#pragma once

#include <opencv2/opencv.hpp> // all opencv header
#include <string>
#include <fstream>
#include <sstream>
#include <iostream>
#include <unordered_map>
#include <hdrplus/bayer_image.h>
#include <dirent.h>
#include <hdrplus/params.h>
#include <hdrplus/burst.h>

namespace hdrplus
{
	uint16_t uGammaCompress_1pix(float x, float threshold, float gainMin, float gainMax, float exponent);
	uint16_t uGammaDecompress_1pix(float x, float threshold, float gainMin, float gainMax, float exponent);
	cv::Mat uGammaCompress_(cv::Mat m, float threshold, float gainMin, float gainMax, float exponent);
	cv::Mat uGammaDecompress_(cv::Mat m, float threshold, float gainMin, float gainMax, float exponent);
	cv::Mat gammasRGB(cv::Mat img, bool mode);


	class finish
	{
	public:
		cv::Mat mergedBayer; // merged image from Merge Module
		std::string burstPath; // path to burst images
		std::vector<std::string> rawPathList; // a list or array of the path to all burst imgs under burst Path
		int refIdx; // index of the reference img
		Parameters params;
		cv::Mat rawReference;
		// LibRaw libraw_processor_finish;
		bayer_image* refBayer;

		std::string mergedImgPath;
		finish()
		{
			refBayer = NULL;
		}

		// please use this initialization after merging part finish
		finish(std::string burstPath, cv::Mat mergedBayer, int refIdx) {
			refBayer = NULL;
			this->refIdx = refIdx;
			this->burstPath = burstPath;
			this->mergedBayer = mergedBayer;
		}

		// for local testing only
		finish(std::string burstPath, std::string mergedBayerPath, int refIdx) {
			this->refIdx = refIdx;
			this->burstPath = burstPath;
			this->mergedBayer = loadFromCSV(mergedBayerPath, CV_16UC1);//
			load_rawPathList(burstPath);
			refBayer = new bayer_image(this->rawPathList[refIdx]);
			this->rawReference = refBayer->raw_image;//;grayscale_image

			// initialize parameters in libraw_processor_finish
			setLibRawParams();
			showParams();

			std::cout << "Finish init() finished!" << std::endl;
		}



		~finish()
		{
			if (refBayer != NULL)
			{
				delete refBayer;
				refBayer = NULL;
			}
		}

		// finish pipeline func
		// void process(std::string burstPath, cv::Mat mergedBayer,int refIdx);
		void process(const hdrplus::burst& burst_images, cv::Mat& finalOutputImage);

		// replace Mat a with Mat b
		void copy_mat_16U(cv::Mat& A, cv::Mat B);
		void copy_rawImg2libraw(std::shared_ptr<LibRaw>& libraw_ptr, cv::Mat B);

		// postprocess
		// cv::Mat postprocess(std::shared_ptr<LibRaw>& libraw_ptr);

		void showImg(cv::Mat img)
		{
			int ch = CV_MAT_CN(CV_8UC1);

			// cv::Mat tmp(4208,3120,CV_16UC1);
			cv::Mat tmp(img);
			// uint16_t* ptr_tmp = (uint16_t*)tmp.data;
			// uint16_t* ptr_img = (uint16_t*)img.data;
			// // col major to row major
			// for(int r = 0; r < tmp.rows; r++) {
			//     for(int c = 0; c < tmp.cols; c++) {
			//         *(ptr_tmp+r*tmp.cols+c) = *(ptr_img+c*tmp.rows+r)/2048.0*255.0;
			//     }
			// }
			// std::cout<<"height="<<tmp.rows<<std::endl;
			// std::cout<<"width="<<tmp.cols<<std::endl;
			// cv::transpose(tmp, tmp);

			uint16_t* ptr = (uint16_t*)tmp.data;
			for (int r = 0; r < tmp.rows; r++) {
				for (int c = 0; c < tmp.cols; c++) {
					*(ptr + r * tmp.cols + c) = *(ptr + r * tmp.cols + c) / 2048.0*255.0;
				}
			}

			tmp = tmp.reshape(ch);
			tmp.convertTo(tmp, CV_8UC1);
			cv::imshow("test", tmp);
			cv::imwrite("test2.jpg", tmp);
			cv::waitKey(0);
			std::cout << this->mergedBayer.size() << std::endl;
		}

		void showMat(cv::Mat img) {
			std::cout << "size=" << img.size() << std::endl;
			std::cout << "type=" << img.type() << std::endl;
		}

		void showParams()
		{
			std::cout << "Parameters:" << std::endl;
			std::cout << "tuning_ltmGain = " << this->params.tuning.ltmGain << std::endl;
			std::cout << "tuning_gtmContrast = " << this->params.tuning.gtmContrast << std::endl;
			for (auto key_val : this->params.flags) {
				std::cout << key_val.first << "," << key_val.second << std::endl;
			}
			std::cout << "demosaic_algorithm = " << refBayer->libraw_processor->imgdata.params.user_qual << std::endl;
			std::cout << "half_size = " << refBayer->libraw_processor->imgdata.params.half_size << std::endl;
			std::cout << "use_camera_wb = " << refBayer->libraw_processor->imgdata.params.use_camera_wb << std::endl;
			std::cout << "use_auto_wb = " << refBayer->libraw_processor->imgdata.params.use_auto_wb << std::endl;
			std::cout << "no_auto_bright = " << refBayer->libraw_processor->imgdata.params.no_auto_bright << std::endl;
			std::cout << "output_color = " << refBayer->libraw_processor->imgdata.params.output_color << std::endl;
			std::cout << "gamma[0] = " << refBayer->libraw_processor->imgdata.params.gamm[0] << std::endl;
			std::cout << "gamma[1] = " << refBayer->libraw_processor->imgdata.params.gamm[1] << std::endl;
			std::cout << "output_bps = " << refBayer->libraw_processor->imgdata.params.output_bps << std::endl;

			// std::cout<<"demosaic_algorithm = "<<libraw_processor_finish.imgdata.params.user_qual<<std::endl;
			// std::cout<<"half_size = "<<libraw_processor_finish.imgdata.params.half_size<<std::endl;
			// std::cout<<"use_camera_wb = "<<libraw_processor_finish.imgdata.params.use_camera_wb<<std::endl;
			// std::cout<<"use_auto_wb = "<<libraw_processor_finish.imgdata.params.use_auto_wb<<std::endl;
			// std::cout<<"no_auto_bright = "<<libraw_processor_finish.imgdata.params.no_auto_bright<<std::endl;
			// std::cout<<"output_color = "<<libraw_processor_finish.imgdata.params.output_color <<std::endl;
			// std::cout<<"gamma[0] = "<<libraw_processor_finish.imgdata.params.gamm[0]<<std::endl;
			// std::cout<<"gamma[1] = "<<libraw_processor_finish.imgdata.params.gamm[1]<<std::endl;
			// std::cout<<"output_bps = "<<libraw_processor_finish.imgdata.params.output_bps<<std::endl;

			std::cout << "====================" << std::endl;
		}

		void showRawPathList() {
			std::cout << "RawPathList:" << std::endl;
			for (auto pth : this->rawPathList) {
				std::cout << pth << std::endl;
			}
			std::cout << "====================" << std::endl;
		}




	private:
		cv::Mat loadFromCSV(const std::string& path, int opencv_type)
		{
			cv::Mat m;
			std::ifstream csvFile(path);

			std::string line;

			while (getline(csvFile, line))
			{
				std::vector<int> dvals;
				std::stringstream ss(line);
				std::string val;
				// int count=0;
				while (getline(ss, val, ','))
				{
					dvals.push_back(stod(val));//*255.0/2048.0
					// count++;
				}
				// std::cout<<count<<std::endl;
				cv::Mat mline(dvals, true);
				cv::transpose(mline, mline);

				m.push_back(mline);
			}
			int ch = CV_MAT_CN(opencv_type);

			m = m.reshape(ch);
			m.convertTo(m, opencv_type);

			return m;
		}

		void load_rawPathList(std::string burstPath)
		{
			DIR *pDir; // pointer to root
			struct dirent *ptr;
			if (!(pDir = opendir(burstPath.c_str())))
			{
				std::cout << "root dir not found!" << std::endl;
				return;
			}
			while ((ptr = readdir(pDir)) != nullptr)
			{
				// ptr will move to the next file automatically
				std::string sub_file = burstPath + "/" + ptr->d_name; // current filepath that ptr points to
				if (ptr->d_type != 8 && ptr->d_type != 4) { // not normal file or dir
					return;
				}
				// only need normal files
				if (ptr->d_type == 8) {
					if (strcmp(ptr->d_name, ".") != 0 && strcmp(ptr->d_name, "..") != 0) {
						if (strstr(ptr->d_name, ".dng")) {
							rawPathList.emplace_back(sub_file);
						}
					}
				}
			}
			// close root dir
			closedir(pDir);
		}

		void setLibRawParams() {
			refBayer->libraw_processor->imgdata.params.user_qual = params.rawpyArgs.demosaic_algorithm;
			refBayer->libraw_processor->imgdata.params.half_size = params.rawpyArgs.half_size;
			refBayer->libraw_processor->imgdata.params.use_camera_wb = params.rawpyArgs.use_camera_wb;
			refBayer->libraw_processor->imgdata.params.use_auto_wb = params.rawpyArgs.use_auto_wb;
			refBayer->libraw_processor->imgdata.params.no_auto_bright = params.rawpyArgs.no_auto_bright;
			refBayer->libraw_processor->imgdata.params.output_color = params.rawpyArgs.output_color;
			refBayer->libraw_processor->imgdata.params.gamm[0] = params.rawpyArgs.gamma[0];
			refBayer->libraw_processor->imgdata.params.gamm[1] = params.rawpyArgs.gamma[1];
			refBayer->libraw_processor->imgdata.params.output_bps = params.rawpyArgs.output_bps;

			// libraw_processor_finish.imgdata.params.user_qual = params.rawpyArgs.demosaic_algorithm;
			// libraw_processor_finish.imgdata.params.half_size = params.rawpyArgs.half_size;
			// libraw_processor_finish.imgdata.params.use_camera_wb = params.rawpyArgs.use_camera_wb;
			// libraw_processor_finish.imgdata.params.use_auto_wb = params.rawpyArgs.use_auto_wb;
			// libraw_processor_finish.imgdata.params.no_auto_bright = params.rawpyArgs.no_auto_bright;
			// libraw_processor_finish.imgdata.params.output_color = params.rawpyArgs.output_color;
			// libraw_processor_finish.imgdata.params.gamm[0] = params.rawpyArgs.gamma[0];
			// libraw_processor_finish.imgdata.params.gamm[1] = params.rawpyArgs.gamma[1];
			// libraw_processor_finish.imgdata.params.output_bps = params.rawpyArgs.output_bps;
		}


	};

} // namespace hdrplus