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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) << 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();
}

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 + "reinharddevlin.png", expected);
	result.convertTo(result, CV_8UC3, 255);
	checkEqual(result, expected, 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;
	loadImage(file_name, img);
	cvtColor(img, img, COLOR_RGB2GRAY);

	int max_bits = 5;
	int max_shift = 32;
	srand(static_cast<unsigned>(time(0)));
	int errors = 0;

	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);
}