opencv/modules/photo/test/test_hdr.cpp

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#include "test_precomp.hpp"
#include <string>
#include <algorithm>
#include <fstream>

using namespace cv;
using namespace std;

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);
	ASSERT_FALSE(max > threshold);
}

TEST(Photo_Tonemap, regression)
{
	string test_path = string(cvtest::TS::ptr()->get_data_path()) + "hdr/";
	
	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);
	result.convertTo(result, CV_8UC3, 255);
	checkEqual(result, expected, 0);

	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);

	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);

	Ptr<TonemapReinhardDevlin> reinhard_devlin = createTonemapReinhardDevlin(gamma);
	reinhard_devlin->process(img, result);
	loadImage(test_path + "reinhard_devlin.png", expected);
	result.convertTo(result, CV_8UC3, 255);
	checkEqual(result, expected, 0);
}



//void loadExposureSeq(String fuse_path, vector<Mat>& images, vector<float>& times = vector<float>())
//{
//	ifstream list_file(fuse_path + "list.txt");
//	ASSERT_TRUE(list_file.is_open());
//	string name; 
//	float val;
//	while(list_file >> name >> val) {
//		Mat img = imread(fuse_path + name);
//		ASSERT_FALSE(img.empty()) << "Could not load input image " << fuse_path + name;
//		images.push_back(img);
//		times.push_back(1 / val);
//	}
//	list_file.close();
//}
////
////TEST(Photo_MergeMertens, regression)
////{
////	string test_path = string(cvtest::TS::ptr()->get_data_path()) + "hdr/";
////	string fuse_path = test_path + "fusion/";
////
////	vector<Mat> images;
////	loadExposureSeq(fuse_path, images);
////
////	MergeMertens merge;
////
////	Mat result, expected;
////	loadImage(test_path + "exp_fusion.png", expected);
////	merge.process(images, result);
////	result.convertTo(result, CV_8UC3, 255);
////	checkEqual(expected, result, 0);
////}
//
//TEST(Photo_Debevec, regression)
//{
//	string test_path = string(cvtest::TS::ptr()->get_data_path()) + "hdr/";
//	string fuse_path = test_path + "fusion/";
//	
//	vector<float> times;
//	vector<Mat> images;
//
//	loadExposureSeq(fuse_path, images, times);
//
//	Mat response, expected(256, 3, CV_32F);
//	ifstream resp_file(test_path + "response.csv");
//	for(int i = 0; i < 256; i++) {
//		for(int channel = 0; channel < 3; channel++) {
//			resp_file >> expected.at<float>(i, channel);
//			resp_file.ignore(1);
//		}
//	}
//	resp_file.close();
//
//	CalibrateDebevec calib;
//	MergeDebevec merge;
//
//	//calib.process(images, response, times);
//	//checkEqual(expected, response, 0.001);
//	//
//	Mat result;
//	loadImage(test_path + "no_calibration.hdr", expected);
//	merge.process(images, result, times);
//	checkEqual(expected, result, 0.01);
//
//	//loadImage(test_path + "rle.hdr", expected);
//	//merge.process(images, result, times, response);
//	//checkEqual(expected, result, 0.01);
//}
//
//TEST(Photo_Tonemap, regression)
//{
//	initModule_photo();
//	string test_path = string(cvtest::TS::ptr()->get_data_path()) + "hdr/tonemap/";
//	Mat img;
//	loadImage(test_path + "../rle.hdr", img);
//
//	vector<String> algorithms;
//	Algorithm::getList(algorithms);
//	for(size_t i = 0; i < algorithms.size(); i++) {
//		String str = algorithms[i];
//		size_t dot = str.find('.');
//		if(dot != String::npos && str.substr(0, dot).compare("Tonemap") == 0) {
//			String algo_name = str.substr(dot + 1, str.size());
//		    Mat expected;
//			loadImage(test_path + algo_name.toLowerCase() + ".png", expected);
//			Ptr<Tonemap> mapper = Tonemap::create(algo_name);	
//	    	ASSERT_FALSE(mapper.empty()) << algo_name;
//			Mat result;
//			mapper->process(img, result);
//			result.convertTo(result, CV_8UC3, 255);
//			checkEqual(expected, result, 0);
//		}
//	}
////}
////
////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 = imread(file_name);
////	ASSERT_FALSE(img.empty()) << "Could not load input image " << file_name;
////	cvtColor(img, img, COLOR_RGB2GRAY);
////
////	int max_bits = 5;
////	int max_shift = 32;
////	srand(static_cast<unsigned>(time(0)));
////	int errors = 0;
////
////	AlignMTB align(max_bits);
////
////	for(int i = 0; i < TESTS_COUNT; i++) {
////		Point shift(rand() % max_shift, rand() % max_shift);
////		Mat res;
////		align.shiftMat(img, shift, res);
////		Point calc = align.getExpShift(img, res);
////		errors += (calc != -shift);
////	}
////	ASSERT_TRUE(errors < 5);
////}