32;
srand(static_cast<unsigned>(time(0)));
int errors = 0;
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Ptr<AlignMTB> align = createAlignMTB(max_bits);
for(int i = 0; i < TESTS_COUNT; i++) {
Point shift(rand() % max_shift, rand() % max_shift);
Mat res;
align->shiftMat(img, res, shift);
Point calc;
align->calculateShift(img, res, calc);
errors += (calc != -shift);
}
ASSERT_TRUE(errors < 5) << errors << " errors";
}
TEST(Photo_MergeMertens, regression)
{
string test_path = string(cvtest::TS::ptr()->get_data_path()) + "hdr/";
vector<Mat> images;
loadExposureSeq(test_path + "exposures/", images);
Ptr<MergeMertens> merge = createMergeMertens();
Mat result, expected;
loadImage(test_path + "merge/mertens.png", expected);
merge->process(images, result);
result.convertTo(result, CV_8UC3, 255);
checkEqual(expected, result, 0);
}
TEST(Photo_MergeDebevec, regression)
{
string test_path = string(cvtest::TS::ptr()->get_data_path()) + "hdr/";
vector<Mat> images;
vector<float> times;
Mat response;
loadExposureSeq(test_path + "exposures/", images, times);
loadResponseCSV(test_path + "exposures/response.csv", response);
Ptr<MergeDebevec> merge = createMergeDebevec();
Mat result, expected;
loadImage(test_path + "merge/debevec.exr", expected);
merge->process(images, result, times, response);
checkEqual(expected, result, 1e-3f);
}
TEST(Photo_CalibrateDebevec, regression)
{
string test_path = string(cvtest::TS::ptr()->get_data_path()) + "hdr/";
vector<Mat> images;
vector<float> times;
Mat expected, response;
loadExposureSeq(test_path + "exposures/", images, times);
loadResponseCSV(test_path + "calibrate/debevec.csv", expected);
Ptr<CalibrateDebevec> calibrate = createCalibrateDebevec();
srand(1);
calibrate->process(images, response, times);
checkEqual(expected, response, 1e-3f);
}