waifu2x-caffe/common/waifu2x.cpp

#include "waifu2x.h"
#include <caffe/caffe.hpp>
#include <cudnn.h>
#include <mutex>
#include <opencv2/opencv.hpp>
#include <rapidjson/document.h>
#include <tclap/CmdLine.h>
#include <boost/filesystem.hpp>
#include <boost/algorithm/string.hpp>
#include <chrono>
#include <cuda_runtime.h>

#include <boost/iostreams/stream.hpp>
#include <boost/iostreams/device/file_descriptor.hpp>
#include <google/protobuf/io/coded_stream.h>
#include <google/protobuf/io/zero_copy_stream_impl.h>
#include <google/protobuf/text_format.h>
#include <fcntl.h>
#ifdef _MSC_VER
#include <io.h>
#endif

#define STB_IMAGE_IMPLEMENTATION
#include <stb_image.h>
#define STB_IMAGE_WRITE_IMPLEMENTATION
#include <stb_image_write.h>

#if defined(WIN32) || defined(WIN64)
#include <Windows.h>
#endif

#define CV_VERSION_STR CVAUX_STR(CV_MAJOR_VERSION) CVAUX_STR(CV_MINOR_VERSION) CVAUX_STR(CV_SUBMINOR_VERSION)

// <20>r<EFBFBD><72><EFBFBD>h<EFBFBD><68><EFBFBD>[<5B>h
#ifdef _DEBUG
#define CV_EXT_STR "d.lib"
#else
#define CV_EXT_STR ".lib"
#endif

#ifdef _MSC_VER
#ifdef _DEBUG
#pragma comment(lib, "caffe-d.lib")
#pragma comment(lib, "proto-d.lib")
#pragma comment(lib, "libboost_system-vc120-mt-gd-1_59.lib")
#pragma comment(lib, "libboost_thread-vc120-mt-gd-1_59.lib")
#pragma comment(lib, "libboost_filesystem-vc120-mt-gd-1_59.lib")
#pragma comment(lib, "glogd.lib")
#pragma comment(lib, "gflagsd.lib")
#pragma comment(lib, "libprotobufd.lib")
#pragma comment(lib, "libhdf5_hl_D.lib")
#pragma comment(lib, "libhdf5_D.lib")
#pragma comment(lib, "zlibstaticd.lib")
#pragma comment(lib, "libopenblas.dll.a")
#pragma comment(lib, "cudart.lib")
#pragma comment(lib, "curand.lib")
#pragma comment(lib, "cublas.lib")
#pragma comment(lib, "cudnn.lib")

#pragma comment(lib, "opencv_core" CV_VERSION_STR CV_EXT_STR)
#pragma comment(lib, "opencv_imgcodecs" CV_VERSION_STR CV_EXT_STR)
#pragma comment(lib, "opencv_imgproc" CV_VERSION_STR CV_EXT_STR)
//#pragma comment(lib, "IlmImf" CV_EXT_STR)
//#pragma comment(lib, "libjasper" CV_EXT_STR)
//#pragma comment(lib, "libjpeg" CV_EXT_STR)
//#pragma comment(lib, "libpng" CV_EXT_STR)
//#pragma comment(lib, "libtiff" CV_EXT_STR)
//#pragma comment(lib, "libwebp" CV_EXT_STR)
//#pragma comment(lib, "ippicvmt.lib")

#pragma comment(lib, "libboost_iostreams-vc120-mt-gd-1_59.lib")
#else
#pragma comment(lib, "caffe.lib")
#pragma comment(lib, "proto.lib")
#pragma comment(lib, "libboost_system-vc120-mt-1_59.lib")
#pragma comment(lib, "libboost_thread-vc120-mt-1_59.lib")
#pragma comment(lib, "libboost_filesystem-vc120-mt-1_59.lib")
#pragma comment(lib, "glog.lib")
#pragma comment(lib, "gflags.lib")
#pragma comment(lib, "libprotobuf.lib")
#pragma comment(lib, "libhdf5_hl.lib")
#pragma comment(lib, "libhdf5.lib")
#pragma comment(lib, "zlibstatic.lib")
#pragma comment(lib, "libopenblas.dll.a")
#pragma comment(lib, "cudart.lib")
#pragma comment(lib, "curand.lib")
#pragma comment(lib, "cublas.lib")
#pragma comment(lib, "cudnn.lib")

#pragma comment(lib, "opencv_core" CV_VERSION_STR CV_EXT_STR)
#pragma comment(lib, "opencv_imgcodecs" CV_VERSION_STR CV_EXT_STR)
#pragma comment(lib, "opencv_imgproc" CV_VERSION_STR CV_EXT_STR)
//#pragma comment(lib, "IlmImf" CV_EXT_STR)
//#pragma comment(lib, "libjasper" CV_EXT_STR)
//#pragma comment(lib, "libjpeg" CV_EXT_STR)
//#pragma comment(lib, "libpng" CV_EXT_STR)
//#pragma comment(lib, "libtiff" CV_EXT_STR)
//#pragma comment(lib, "libwebp" CV_EXT_STR)
//#pragma comment(lib, "ippicvmt.lib")

#pragma comment(lib, "libboost_iostreams-vc120-mt-1_59.lib")
#endif
#endif

// <20><><EFBFBD>͉摜<CD89>̃I<CC83>t<EFBFBD>Z<EFBFBD>b<EFBFBD>g
const int offset = 0;
// srcnn.prototxt<78>Œ<EFBFBD><C592>`<60><><EFBFBD>ꂽ<EFBFBD><EA82BD><EFBFBD>C<EFBFBD><43><EFBFBD>[<5B>̐<EFBFBD>
const int layer_num = 7;

const int ConvertMode = CV_RGB2YUV;
const int ConvertInverseMode = CV_YUV2RGB;

// <20>Œ<EFBFBD><C592><EFBFBD><EFBFBD>K<EFBFBD>v<EFBFBD><76>CUDA<44>h<EFBFBD><68><EFBFBD>C<EFBFBD>o<EFBFBD>[<5B>̃o<CC83>[<5B>W<EFBFBD><57><EFBFBD><EFBFBD>
const int MinCudaDriverVersion = 7050;

// float<61>ȉ摜<C889><E6919C>uint8_t<5F>ȉ摜<C889>ɕϊ<C995><CF8A><EFBFBD><EFBFBD><EFBFBD><EFBFBD>ۂ̎l<CC8E>̌ܓ<CC8C><DC93>Ɏg<C98E><67><EFBFBD>l
// https://github.com/nagadomi/waifu2x/commit/797b45ae23665a1c5e3c481c018e48e6f0d0e383
const double clip_eps8 = (1.0 / 255.0) * 0.5 - (1.0e-7 * (1.0 / 255.0) * 0.5);
const double clip_eps16 = (1.0 / 65535.0) * 0.5 - (1.0e-7 * (1.0 / 65535.0) * 0.5);
const double clip_eps32 = 1.0 * 0.5 - (1.0e-7 * 0.5);

const int kProtoReadBytesLimit = INT_MAX;  // Max size of 2 GB minus 1 byte.

static std::once_flag waifu2x_once_flag;
static std::once_flag waifu2x_cudnn_once_flag;
static std::once_flag waifu2x_cuda_once_flag;

const std::vector<Waifu2x::stOutputExtentionElement> Waifu2x::OutputExtentionList =
{
	{ L".png", { 8, 16 }, boost::optional<int>(), boost::optional<int>(), boost::optional<int>(), boost::optional<int>() },
	{ L".bmp", { 8 }, boost::optional<int>(), boost::optional<int>(), boost::optional<int>(), boost::optional<int>() },
	{ L".jpg", { 8 }, 0, 100, 95, cv::IMWRITE_JPEG_QUALITY },
	{ L".jp2", { 8, 16 }, boost::optional<int>(), boost::optional<int>(), boost::optional<int>(), boost::optional<int>() },
	{ L".sr", { 8 }, boost::optional<int>(), boost::optional<int>(), boost::optional<int>(), boost::optional<int>() },
	{ L".tif", { 8, 16, 32 }, boost::optional<int>(), boost::optional<int>(), boost::optional<int>(), boost::optional<int>() },
	{ L".hdr", { 8, 16, 32 }, boost::optional<int>(), boost::optional<int>(), boost::optional<int>(), boost::optional<int>() },
	{ L".exr", { 8, 16, 32 }, boost::optional<int>(), boost::optional<int>(), boost::optional<int>(), boost::optional<int>() },
	{ L".ppm", { 8, 16 }, boost::optional<int>(), boost::optional<int>(), boost::optional<int>(), boost::optional<int>() },
	{ L".webp", { 8 }, 1, 100, 100, cv::IMWRITE_WEBP_QUALITY },
	{ L".tga", { 8 }, boost::optional<int>(), boost::optional<int>(), boost::optional<int>(), boost::optional<int>() },
};

#ifndef CUDA_CHECK_WAIFU2X
#define CUDA_CHECK_WAIFU2X(condition) \
 do { \
    cudaError_t error = condition; \
    if(error != cudaSuccess) throw error; \
 } while (0)
#endif

#define CUDA_HOST_SAFE_FREE(ptr) \
	do { \
		if (ptr) { \
			cudaFreeHost(ptr); \
			ptr = nullptr; \
		} \
	} while (0)

#define SAFE_DELETE_WAIFU2X(ptr) \
	do { \
		if (ptr) { \
			delete [] ptr; \
			ptr = nullptr; \
		} \
	} while (0)

namespace
{
	class IgnoreErrorCV
	{
	private:
		static int handleError(int status, const char* func_name,
			const char* err_msg, const char* file_name,
			int line, void* userdata)
		{
			return 0;
		}

	public:
		IgnoreErrorCV()
		{
			cv::redirectError(handleError);
		}
	};

	IgnoreErrorCV g_IgnoreErrorCV;
}

template<typename BufType>
static bool writeFile(boost::iostreams::stream<boost::iostreams::file_descriptor> &os, const std::vector<BufType> &buf)
{
	if (!os)
		return false;

	const auto WriteSize = sizeof(BufType) * buf.size();
	os.write((const char *)buf.data(), WriteSize);
	if (os.fail())
		return false;

	return true;
}

template<typename BufType>
static bool writeFile(const boost::filesystem::path &path, std::vector<BufType> &buf)
{
	boost::iostreams::stream<boost::iostreams::file_descriptor> os;

	try
	{
		os.open(path, std::ios_base::out | std::ios_base::binary | std::ios_base::trunc);
	}
	catch (...)
	{
		return false;
	}

	return writeFile(os, buf);
}

template<typename BufType>
static bool readFile(boost::iostreams::stream<boost::iostreams::file_descriptor_source> &is, std::vector<BufType> &buf)
{
	if (!is)
		return false;

	const auto size = is.seekg(0, std::ios::end).tellg();
	is.seekg(0, std::ios::beg);

	buf.resize((size / sizeof(BufType)) + (size % sizeof(BufType)));
	is.read(buf.data(), size);
	if (is.gcount() != size)
		return false;

	return true;
}

template<typename BufType>
static bool readFile(const boost::filesystem::path &path, std::vector<BufType> &buf)
{
	boost::iostreams::stream<boost::iostreams::file_descriptor_source> is;

	try
	{
		is.open(path, std::ios_base::in | std::ios_base::binary);
	}
	catch (...)
	{
		return false;
	}

	return readFile(is, buf);
}

static Waifu2x::eWaifu2xError readProtoText(const boost::filesystem::path &path, ::google::protobuf::Message* proto)
{
	boost::iostreams::stream<boost::iostreams::file_descriptor_source> is;

	try
	{
		is.open(path, std::ios_base::in);
	}
	catch (...)
	{
		return Waifu2x::eWaifu2xError_FailedOpenModelFile;
	}

	if (!is)
		return Waifu2x::eWaifu2xError_FailedOpenModelFile;

	std::vector<char> tmp;
	if (!readFile(is, tmp))
		return Waifu2x::eWaifu2xError_FailedParseModelFile;

	google::protobuf::io::ArrayInputStream input(tmp.data(), tmp.size());
	const bool success = google::protobuf::TextFormat::Parse(&input, proto);

	if (!success)
		return Waifu2x::eWaifu2xError_FailedParseModelFile;

	return Waifu2x::eWaifu2xError_OK;
}

static Waifu2x::eWaifu2xError readProtoBinary(const boost::filesystem::path &path, ::google::protobuf::Message* proto)
{
	boost::iostreams::stream<boost::iostreams::file_descriptor_source> is;
	
	try
	{
		is.open(path, std::ios_base::in | std::ios_base::binary);
	}
	catch (...)
	{
		return Waifu2x::eWaifu2xError_FailedOpenModelFile;
	}

	if (!is)
		return Waifu2x::eWaifu2xError_FailedOpenModelFile;

	std::vector<char> tmp;
	if (!readFile(is, tmp))
		return Waifu2x::eWaifu2xError_FailedParseModelFile;

	google::protobuf::io::ArrayInputStream input(tmp.data(), tmp.size());

	google::protobuf::io::CodedInputStream coded_input(&input);
	coded_input.SetTotalBytesLimit(kProtoReadBytesLimit, 536870912);

	const bool success = proto->ParseFromCodedStream(&coded_input);
	if (!success)
		return Waifu2x::eWaifu2xError_FailedParseModelFile;

	return Waifu2x::eWaifu2xError_OK;
}

static Waifu2x::eWaifu2xError writeProtoBinary(const ::google::protobuf::Message& proto, const boost::filesystem::path &path)
{
	boost::iostreams::stream<boost::iostreams::file_descriptor> os;

	try
	{
		os.open(path, std::ios_base::out | std::ios_base::binary | std::ios_base::trunc);
	}
	catch (...)
	{
		return Waifu2x::eWaifu2xError_FailedOpenModelFile;
	}

	if (!os)
		return Waifu2x::eWaifu2xError_FailedWriteModelFile;

	if (!proto.SerializePartialToOstream(&os))
		return Waifu2x::eWaifu2xError_FailedWriteModelFile;

	return Waifu2x::eWaifu2xError_OK;
}


Waifu2x::Waifu2x() : is_inited(false), isCuda(false), input_block(nullptr), dummy_data(nullptr), output_block(nullptr)
{
}

Waifu2x::~Waifu2x()
{
	destroy();
}

// cuDNN<4E><4E><EFBFBD>g<EFBFBD><67><EFBFBD>邩<EFBFBD>`<60>F<EFBFBD>b<EFBFBD>N<EFBFBD>B<EFBFBD><42><EFBFBD><EFBFBD>Windows<77>̂<EFBFBD>
Waifu2x::eWaifu2xcuDNNError Waifu2x::can_use_cuDNN()
{
	static eWaifu2xcuDNNError cuDNNFlag = eWaifu2xcuDNNError_NotFind;
	std::call_once(waifu2x_cudnn_once_flag, [&]()
	{
#if defined(WIN32) || defined(WIN64)
		HMODULE hModule = LoadLibrary(TEXT(CUDNN_DLL_NAME));
		if (hModule != NULL)
		{
			typedef cudnnStatus_t(__stdcall * cudnnCreateType)(cudnnHandle_t *);
			typedef cudnnStatus_t(__stdcall * cudnnDestroyType)(cudnnHandle_t);
			typedef uint64_t(__stdcall * cudnnGetVersionType)();

			cudnnCreateType cudnnCreateFunc = (cudnnCreateType)GetProcAddress(hModule, "cudnnCreate");
			cudnnDestroyType cudnnDestroyFunc = (cudnnDestroyType)GetProcAddress(hModule, "cudnnDestroy");
			cudnnGetVersionType cudnnGetVersionFunc = (cudnnGetVersionType)GetProcAddress(hModule, "cudnnGetVersion");
			if (cudnnCreateFunc != nullptr && cudnnDestroyFunc != nullptr && cudnnGetVersionFunc != nullptr)
			{
				if (cudnnGetVersionFunc() >= 3000)
				{
					cudnnHandle_t h;
					if (cudnnCreateFunc(&h) == CUDNN_STATUS_SUCCESS)
					{
						if (cudnnDestroyFunc(h) == CUDNN_STATUS_SUCCESS)
							cuDNNFlag = eWaifu2xcuDNNError_OK;
						else
							cuDNNFlag = eWaifu2xcuDNNError_CannotCreate;
					}
					else
						cuDNNFlag = eWaifu2xcuDNNError_CannotCreate;
				}
				else
					cuDNNFlag = eWaifu2xcuDNNError_OldVersion;
			}
			else
				cuDNNFlag = eWaifu2xcuDNNError_NotFind;

			FreeLibrary(hModule);
		}
#endif
	});

	return cuDNNFlag;
}

// CUDA<44><41><EFBFBD>g<EFBFBD><67><EFBFBD>邩<EFBFBD>`<60>F<EFBFBD>b<EFBFBD>N
Waifu2x::eWaifu2xCudaError Waifu2x::can_use_CUDA()
{
	static eWaifu2xCudaError CudaFlag = eWaifu2xCudaError_NotFind;
	std::call_once(waifu2x_cuda_once_flag, [&]()
	{
		int driverVersion = 0;
		if (cudaDriverGetVersion(&driverVersion) == cudaSuccess)
		{
			if (driverVersion > 0)
			{
				int runtimeVersion;
				if (cudaRuntimeGetVersion(&runtimeVersion) == cudaSuccess)
				{
					if (runtimeVersion >= MinCudaDriverVersion && driverVersion >= runtimeVersion)
						CudaFlag = eWaifu2xCudaError_OK;
					else
						CudaFlag = eWaifu2xCudaError_OldVersion;
				}
				else
					CudaFlag = eWaifu2xCudaError_NotFind;
			}
			else
				CudaFlag = eWaifu2xCudaError_NotFind;
		}
		else
			CudaFlag = eWaifu2xCudaError_NotFind;
	});

	return CudaFlag;
}

void Waifu2x::init_liblary()
{
}

void Waifu2x::quit_liblary()
{
}

cv::Mat Waifu2x::LoadMat(const boost::filesystem::path &path)
{
	cv::Mat mat;
	LoadMat(mat, path);

	return mat;
}

Waifu2x::eWaifu2xError Waifu2x::AlphaMakeBorder(std::vector<cv::Mat> &planes, const cv::Mat &alpha, const int offset)
{
	// <20><><EFBFBD>̃J<CC83>[<5B>l<EFBFBD><6C><EFBFBD>Ɖ摜<C689>̏􍞂݂<F48D9E82><DD82>s<EFBFBD><73><EFBFBD>ƁA(x, y)<29>𒆐S<F0928690>Ƃ<EFBFBD><C682><EFBFBD>3<EFBFBD>~3<>̈<EFBFBD><CC88>̍<EFBFBD><CC8D>v<EFBFBD>l<EFBFBD><6C><EFBFBD><EFBFBD><EFBFBD>܂<EFBFBD>
	const static cv::Mat sum2d_kernel = (cv::Mat_<double>(3, 3) <<
		1., 1., 1.,
		1., 1., 1.,
		1., 1., 1.);

	cv::Mat mask;
	cv::threshold(alpha, mask, 0.0, 1.0, cv::THRESH_BINARY); // <20>A<EFBFBD><41><EFBFBD>t<EFBFBD>@<40>`<60><><EFBFBD><EFBFBD><EFBFBD>l<EFBFBD><6C><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD>l<EFBFBD><6C><EFBFBD><EFBFBD><EFBFBD>ă}<7D>X<EFBFBD>N<EFBFBD>Ƃ<EFBFBD><C682>Ĉ<EFBFBD><C488><EFBFBD>

	cv::Mat mask_nega;
	cv::threshold(mask, mask_nega, 0.0, 1.0, cv::THRESH_BINARY_INV); // <20><><EFBFBD>]<5D><><EFBFBD><EFBFBD><EFBFBD>}<7D>X<EFBFBD>N<EFBFBD>i<EFBFBD>l<EFBFBD><6C>1<EFBFBD>̉ӏ<CC89><D38F>͊<EFBFBD><CD8A>S<EFBFBD><53><EFBFBD><EFBFBD><EFBFBD>łȂ<C582><C882>L<EFBFBD><4C><EFBFBD>ȉ<EFBFBD><C889>f<EFBFBD>ƂȂ<C682><C882>j

	for (auto &p : planes) // <20><><EFBFBD>S<EFBFBD>ɓ<EFBFBD><C993><EFBFBD><EFBFBD>ȃs<C883>N<EFBFBD>Z<EFBFBD><5A><EFBFBD>ɂ<EFBFBD><C982><EFBFBD><EFBFBD>S<EFBFBD>~<7E><><EFBFBD><EFBFBD><EFBFBD><EFBFBD>
	{
		p = p.mul(mask);
	}

	for (int i = 0; i < offset; i++)
	{
		cv::Mat mask_weight;
		cv::filter2D(mask, mask_weight, -1, sum2d_kernel, cv::Point(-1, -1), 0, cv::BORDER_DEFAULT); // <20>}<7D>X<EFBFBD>N<EFBFBD><4E>3<EFBFBD>~3<>̈<EFBFBD><CC88>̍<EFBFBD><CC8D>v<EFBFBD>l<EFBFBD><6C><EFBFBD><EFBFBD><EFBFBD>߂<EFBFBD>

		cv::Mat mask_nega_u8;
		mask_nega.convertTo(mask_nega_u8, CV_8U, 255.0, clip_eps8); // mask_nega<67><61>CV_U8<55>ŁiOpenCV<43><56>API<50><49><EFBFBD>K<EFBFBD>v<EFBFBD>ɂȂ<C982><C882>j

		for (auto &p : planes) // 1<>`<60><><EFBFBD><EFBFBD><EFBFBD>l<EFBFBD><6C><EFBFBD><EFBFBD><EFBFBD><EFBFBD><C28F><EFBFBD>
		{
			// <20>`<60><><EFBFBD><EFBFBD><EFBFBD>l<EFBFBD><6C><EFBFBD><EFBFBD>3<EFBFBD>~3<>̈<EFBFBD><CC88><EFBFBD><EFBFBD>̗L<CC97><4C><EFBFBD><EFBFBD><EFBFBD>f<EFBFBD>̕<EFBFBD><CC95>ϒl<CF92><6C><EFBFBD><EFBFBD><EFBFBD>߂<EFBFBD>
			cv::Mat border;
			cv::filter2D(p, border, -1, sum2d_kernel, cv::Point(-1, -1), 0, cv::BORDER_DEFAULT);
			border /= mask_weight;

			// <20>`<60><><EFBFBD><EFBFBD><EFBFBD>l<EFBFBD><6C><EFBFBD>̗L<CC97><4C><EFBFBD>ȉ<EFBFBD><C889>f<EFBFBD>̕<EFBFBD><CC95><EFBFBD><EFBFBD>ɁA<C981>v<EFBFBD>Z<EFBFBD><5A><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD>ϒl<CF92><6C><EFBFBD>R<EFBFBD>s<EFBFBD>[
			border.copyTo(p, mask_nega_u8);
		}

		// <20>}<7D>X<EFBFBD>N<EFBFBD><4E>1<EFBFBD><31><EFBFBD>c<EFBFBD><63><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD>̂<EFBFBD><CC82>V<EFBFBD><56><EFBFBD><EFBFBD><EFBFBD>}<7D>X<EFBFBD>N<EFBFBD>Ƃ<EFBFBD><C682><EFBFBD>(<28>}<7D>X<EFBFBD>N<EFBFBD><4E>3<EFBFBD>~3<>̈<EFBFBD><CC88>̍<EFBFBD><CC8D>v<EFBFBD>l<EFBFBD><6C><EFBFBD><EFBFBD><EFBFBD>߂<EFBFBD><DF82><EFBFBD><EFBFBD>̂̔<CC82>0<EFBFBD>̈<EFBFBD><CC88>́A<CD81>}<7D>X<EFBFBD>N<EFBFBD><4E>1<EFBFBD><31><EFBFBD>c<EFBFBD><63><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD>̗̂̈<CC97><CC88>ɓ<EFBFBD><C993><EFBFBD><EFBFBD><EFBFBD>)
		cv::threshold(mask_weight, mask, 0.0, 1.0, cv::THRESH_BINARY);
		// <20>V<EFBFBD><56><EFBFBD><EFBFBD><EFBFBD>}<7D>X<EFBFBD>N<EFBFBD>̔<EFBFBD><CC94>]<5D><><EFBFBD><EFBFBD><EFBFBD>}<7D>X<EFBFBD>N<EFBFBD><4E><EFBFBD>v<EFBFBD>Z
		cv::threshold(mask, mask_nega, 0.0, 1.0, cv::THRESH_BINARY_INV);
	}

	// <20><><EFBFBD>f<EFBFBD><66>0<EFBFBD><30><EFBFBD><EFBFBD>1<EFBFBD>ɃN<C983><4E><EFBFBD>b<EFBFBD>s<EFBFBD><73><EFBFBD>O
	for (auto &p : planes)
	{
		cv::threshold(p, p, 1.0, 1.0, cv::THRESH_TRUNC);
		cv::threshold(p, p, 0.0, 0.0, cv::THRESH_TOZERO);
	}

	return eWaifu2xError_OK;
}

// <20>摜<EFBFBD><E6919C><EFBFBD>ǂݍ<C782><DD8D><EFBFBD><EFBFBD>Œl<C592><6C>0.0f<EFBFBD>`1.0f<EFBFBD>͈̔͂ɕϊ<EFBFBD>
Waifu2x::eWaifu2xError Waifu2x::LoadMat(cv::Mat &float_image, const boost::filesystem::path &input_file)
{
	cv::Mat original_image;

	{
		std::vector<char> img_data;
		if (!readFile(input_file, img_data))
			return Waifu2x::eWaifu2xError_FailedOpenInputFile;

		cv::Mat im(img_data.size(), 1, CV_8U, img_data.data());
		original_image = cv::imdecode(im, cv::IMREAD_UNCHANGED);

		if (original_image.empty())
		{
			const eWaifu2xError ret = LoadMatBySTBI(original_image, img_data);
			if (ret != eWaifu2xError_OK)
				return ret;
		}
	}

	cv::Mat convert;
	switch (original_image.depth())
	{
	case CV_8U:
		original_image.convertTo(convert, CV_32F, 1.0 / GetValumeMaxFromCVDepth(CV_8U));
		break;

	case CV_16U:
		original_image.convertTo(convert, CV_32F, 1.0 / GetValumeMaxFromCVDepth(CV_16U));
		break;

	case CV_32F:
		convert = original_image; // <20><><EFBFBD><EFBFBD><EFBFBD><EFBFBD>0.0<EFBFBD>`1.0<EFBFBD>̂͂<EFBFBD><EFBFBD>Ȃ̂ŕϊ<EFBFBD><EFBFBD>͕K<EFBFBD>v<EFBFBD>Ȃ<EFBFBD>
		break;
	}
	
	original_image.release();

	if (convert.channels() == 1)
		cv::cvtColor(convert, convert, cv::COLOR_GRAY2BGR);
	else if (convert.channels() == 4)
	{
		// <20>A<EFBFBD><41><EFBFBD>t<EFBFBD>@<40>`<60><><EFBFBD><EFBFBD><EFBFBD>l<EFBFBD><6C><EFBFBD>t<EFBFBD><74><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD>瓧<EFBFBD><E793A7><EFBFBD>ȃs<C883>N<EFBFBD>Z<EFBFBD><5A><EFBFBD>̂ƕs<C695><73><EFBFBD><EFBFBD><EFBFBD>ȃs<C883>N<EFBFBD>Z<EFBFBD><5A><EFBFBD>̋<EFBFBD><CC8B>E<EFBFBD><45><EFBFBD><EFBFBD><EFBFBD>̐F<CC90><46><EFBFBD>L<EFBFBD><4C><EFBFBD><EFBFBD>

		std::vector<cv::Mat> planes;
		cv::split(convert, planes);

		cv::Mat alpha = planes[3];
		planes.resize(3);
		AlphaMakeBorder(planes, alpha, layer_num);

		planes.push_back(alpha);
		cv::merge(planes, convert);
	}

	float_image = convert;

	return eWaifu2xError_OK;
}

Waifu2x::eWaifu2xError Waifu2x::LoadMatBySTBI(cv::Mat &float_image, const std::vector<char> &img_data)
{
	int x, y, comp;
	stbi_uc *data = stbi_load_from_memory((const stbi_uc *)img_data.data(), img_data.size(), &x, &y, &comp, 4);
	if (!data)
		return eWaifu2xError_FailedOpenInputFile;

	int type = 0;
	switch (comp)
	{
	case 1:
	case 3:
	case 4:
		type = CV_MAKETYPE(CV_8U, comp);
		break;

	default:
		return eWaifu2xError_FailedOpenInputFile;
	}

	float_image = cv::Mat(cv::Size(x, y), type);

	const auto LinePixel = float_image.step1() / float_image.channels();
	const auto Channel = float_image.channels();
	const auto Width = float_image.size().width;
	const auto Height = float_image.size().height;

	assert(x == Width);
	assert(y == Height);
	assert(Channel == comp);

	auto ptr = float_image.data;
	for (int i = 0; i < y; i++)
	{
		for (int j = 0; j < x; j++)
		{
			for (int ch = 0; ch < Channel; ch++)
				ptr[(i * LinePixel + j) * comp + ch] = data[(i * x + j) * comp + ch];
		}
	}

	stbi_image_free(data);

	if (comp >= 3)
	{
		// RGB<47><42><EFBFBD><EFBFBD><EFBFBD><EFBFBD>BGR<47>ɕϊ<C995>
		for (int i = 0; i < y; i++)
		{
			for (int j = 0; j < x; j++)
				std::swap(ptr[(i * LinePixel + j) * comp + 0], ptr[(i * LinePixel + j) * comp + 2]);
		}
	}

	return eWaifu2xError_OK;
}

// <20>摜<EFBFBD><E6919C><EFBFBD><EFBFBD><EFBFBD>P<EFBFBD>x<EFBFBD>̉摜<CC89><E6919C><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD>o<EFBFBD><6F>
Waifu2x::eWaifu2xError Waifu2x::CreateBrightnessImage(const cv::Mat &float_image, cv::Mat &im)
{
	if (float_image.channels() > 1)
	{
		cv::Mat converted_color;
		cv::cvtColor(float_image, converted_color, ConvertMode);

		std::vector<cv::Mat> planes;
		cv::split(converted_color, planes);

		im = planes[0];
		planes.clear();
	}
	else
		im = float_image;

	return eWaifu2xError_OK;
}

// <20><><EFBFBD>͉摜<CD89><E6919C>(Photoshop<6F>ł<EFBFBD><C582><EFBFBD>)<29>L<EFBFBD><4C><EFBFBD><EFBFBD><EFBFBD>o<EFBFBD>X<EFBFBD>T<EFBFBD>C<EFBFBD>Y<EFBFBD><59>output_size<7A>̔{<7B><><EFBFBD>ɕύX
// <20>摜<EFBFBD>͍<EFBFBD><CD8D><EFBFBD><EFBFBD>z<EFBFBD>u<EFBFBD>A<EFBFBD>]<5D><><EFBFBD><EFBFBD>cv::BORDER_REPLICATE<54>Ŗ<EFBFBD><C596>߂<EFBFBD>
Waifu2x::eWaifu2xError Waifu2x::PaddingImage(const cv::Mat &input, cv::Mat &output)
{
	const auto h_blocks = (int)floor(input.size().width / output_size) + (input.size().width % output_size == 0 ? 0 : 1);
	const auto w_blocks = (int)floor(input.size().height / output_size) + (input.size().height % output_size == 0 ? 0 : 1);
	const auto height = offset + h_blocks * output_size + offset;
	const auto width = offset + w_blocks * output_size + offset;
	const auto pad_h1 = offset;
	const auto pad_w1 = offset;
	const auto pad_h2 = (height - offset) - input.size().width;
	const auto pad_w2 = (width - offset) - input.size().height;

	cv::copyMakeBorder(input, output, pad_w1, pad_w2, pad_h1, pad_h2, cv::BORDER_REPLICATE);

	return eWaifu2xError_OK;
}

// <20>摜<EFBFBD><E6919C>cv::INTER_NEAREST<53>œ<EFBFBD><C593>{<7B>Ɋg<C98A>債<EFBFBD>āAPaddingImage()<29>Ńp<C583>f<EFBFBD>B<EFBFBD><42><EFBFBD>O<EFBFBD><4F><EFBFBD><EFBFBD>
Waifu2x::eWaifu2xError Waifu2x::Zoom2xAndPaddingImage(const cv::Mat &input, cv::Mat &output, cv::Size_<int> &zoom_size)
{
	zoom_size = input.size();
	zoom_size.width *= 2;
	zoom_size.height *= 2;

	cv::Mat zoom_image;
	cv::resize(input, zoom_image, zoom_size, 0.0, 0.0, cv::INTER_NEAREST);

	return PaddingImage(zoom_image, output);
}

// <20><><EFBFBD>͉摜<CD89><E6919C>zoom_size<7A>̑傫<CC91><E582AB><EFBFBD><EFBFBD>cv::INTER_CUBIC<49>Ŋg<C58A>債<EFBFBD>A<EFBFBD>F<EFBFBD><46><EFBFBD><EFBFBD><EFBFBD>݂̂<CC82><DD82>c<EFBFBD><63>
Waifu2x::eWaifu2xError Waifu2x::CreateZoomColorImage(const cv::Mat &float_image, const cv::Size_<int> &zoom_size, std::vector<cv::Mat> &cubic_planes)
{
	cv::Mat zoom_cubic_image;
	cv::resize(float_image, zoom_cubic_image, zoom_size, 0.0, 0.0, cv::INTER_CUBIC);

	cv::Mat converted_cubic_image;
	cv::cvtColor(zoom_cubic_image, converted_cubic_image, ConvertMode);
	zoom_cubic_image.release();

	cv::split(converted_cubic_image, cubic_planes);
	converted_cubic_image.release();

	// <20><><EFBFBD><EFBFBD>Y<EFBFBD><59><EFBFBD><EFBFBD><EFBFBD>͎g<CD8E><67><EFBFBD>Ȃ<EFBFBD><C882>̂ʼn<CC82><C589><EFBFBD>
	cubic_planes[0].release();

	return eWaifu2xError_OK;
}

// <20><><EFBFBD>f<EFBFBD><66><EFBFBD>t<EFBFBD>@<40>C<EFBFBD><43><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD>l<EFBFBD>b<EFBFBD>g<EFBFBD><67><EFBFBD>[<5B>N<EFBFBD><4E><EFBFBD>\<5C>z
// process<73><73>cudnn<6E><6E><EFBFBD>w<EFBFBD>肳<EFBFBD><E882B3><EFBFBD>Ȃ<EFBFBD><C882><EFBFBD><EFBFBD><EFBFBD><EFBFBD>ꍇ<EFBFBD><EA8D87>cuDNN<4E><4E><EFBFBD>Ăяo<D18F><6F><EFBFBD><EFBFBD><EFBFBD>Ȃ<EFBFBD><C882>悤<EFBFBD>ɕύX<CF8D><58><EFBFBD><EFBFBD>
Waifu2x::eWaifu2xError Waifu2x::ConstractNet(boost::shared_ptr<caffe::Net<float>> &net, const boost::filesystem::path &model_path, const boost::filesystem::path &param_path, const std::string &process)
{
	boost::filesystem::path modelbin_path = model_path;
	modelbin_path += ".protobin";
	boost::filesystem::path caffemodel_path = param_path;
	caffemodel_path += ".caffemodel";

	caffe::NetParameter param_model;
	caffe::NetParameter param_caffemodel;

	const auto retModelBin = readProtoBinary(modelbin_path, &param_model);
	const auto retParamBin = readProtoBinary(caffemodel_path, &param_caffemodel);

	if (retModelBin == eWaifu2xError_OK && retParamBin == eWaifu2xError_OK)
	{
		Waifu2x::eWaifu2xError ret;

		ret = SetParameter(param_model, process);
		if (ret != eWaifu2xError_OK)
			return ret;

		if (!caffe::UpgradeNetAsNeeded(caffemodel_path.string(), &param_caffemodel))
			return Waifu2x::eWaifu2xError_FailedParseModelFile;

		net = boost::shared_ptr<caffe::Net<float>>(new caffe::Net<float>(param_model));
		net->CopyTrainedLayersFrom(param_caffemodel);

		input_plane = param_model.input_dim(1);
	}
	else
	{
		const auto ret = LoadParameterFromJson(net, model_path, param_path, modelbin_path, caffemodel_path, process);
		if (ret != eWaifu2xError_OK)
			return ret;
	}

	return eWaifu2xError_OK;
}

Waifu2x::eWaifu2xError Waifu2x::SetParameter(caffe::NetParameter &param, const std::string &process) const
{
	param.mutable_state()->set_phase(caffe::TEST);

	{
		auto mid = param.mutable_input_dim();

		if (mid->size() != 4)
			return eWaifu2xError_FailedParseModelFile;

		*mid->Mutable(0) = batch_size;
		*mid->Mutable(2) = input_block_size;
		*mid->Mutable(3) = input_block_size;
	}

	for (int i = 0; i < param.layer_size(); i++)
	{
		caffe::LayerParameter *layer_param = param.mutable_layer(i);
		const std::string& type = layer_param->type();
		if (type == "Convolution")
		{
			if (process == "cudnn")
				layer_param->mutable_convolution_param()->set_engine(caffe::ConvolutionParameter_Engine_CUDNN);
			else
				layer_param->mutable_convolution_param()->set_engine(caffe::ConvolutionParameter_Engine_CAFFE);
		}
		else if (type == "ReLU")
		{
			if (process == "cudnn")
				layer_param->mutable_relu_param()->set_engine(caffe::ReLUParameter_Engine_CUDNN);
			else
				layer_param->mutable_relu_param()->set_engine(caffe::ReLUParameter_Engine_CAFFE);
		}
	}

	return eWaifu2xError_OK;
}

Waifu2x::eWaifu2xError Waifu2x::LoadParameterFromJson(boost::shared_ptr<caffe::Net<float>> &net, const boost::filesystem::path &model_path, const boost::filesystem::path &param_path
	, const boost::filesystem::path &modelbin_path, const boost::filesystem::path &caffemodel_path, const std::string &process)
{
	Waifu2x::eWaifu2xError ret;

	caffe::NetParameter param;
	ret = readProtoText(model_path, &param);
	if (ret != eWaifu2xError_OK)
		return ret;

	ret = writeProtoBinary(param, modelbin_path);
	if (ret != eWaifu2xError_OK)
		return ret;

	ret = SetParameter(param, process);
	if (ret != eWaifu2xError_OK)
		return ret;

	net = boost::shared_ptr<caffe::Net<float>>(new caffe::Net<float>(param));

	rapidjson::Document d;
	std::vector<char> jsonBuf;

	try
	{
		boost::iostreams::stream<boost::iostreams::file_descriptor_source> is(param_path, std::ios_base::in | std::ios_base::binary);

		try
		{
			is.open(param_path, std::ios_base::in | std::ios_base::binary);
		}
		catch (...)
		{
			return Waifu2x::eWaifu2xError_FailedOpenModelFile;
		}

		if(!is)
			return eWaifu2xError_FailedOpenModelFile;

		const size_t size = is.seekg(0, std::ios::end).tellg();
		is.seekg(0, std::ios::beg);

		jsonBuf.resize(size + 1);
		is.read(jsonBuf.data(), jsonBuf.size());

		jsonBuf[jsonBuf.size() - 1] = '\0';

		d.Parse(jsonBuf.data());
	}
	catch (...)
	{
		return eWaifu2xError_FailedParseModelFile;
	}

	if (d.Size() != 7)
		return eWaifu2xError_FailedParseModelFile;

	int inputPlane = 0;
	int outputPlane = 0;
	try
	{
		inputPlane = d[0]["nInputPlane"].GetInt();
		outputPlane = d[d.Size() - 1]["nOutputPlane"].GetInt();
	}
	catch (...)
	{
		return eWaifu2xError_FailedParseModelFile;
	}

	if (inputPlane == 0 || outputPlane == 0)
		return eWaifu2xError_FailedParseModelFile;

	if (inputPlane != outputPlane)
		return eWaifu2xError_FailedParseModelFile;

	//if (param.layer_size() < 17)
	//	return eWaifu2xError_FailedParseModelFile;

	std::vector<boost::shared_ptr<caffe::Layer<float>>> list;
	auto &v = net->layers();
	for (auto &l : v)
	{
		auto lk = l->type();
		auto &bv = l->blobs();
		if (bv.size() > 0)
			list.push_back(l);
	}

	try
	{
		std::vector<float> weightList;
		std::vector<float> biasList;

		int count = 0;
		for (auto it = d.Begin(); it != d.End(); ++it)
		{
			const auto &weight = (*it)["weight"];
			const auto nInputPlane = (*it)["nInputPlane"].GetInt();
			const auto nOutputPlane = (*it)["nOutputPlane"].GetInt();
			const auto kW = (*it)["kW"].GetInt();
			const auto &bias = (*it)["bias"];

			auto leyer = list[count];

			auto &b0 = leyer->blobs()[0];
			auto &b1 = leyer->blobs()[1];

			float *b0Ptr = nullptr;
			float *b1Ptr = nullptr;

			if (caffe::Caffe::mode() == caffe::Caffe::CPU)
			{
				b0Ptr = b0->mutable_cpu_data();
				b1Ptr = b1->mutable_cpu_data();
			}
			else
			{
				b0Ptr = b0->mutable_gpu_data();
				b1Ptr = b1->mutable_gpu_data();
			}

			const auto WeightSize1 = weight.Size();
			const auto WeightSize2 = weight[0].Size();
			const auto KernelHeight = weight[0][0].Size();
			const auto KernelWidth = weight[0][0][0].Size();

			if (!(b0->count() == WeightSize1 * WeightSize2 * KernelHeight * KernelWidth))
				return eWaifu2xError_FailedConstructModel;

			if (!(b1->count() == bias.Size()))
				return eWaifu2xError_FailedConstructModel;

			weightList.resize(0);
			biasList.resize(0);

			size_t weightCount = 0;
			for (auto it2 = weight.Begin(); it2 != weight.End(); ++it2)
			{
				for (auto it3 = (*it2).Begin(); it3 != (*it2).End(); ++it3)
				{
					for (auto it4 = (*it3).Begin(); it4 != (*it3).End(); ++it4)
					{
						for (auto it5 = (*it4).Begin(); it5 != (*it4).End(); ++it5)
							weightList.push_back((float)it5->GetDouble());
					}
				}
			}

			caffe::caffe_copy(b0->count(), weightList.data(), b0Ptr);

			for (auto it2 = bias.Begin(); it2 != bias.End(); ++it2)
				biasList.push_back((float)it2->GetDouble());

			caffe::caffe_copy(b1->count(), biasList.data(), b1Ptr);

			count++;
		}

		net->ToProto(&param);

		ret = writeProtoBinary(param, caffemodel_path);
		if (ret != eWaifu2xError_OK)
			return ret;
	}
	catch (...)
	{
		return eWaifu2xError_FailedConstructModel;
	}

	input_plane = inputPlane;

	return eWaifu2xError_OK;
}

// <20>l<EFBFBD>b<EFBFBD>g<EFBFBD><67><EFBFBD>[<5B>N<EFBFBD><4E><EFBFBD>g<EFBFBD><67><EFBFBD>ĉ摜<C489><E6919C><EFBFBD>č\<5C>z<EFBFBD><7A><EFBFBD><EFBFBD>
Waifu2x::eWaifu2xError Waifu2x::ReconstructImage(boost::shared_ptr<caffe::Net<float>> net, cv::Mat &im)
{
	const auto Height = im.size().height;
	const auto Width = im.size().width;
	const auto Line = im.step1();

	assert(Width % output_size == 0);
	assert(Height % output_size == 0);

	assert(im.channels() == 1 || im.channels() == 3);

	cv::Mat outim(im.rows, im.cols, im.type());

	// float *imptr = (float *)im.data;
	float *imptr = (float *)outim.data;

	try
	{
		auto input_blobs = net->input_blobs();
		auto input_blob = net->input_blobs()[0];

		input_blob->Reshape(batch_size, input_plane, input_block_size, input_block_size);

		assert(im.channels() == input_plane);
		assert(input_blob->shape(1) == input_plane);

		const int WidthNum = Width / output_size;
		const int HeightNum = Height / output_size;

		const int BlockNum = WidthNum * HeightNum;

		const int input_block_plane_size = input_block_size * input_block_size * input_plane;
		const int output_block_plane_size = output_block_size * output_block_size * input_plane;

		const int output_padding = inner_padding + outer_padding - layer_num;

		// <20>摜<EFBFBD><E6919C>(<28><><EFBFBD><EFBFBD><EF8381><EFBFBD><EFBFBD><EFBFBD>̓s<CC93><73><EFBFBD><EFBFBD>)output_size*output_size<7A>ɕ<EFBFBD><C995><EFBFBD><EFBFBD>čč\<5C>z<EFBFBD><7A><EFBFBD><EFBFBD>
		for (int num = 0; num < BlockNum; num += batch_size)
		{
			const int processNum = (BlockNum - num) >= batch_size ? batch_size : BlockNum - num;

			if (processNum < batch_size)
				input_blob->Reshape(processNum, input_plane, input_block_size, input_block_size);

			for (int n = 0; n < processNum; n++)
			{
				const int wn = (num + n) % WidthNum;
				const int hn = (num + n) / WidthNum;

				const int w = wn * output_size;
				const int h = hn * output_size;

				if (w + crop_size <= Width && h + crop_size <= Height)
				{
					int x, y;
					x = w - inner_padding;
					y = h - inner_padding;

					int width, height;

					width = crop_size + inner_padding * 2;
					height = crop_size + inner_padding * 2;

					int top, bottom, left, right;

					top = outer_padding;
					bottom = outer_padding;
					left = outer_padding;
					right = outer_padding;

					if (x < 0)
					{
						left += -x;
						width -= -x;
						x = 0;
					}

					if (x + width > Width)
					{
						right += (x + width) - Width;
						width = Width - x;
					}

					if (y < 0)
					{
						top += -y;
						height -= -y;
						y = 0;
					}

					if (y + height > Height)
					{
						bottom += (y + height) - Height;
						height = Height - y;
					}

					cv::Mat someimg = im(cv::Rect(x, y, width, height));

					cv::Mat someborderimg;
					// <20>摜<EFBFBD>𒆉<EFBFBD><F0928689>Ƀp<C983>f<EFBFBD>B<EFBFBD><42><EFBFBD>O<EFBFBD>B<EFBFBD>]<5D><><EFBFBD><EFBFBD>cv::BORDER_REPLICATE<54>Ŗ<EFBFBD><C596>߂<EFBFBD>
					// <20><><EFBFBD><EFBFBD>im<69>ʼn<EFBFBD><C589>f<EFBFBD><66><EFBFBD><EFBFBD><EFBFBD>݂<EFBFBD><DD82>镔<EFBFBD><E99594><EFBFBD>͗]<5D><><EFBFBD>ƔF<C694><46><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD>Ȃ<EFBFBD><C882><EFBFBD><EFBFBD>Ainner_padding<6E><67>layer_num<75><6D>outer_padding<6E><67>1<EFBFBD>ȏ<EFBFBD><C88F>Ȃ炻<C882><E782BB><EFBFBD>̕<EFBFBD><CC95><EFBFBD><EFBFBD>̉<EFBFBD><CC89>f<EFBFBD>͌<EFBFBD><CD8C>ʉ摜<CA89>Ƃ<EFBFBD><C682>Ď<EFBFBD><C48E><EFBFBD><EFBFBD>o<EFBFBD><6F><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD>ɂ͉e<CD89><65><EFBFBD><EFBFBD><EFBFBD>Ȃ<EFBFBD>
					cv::copyMakeBorder(someimg, someborderimg, top, bottom, left, right, cv::BORDER_REPLICATE);
					someimg.release();

					// <20>摜<EFBFBD>𒼗<EFBFBD><F092BC97>ɕϊ<C995>
					{
						float *fptr = input_block + (input_block_plane_size * n);
						const float *uptr = (const float *)someborderimg.data;

						const auto Line = someborderimg.step1();

						if (someborderimg.channels() == 1)
						{
							if (input_block_size == Line)
								memcpy(fptr, uptr, input_block_size * input_block_size * sizeof(float));
							else
							{
								for (int i = 0; i < input_block_size; i++)
									memcpy(fptr + i * input_block_size, uptr + i * Line, input_block_size * sizeof(float));
							}
						}
						else
						{
							const auto LinePixel = someborderimg.step1() / someborderimg.channels();
							const auto Channel = someborderimg.channels();
							const auto Width = someborderimg.size().width;
							const auto Height = someborderimg.size().height;

							for (int i = 0; i < Height; i++)
							{
								for (int j = 0; j < LinePixel; j++)
								{
									for (int ch = 0; ch < Channel; ch++)
										fptr[(ch * Height + i) * Width + j] = uptr[(i * LinePixel + j) * Channel + ch];
								}
							}
						}
					}
				}
			}

			assert(input_blob->count() == input_block_plane_size * processNum);

			// <20>l<EFBFBD>b<EFBFBD>g<EFBFBD><67><EFBFBD>[<5B>N<EFBFBD>ɉ摜<C989><E6919C><EFBFBD><EFBFBD><EFBFBD><EFBFBD>
			input_blob->set_cpu_data(input_block);

			// <20>v<EFBFBD>Z
			auto out = net->ForwardPrefilled(nullptr);

			auto b = out[0];

			assert(b->count() == output_block_plane_size * processNum);

			const float *ptr = nullptr;

			if (caffe::Caffe::mode() == caffe::Caffe::CPU)
				ptr = b->cpu_data();
			else
				ptr = b->gpu_data();

			caffe::caffe_copy(output_block_plane_size * processNum, ptr, output_block);

			for (int n = 0; n < processNum; n++)
			{
				const int wn = (num + n) % WidthNum;
				const int hn = (num + n) / WidthNum;

				const int w = wn * output_size;
				const int h = hn * output_size;

				const float *fptr = output_block + (output_block_plane_size * n);

				// <20><><EFBFBD>ʂ<EFBFBD><CA82>o<EFBFBD>͉摜<CD89>ɃR<C983>s<EFBFBD>[
				if (outim.channels() == 1)
				{
					for (int i = 0; i < crop_size; i++)
						memcpy(imptr + (h + i) * Line + w, fptr + (i + output_padding) * output_block_size + output_padding, crop_size * sizeof(float));
				}
				else
				{
					const auto LinePixel = outim.step1() / outim.channels();
					const auto Channel = outim.channels();

					for (int i = 0; i < crop_size; i++)
					{
						for (int j = 0; j < crop_size; j++)
						{
							for (int ch = 0; ch < Channel; ch++)
								imptr[((h + i) * LinePixel + (w + j)) * Channel + ch] = fptr[(ch * output_block_size + i + output_padding) * output_block_size + j + output_padding];
						}
					}
				}
			}
		}
	}
	catch (...)
	{
		return eWaifu2xError_FailedProcessCaffe;
	}

	im = outim;

	return eWaifu2xError_OK;
}

Waifu2x::eWaifu2xError Waifu2x::init(int argc, char** argv, const std::string &Mode, const int NoiseLevel, const double ScaleRatio, const boost::filesystem::path &ModelDir, const std::string &Process,
	const boost::optional<int> OutputQuality, const int OutputDepth, const bool UseTTA, const int CropSize, const int BatchSize)
{
	Waifu2x::eWaifu2xError ret;

	if (is_inited)
		return eWaifu2xError_OK;

	if (ScaleRatio <= 0.0)
		return eWaifu2xError_InvalidParameter;

	try
	{
		mode = Mode;
		noise_level = NoiseLevel;
		scale_ratio = ScaleRatio;
		model_dir = ModelDir;
		process = Process;
		use_tta = UseTTA;

		output_quality = OutputQuality;
		output_depth = OutputDepth;

		crop_size = CropSize;
		batch_size = BatchSize;

		inner_padding = layer_num;
		outer_padding = 1;

		output_size = crop_size - offset * 2;
		input_block_size = crop_size + (inner_padding + outer_padding) * 2;
		original_width_height = 128 + layer_num * 2;

		output_block_size = crop_size + (inner_padding + outer_padding - layer_num) * 2;

		std::call_once(waifu2x_once_flag, [argc, argv]()
		{
			assert(argc >= 1);

			int tmpargc = 1;
			char* tmpargvv[] = { argv[0] };
			char** tmpargv = tmpargvv;
			// glog<6F><67><EFBFBD>̏<EFBFBD><CC8F><EFBFBD><EFBFBD><EFBFBD>
			caffe::GlobalInit(&tmpargc, &tmpargv);
		});

		const auto cuDNNCheckStartTime = std::chrono::system_clock::now();

		if (process == "gpu")
		{
			if (can_use_CUDA() != eWaifu2xCudaError_OK)
				return eWaifu2xError_FailedCudaCheck;
			// cuDNN<4E><4E><EFBFBD>g<EFBFBD><67><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD>Ȃ<EFBFBD>cuDNN<4E><4E><EFBFBD>g<EFBFBD><67>
			else if (can_use_cuDNN() == eWaifu2xcuDNNError_OK)
				process = "cudnn";
		}

		const auto cuDNNCheckEndTime = std::chrono::system_clock::now();

		boost::filesystem::path mode_dir_path(model_dir);
		if (!mode_dir_path.is_absolute()) // model_dir<69><72><EFBFBD><EFBFBD><EFBFBD>΃p<CE83>X<EFBFBD>Ȃ<EFBFBD><C882><EFBFBD><EFBFBD>΃p<CE83>X<EFBFBD>ɒ<EFBFBD><C992><EFBFBD>
		{
			// <20>܂<EFBFBD><DC82>̓J<CD83><4A><EFBFBD><EFBFBD><EFBFBD>g<EFBFBD>f<EFBFBD>B<EFBFBD><42><EFBFBD>N<EFBFBD>g<EFBFBD><67><EFBFBD><EFBFBD><EFBFBD>ɂ<EFBFBD><C982>邩<EFBFBD>T<EFBFBD><54>
			mode_dir_path = boost::filesystem::absolute(model_dir);
			if (!boost::filesystem::exists(mode_dir_path) && argc >= 1) // <20><><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD>argv[0]<5D><><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD>s<EFBFBD>t<EFBFBD>@<40>C<EFBFBD><43><EFBFBD>̂<EFBFBD><CC82><EFBFBD><EFBFBD>t<EFBFBD>H<EFBFBD><48><EFBFBD>_<EFBFBD>𐄒肵<F0908492>A<EFBFBD><41><EFBFBD>̃t<CC83>H<EFBFBD><48><EFBFBD>_<EFBFBD><5F><EFBFBD>ɂ<EFBFBD><C982>邩<EFBFBD>T<EFBFBD><54>
			{
				boost::filesystem::path a0(argv[0]);
				if (a0.is_absolute())
					mode_dir_path = a0.branch_path() / model_dir;
			}
		}

		if (!boost::filesystem::exists(mode_dir_path))
			return eWaifu2xError_FailedOpenModelFile;

		if (process == "cpu")
		{
			caffe::Caffe::set_mode(caffe::Caffe::CPU);
			isCuda = false;
		}
		else
		{
			caffe::Caffe::set_mode(caffe::Caffe::GPU);
			isCuda = true;
		}

		if (mode == "noise" || mode == "noise_scale" || mode == "auto_scale")
		{
			const boost::filesystem::path model_path = (mode_dir_path / "srcnn.prototxt").string();
			const boost::filesystem::path param_path = (mode_dir_path / ("noise" + std::to_string(noise_level) + "_model.json")).string();

			ret = ConstractNet(net_noise, model_path, param_path, process);
			if (ret != eWaifu2xError_OK)
				return ret;
		}

		if (mode == "scale" || mode == "noise_scale" || mode == "auto_scale")
		{
			const boost::filesystem::path model_path = (mode_dir_path / "srcnn.prototxt").string();
			const boost::filesystem::path param_path = (mode_dir_path / "scale2.0x_model.json").string();

			ret = ConstractNet(net_scale, model_path, param_path, process);
			if (ret != eWaifu2xError_OK)
				return ret;
		}

		const int input_block_plane_size = input_block_size * input_block_size * input_plane;
		const int output_block_plane_size = output_block_size * output_block_size * input_plane;

		if (isCuda)
		{
			CUDA_CHECK_WAIFU2X(cudaHostAlloc(&input_block, sizeof(float) * input_block_plane_size * batch_size, cudaHostAllocWriteCombined));
			CUDA_CHECK_WAIFU2X(cudaHostAlloc(&dummy_data, sizeof(float) * input_block_plane_size * batch_size, cudaHostAllocWriteCombined));
			CUDA_CHECK_WAIFU2X(cudaHostAlloc(&output_block, sizeof(float) * output_block_plane_size * batch_size, cudaHostAllocDefault));
		}
		else
		{
			input_block = new float[input_block_plane_size * batch_size];
			dummy_data = new float[input_block_plane_size * batch_size];
			output_block = new float[output_block_plane_size * batch_size];
		}

		for (size_t i = 0; i < input_block_plane_size * batch_size; i++)
			dummy_data[i] = 0.0f;

		is_inited = true;
	}
	catch (...)
	{
		return eWaifu2xError_InvalidParameter;
	}

	return eWaifu2xError_OK;
}

void Waifu2x::destroy()
{
	net_noise.reset();
	net_scale.reset();

	if (isCuda)
	{
		CUDA_HOST_SAFE_FREE(input_block);
		CUDA_HOST_SAFE_FREE(dummy_data);
		CUDA_HOST_SAFE_FREE(output_block);
	}
	else
	{
		SAFE_DELETE_WAIFU2X(input_block);
		SAFE_DELETE_WAIFU2X(dummy_data);
		SAFE_DELETE_WAIFU2X(output_block);
	}

	is_inited = false;
}

static void Waifu2x_stbi_write_func(void *context, void *data, int size)
{
	boost::iostreams::stream<boost::iostreams::file_descriptor> *osp = (boost::iostreams::stream<boost::iostreams::file_descriptor> *)context;
	osp->write((const char *)data, size);
}

Waifu2x::eWaifu2xError Waifu2x::WriteMat(const cv::Mat &im, const boost::filesystem::path &output_file, const boost::optional<int> &output_quality)
{
	const boost::filesystem::path ip(output_file);
	const std::string ext = ip.extension().string();

	const bool isJpeg = boost::iequals(ext, ".jpg") || boost::iequals(ext, ".jpeg");

	if (boost::iequals(ext, ".tga"))
	{
		unsigned char *data = im.data;

		std::vector<unsigned char> rgbimg;
		if (im.channels() >= 3 || im.step1() != im.size().width * im.channels()) // RGB<47>p<EFBFBD>o<EFBFBD>b<EFBFBD>t<EFBFBD>@<40>ɃR<C983>s<EFBFBD>[(<28><><EFBFBD>邢<EFBFBD>̓p<CD83>f<EFBFBD>B<EFBFBD><42><EFBFBD>O<EFBFBD><4F><EFBFBD>Ƃ<EFBFBD>)
		{
			const auto Line = im.step1();
			const auto Channel = im.channels();
			const auto Width = im.size().width;
			const auto Height = im.size().height;

			rgbimg.resize(Width * Height * Channel);

			const auto Stride = Width * Channel;
			for (int i = 0; i < Height; i++)
				memcpy(rgbimg.data() + Stride * i, im.data + Line * i, Stride);

			data = rgbimg.data();
		}

		if (im.channels() >= 3) // BGR<47><52>RGB<47>ɕ<EFBFBD><C995>ёւ<D191>
		{
			const auto Line = im.step1();
			const auto Channel = im.channels();
			const auto Width = im.size().width;
			const auto Height = im.size().height;

			auto ptr = rgbimg.data();
			for (int i = 0; i < Height; i++)
			{
				for (int j = 0; j < Width; j++)
					std::swap(ptr[(i * Width + j) * Channel + 0], ptr[(i * Width + j) * Channel + 2]);
			}
		}

		boost::iostreams::stream<boost::iostreams::file_descriptor> os;

		try
		{
			os.open(output_file, std::ios_base::out | std::ios_base::binary | std::ios_base::trunc);
		}
		catch (...)
		{
			return Waifu2x::eWaifu2xError_FailedOpenOutputFile;
		}

		if(!os)
			return eWaifu2xError_FailedOpenOutputFile;

		if (!stbi_write_tga_to_func(Waifu2x_stbi_write_func, &os, im.size().width, im.size().height, im.channels(), data))
			return eWaifu2xError_FailedOpenOutputFile;

		return eWaifu2xError_OK;
	}

	try
	{
		const boost::filesystem::path op(output_file);
		const boost::filesystem::path opext(op.extension());

		std::vector<int> params;

		const auto &OutputExtentionList = Waifu2x::OutputExtentionList;
		for (const auto &elm : OutputExtentionList)
		{
			if (elm.ext == opext)
			{
				if (elm.imageQualitySettingVolume && output_quality)
				{
					params.push_back(*elm.imageQualitySettingVolume);
					params.push_back(*output_quality);
				}

				break;
			}
		}

		std::vector<uchar> buf;
		cv::imencode(ext, im, buf, params);

		if (writeFile(output_file, buf))
			return eWaifu2xError_OK;

	}
	catch (...)
	{
	}

	return eWaifu2xError_FailedOpenOutputFile;
}

Waifu2x::eWaifu2xError Waifu2x::BeforeReconstructFloatMatProcess(const cv::Mat &in, cv::Mat &out, bool &convertBGRflag)
{
	Waifu2x::eWaifu2xError ret;

	convertBGRflag = false;

	cv::Mat im;
	if (input_plane == 1)
		CreateBrightnessImage(in, im);
	else
	{
		im = in;
		if (in.channels() == 1)
		{
			cv::cvtColor(in, im, CV_GRAY2BGR);
			convertBGRflag = true;
		}

		std::vector<cv::Mat> planes;
		cv::split(im, planes);

		if (im.channels() == 4)
			planes.resize(3);

		// BGR<47><52><EFBFBD><EFBFBD>RGB<47>ɂ<EFBFBD><C982><EFBFBD>
		std::swap(planes[0], planes[2]);

		cv::merge(planes, im);
	}

	out = im;

	return eWaifu2xError_OK;
}

Waifu2x::eWaifu2xError Waifu2x::ReconstructFloatMat(const bool isReconstructNoise, const bool isReconstructScale, const waifu2xCancelFunc cancel_func, const cv::Mat &in, cv::Mat &out)
{
	Waifu2x::eWaifu2xError ret;

	cv::Mat im(in);
	cv::Size_<int> image_size = im.size();

	if (isReconstructNoise)
	{
		PaddingImage(im, im);

		ret = ReconstructImage(net_noise, im);
		if (ret != eWaifu2xError_OK)
			return ret;

		// <20>p<EFBFBD>f<EFBFBD>B<EFBFBD><42><EFBFBD>O<EFBFBD><4F><EFBFBD><EFBFBD><EFBFBD>蕥<EFBFBD><E895A5>
		im = im(cv::Rect(offset, offset, image_size.width, image_size.height));

		// <20>l<EFBFBD><6C>0<EFBFBD>`1<>ɃN<C983><4E><EFBFBD>b<EFBFBD>s<EFBFBD><73><EFBFBD>O
		cv::threshold(im, im, 1.0, 1.0, cv::THRESH_TRUNC);
		cv::threshold(im, im, 0.0, 0.0, cv::THRESH_TOZERO);
	}

	if (cancel_func && cancel_func())
		return eWaifu2xError_Cancel;

	const int scale2 = ceil(log2(scale_ratio));

	if (isReconstructScale)
	{
		bool isError = false;
		for (int i = 0; i < scale2; i++)
		{
			Zoom2xAndPaddingImage(im, im, image_size);

			ret = ReconstructImage(net_scale, im);
			if (ret != eWaifu2xError_OK)
				return ret;

			// <20>p<EFBFBD>f<EFBFBD>B<EFBFBD><42><EFBFBD>O<EFBFBD><4F><EFBFBD><EFBFBD><EFBFBD>蕥<EFBFBD><E895A5>
			im = im(cv::Rect(offset, offset, image_size.width, image_size.height));

			// <20>l<EFBFBD><6C>0<EFBFBD>`1<>ɃN<C983><4E><EFBFBD>b<EFBFBD>s<EFBFBD><73><EFBFBD>O
			cv::threshold(im, im, 1.0, 1.0, cv::THRESH_TRUNC);
			cv::threshold(im, im, 0.0, 0.0, cv::THRESH_TOZERO);
		}
	}

	if (cancel_func && cancel_func())
		return eWaifu2xError_Cancel;

	out = im;

	return eWaifu2xError_OK;
}

Waifu2x::eWaifu2xError Waifu2x::Reconstruct(const bool isReconstructNoise, const bool isReconstructScale, const waifu2xCancelFunc cancel_func, const cv::Mat &in, cv::Mat &out)
{
	Waifu2x::eWaifu2xError ret;

	bool convertBGRflag = false;
	cv::Mat brfm;
	ret = BeforeReconstructFloatMatProcess(in, brfm, convertBGRflag);
	if (ret != eWaifu2xError_OK)
		return ret;

	cv::Mat reconstruct_image;
	if (!use_tta) // <20><><EFBFBD>ʂɏ<CA82><C98F><EFBFBD>
	{
		ret = ReconstructFloatMat(isReconstructNoise, isReconstructScale, cancel_func, brfm, reconstruct_image);
		if (ret != eWaifu2xError_OK)
			return ret;
	}
	else // Test-Time Augmentation Mode
	{
		const auto RotateClockwise90 = [](cv::Mat &mat)
		{
			cv::transpose(mat, mat);
			cv::flip(mat, mat, 1);
		};

		const auto RotateClockwise90N = [RotateClockwise90](cv::Mat &mat, const int rotateNum)
		{
			for (int i = 0; i < rotateNum; i++)
				RotateClockwise90(mat);
		};

		const auto RotateCounterclockwise90 = [](cv::Mat &mat)
		{
			cv::transpose(mat, mat);
			cv::flip(mat, mat, 0);
		};

		const auto RotateCounterclockwise90N = [RotateCounterclockwise90](cv::Mat &mat, const int rotateNum)
		{
			for (int i = 0; i < rotateNum; i++)
				RotateCounterclockwise90(mat);
		};

		cv::Mat ri[8];
		for (int i = 0; i < 8; i++)
		{
			cv::Mat in(brfm.clone());

			const int rotateNum = i % 4;
			RotateClockwise90N(in, rotateNum);

			if (i >= 4)
				cv::flip(in, in, 1); // <20><><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD>]

			ret = ReconstructFloatMat(isReconstructNoise, isReconstructScale, cancel_func, in, in);
			if (ret != eWaifu2xError_OK)
				return ret;

			if (i >= 4)
				cv::flip(in, in, 1); // <20><><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD>]

			RotateCounterclockwise90N(in, rotateNum);

			ri[i] = in;
		}

		reconstruct_image = ri[0];
		for (int i = 1; i < 8; i++)
			reconstruct_image += ri[i];

		reconstruct_image /= 8.0;
	}

	if (convertBGRflag)
	{
		cv::cvtColor(reconstruct_image, reconstruct_image, CV_RGB2GRAY); // <20><><EFBFBD>̒n<CC92>_<EFBFBD>ł͂܂<CD82>RGB<47>Ȃ<EFBFBD><C882>Ƃɒ<C682><C992><EFBFBD>
	}

	// <20>l<EFBFBD><6C>0<EFBFBD>`1<>ɃN<C983><4E><EFBFBD>b<EFBFBD>s<EFBFBD><73><EFBFBD>O
	cv::threshold(reconstruct_image, reconstruct_image, 1.0, 1.0, cv::THRESH_TRUNC);
	cv::threshold(reconstruct_image, reconstruct_image, 0.0, 0.0, cv::THRESH_TOZERO);

	out = reconstruct_image;

	return eWaifu2xError_OK;
}

Waifu2x::eWaifu2xError Waifu2x::AfterReconstructFloatMatProcess(const bool isReconstructScale, const waifu2xCancelFunc cancel_func, const cv::Mat &floatim, const cv::Mat &in, cv::Mat &out)
{
	cv::Size_<int> image_size = in.size();

	cv::Mat process_image;
	if (input_plane == 1)
	{
		// <20>č\<5C>z<EFBFBD><7A><EFBFBD><EFBFBD><EFBFBD>P<EFBFBD>x<EFBFBD>摜<EFBFBD><E6919C>CreateZoomColorImage()<29>ō쐬<C58D><EC90AC><EFBFBD><EFBFBD><EFBFBD>F<EFBFBD><46><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD>}<7D>[<5B>W<EFBFBD><57><EFBFBD>Ēʏ<C492><CA8F>̉摜<CC89>ɕϊ<C995><CF8A><EFBFBD><EFBFBD>A<EFBFBD><41><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD>

		std::vector<cv::Mat> color_planes;
		CreateZoomColorImage(floatim, image_size, color_planes);

		color_planes[0] = in;

		cv::Mat converted_image;
		cv::merge(color_planes, converted_image);
		color_planes.clear();

		cv::cvtColor(converted_image, process_image, ConvertInverseMode);
		converted_image.release();
	}
	else
	{
		std::vector<cv::Mat> planes;
		cv::split(in, planes);

		// RGB<47><42><EFBFBD><EFBFBD>BGR<47>ɒ<EFBFBD><C992><EFBFBD>
		std::swap(planes[0], planes[2]);

		cv::merge(planes, process_image);
	}

	const int scale2 = ceil(log2(scale_ratio));
	const double shrinkRatio = scale_ratio / std::pow(2.0, (double)scale2);

	cv::Mat alpha;
	if (floatim.channels() == 4)
	{
		std::vector<cv::Mat> planes;
		cv::split(floatim, planes);

		if (isReconstructScale)
			Reconstruct(false, true, cancel_func, planes[3], alpha);
		else
			alpha = planes[3];
	}

	// <20>A<EFBFBD><41><EFBFBD>t<EFBFBD>@<40>`<60><><EFBFBD><EFBFBD><EFBFBD>l<EFBFBD><6C><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD>A<EFBFBD><41><EFBFBD>t<EFBFBD>@<40><><EFBFBD>t<EFBFBD><74><EFBFBD><EFBFBD><EFBFBD><EFBFBD>
	if (!alpha.empty())
	{
		std::vector<cv::Mat> planes;
		cv::split(process_image, planes);
		process_image.release();

		planes.push_back(alpha);

		cv::merge(planes, process_image);
	}

	if (isReconstructScale)
	{
		const cv::Size_<int> ns(image_size.width * shrinkRatio, image_size.height * shrinkRatio);
		if (image_size.width != ns.width || image_size.height != ns.height)
			cv::resize(process_image, process_image, ns, 0.0, 0.0, cv::INTER_LINEAR);
	}

	// <20>l<EFBFBD><6C>0<EFBFBD>`1<>ɃN<C983><4E><EFBFBD>b<EFBFBD>s<EFBFBD><73><EFBFBD>O
	cv::threshold(process_image, process_image, 1.0, 1.0, cv::THRESH_TRUNC);
	cv::threshold(process_image, process_image, 0.0, 0.0, cv::THRESH_TOZERO);

	out = process_image;

	return eWaifu2xError_OK;
}

Waifu2x::eWaifu2xError Waifu2x::waifu2x(const boost::filesystem::path &input_file, const boost::filesystem::path &output_file,
	const waifu2xCancelFunc cancel_func)
{
	Waifu2x::eWaifu2xError ret;

	if (!is_inited)
		return eWaifu2xError_NotInitialized;

	const boost::filesystem::path ip(input_file);
	const boost::filesystem::path ipext(ip.extension());

	const bool isJpeg = boost::iequals(ipext.string(), ".jpg") || boost::iequals(ipext.string(), ".jpeg");
	const bool isReconstructNoise = mode == "noise" || mode == "noise_scale" || (mode == "auto_scale" && isJpeg);
	const bool isReconstructScale = mode == "scale" || mode == "noise_scale" || mode == "auto_scale";

	cv::Mat float_image;
	ret = LoadMat(float_image, input_file);
	if (ret != eWaifu2xError_OK)
		return ret;

	cv::Mat reconstruct_image;
	ret = Reconstruct(isReconstructNoise, isReconstructScale, cancel_func, float_image, reconstruct_image);
	if (ret != eWaifu2xError_OK)
		return ret;

	cv::Mat process_image;
	ret = AfterReconstructFloatMatProcess(isReconstructScale, cancel_func, float_image, reconstruct_image, process_image);
	if (ret != eWaifu2xError_OK)
		return ret;

	float_image.release();

	const int cv_depth = DepthBitToCVDepth(output_depth);
	const double max_val = GetValumeMaxFromCVDepth(cv_depth);
	const double eps = GetEPS(cv_depth);

	cv::Mat write_iamge;
	if (output_depth != 32) // <20>o<EFBFBD>͂<EFBFBD>float<61>`<60><><EFBFBD>Ȃ<EFBFBD><C882>ϊ<EFBFBD><CF8A><EFBFBD><EFBFBD>Ȃ<EFBFBD>
		process_image.convertTo(write_iamge, cv_depth, max_val, eps);
	else
		write_iamge = process_image;

	process_image.release();

	// <20><><EFBFBD>S<EFBFBD><53><EFBFBD><EFBFBD><EFBFBD>̃s<CC83>N<EFBFBD>Z<EFBFBD><5A><EFBFBD>̐F<CC90><46><EFBFBD><EFBFBD><EFBFBD><EFBFBD>(<28><><EFBFBD><EFBFBD><EFBFBD>̓s<CC93><73><EFBFBD><EFBFBD><EFBFBD>A<EFBFBD><41><EFBFBD>S<EFBFBD><53><EFBFBD><EFBFBD><EFBFBD>̃s<CC83>N<EFBFBD>Z<EFBFBD><5A><EFBFBD>ɂ<EFBFBD><C982>F<EFBFBD><46><EFBFBD>t<EFBFBD><74><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD>)
	// <20><><EFBFBD>f<EFBFBD><66><EFBFBD>ɂ<EFBFBD><C982><EFBFBD><EFBFBD>Ă͉摜<CD89>S<EFBFBD><53><EFBFBD>̊<EFBFBD><CC8A>S<EFBFBD><53><EFBFBD><EFBFBD><EFBFBD>̏ꏊ<CC8F>ɂ<EFBFBD><C982><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD>l<EFBFBD>̃A<CC83><41><EFBFBD>t<EFBFBD>@<40><><EFBFBD>L<EFBFBD><4C><EFBFBD>邱<EFBFBD>Ƃ<EFBFBD><C682><EFBFBD><EFBFBD><EFBFBD><EFBFBD>B<EFBFBD><42><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD>߂<EFBFBD>cv_depth<74>֕ϊ<D695><CF8A><EFBFBD><EFBFBD>Ă<EFBFBD><C482>炱<EFBFBD>̏<EFBFBD><CC8F><EFBFBD><EFBFBD><EFBFBD><EFBFBD>s<EFBFBD><73><EFBFBD><EFBFBD><EFBFBD>Ƃɂ<C682><C982><EFBFBD>
	// (<28><><EFBFBD><EFBFBD><EFBFBD><EFBFBD>cv_depth<74><68>32<33>̏ꍇ<CC8F><EA8D87><EFBFBD>ƈӖ<C688><D396>͖<EFBFBD><CD96><EFBFBD><EFBFBD><EFBFBD>)
	if (write_iamge.channels() > 3)
	{
		std::vector<cv::Mat> planes;
		cv::split(write_iamge, planes);

		cv::Mat mask;
		cv::threshold(planes[3], mask, 0.0, 1.0, cv::THRESH_BINARY); // <20>A<EFBFBD><41><EFBFBD>t<EFBFBD>@<40>`<60><><EFBFBD><EFBFBD><EFBFBD>l<EFBFBD><6C><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD>l<EFBFBD><6C><EFBFBD><EFBFBD><EFBFBD>ă}<7D>X<EFBFBD>N<EFBFBD>Ƃ<EFBFBD><C682>Ĉ<EFBFBD><C488><EFBFBD>

		// <20>A<EFBFBD><41><EFBFBD>t<EFBFBD>@<40>`<60><><EFBFBD><EFBFBD><EFBFBD>l<EFBFBD><6C><EFBFBD><EFBFBD>0<EFBFBD>̂Ƃ<CC82><C682><EFBFBD><EFBFBD>̐F<CC90><46><EFBFBD><EFBFBD><EFBFBD><EFBFBD>
		planes[0] = planes[0].mul(mask);
		planes[1] = planes[1].mul(mask);
		planes[2] = planes[2].mul(mask);

		cv::merge(planes, write_iamge);
	}

	ret = WriteMat(write_iamge, output_file, output_quality);
	if (ret != eWaifu2xError_OK)
		return ret;

	write_iamge.release();

	return eWaifu2xError_OK;
}

const std::string& Waifu2x::used_process() const
{
	return process;
}

int Waifu2x::DepthBitToCVDepth(const int depth_bit)
{
	switch (depth_bit)
	{
	case 8:
		return CV_8U;

	case 16:
		return CV_16U;

	case 32:
		return CV_32F;
	}

	// <20>s<EFBFBD><73><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD>ǂƂ肠<C682><E882A0><EFBFBD><EFBFBD>CV_8U<38><55><EFBFBD>Ԃ<EFBFBD><D482>Ă<EFBFBD><C482><EFBFBD>
	return CV_8U;
}

double Waifu2x::GetValumeMaxFromCVDepth(const int cv_depth)
{
	switch (cv_depth)
	{
	case CV_8U:
		return 255.0;

	case CV_16U:
		return 65535.0;

	case CV_32F:
		return 1.0;
	}

	// <20>s<EFBFBD><73><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD>ǂƂ肠<C682><E882A0><EFBFBD><EFBFBD>255.0<EFBFBD><EFBFBD><EFBFBD>Ԃ<EFBFBD><EFBFBD>Ă<EFBFBD><EFBFBD><EFBFBD>
	return 255.0;
}

double Waifu2x::GetEPS(const int cv_depth)
{
	switch (cv_depth)
	{
	case CV_8U:
		return clip_eps8;

	case CV_16U:
		return clip_eps16;

	case CV_32F:
		return clip_eps32;
	}

	// <20>s<EFBFBD><73><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD>ǂƂ肠<C682><E882A0><EFBFBD><EFBFBD>clip_eps8<73>Ԃ<EFBFBD><D482>Ă<EFBFBD><C482><EFBFBD>
	return clip_eps8;
}