mirror of
https://github.com/lltcggie/waifu2x-caffe.git
synced 2025-06-26 13:42:48 +00:00
1895 lines
50 KiB
C++
1895 lines
50 KiB
C++
#include "waifu2x.h"
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#include <caffe/caffe.hpp>
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#include <cudnn.h>
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#include <mutex>
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#include <opencv2/opencv.hpp>
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#include <rapidjson/document.h>
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#include <tclap/CmdLine.h>
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#include <boost/filesystem.hpp>
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#include <boost/algorithm/string.hpp>
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#include <chrono>
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#include <cuda_runtime.h>
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#include <boost/iostreams/stream.hpp>
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#include <boost/iostreams/device/file_descriptor.hpp>
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#include <google/protobuf/io/coded_stream.h>
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#include <google/protobuf/io/zero_copy_stream_impl.h>
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#include <google/protobuf/text_format.h>
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#include <fcntl.h>
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#ifdef _MSC_VER
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#include <io.h>
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#endif
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#define STB_IMAGE_IMPLEMENTATION
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#include <stb_image.h>
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#define STB_IMAGE_WRITE_IMPLEMENTATION
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#include <stb_image_write.h>
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#if defined(WIN32) || defined(WIN64)
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#include <Windows.h>
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#endif
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#define CV_VERSION_STR CVAUX_STR(CV_MAJOR_VERSION) CVAUX_STR(CV_MINOR_VERSION) CVAUX_STR(CV_SUBMINOR_VERSION)
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// ƒrƒ‹ƒhƒ‚<C692>[ƒh
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#ifdef _DEBUG
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#define CV_EXT_STR "d.lib"
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#else
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#define CV_EXT_STR ".lib"
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#endif
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#ifdef _MSC_VER
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#ifdef _DEBUG
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#pragma comment(lib, "caffe-d.lib")
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#pragma comment(lib, "proto-d.lib")
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#pragma comment(lib, "libboost_system-vc120-mt-gd-1_59.lib")
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#pragma comment(lib, "libboost_thread-vc120-mt-gd-1_59.lib")
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#pragma comment(lib, "libboost_filesystem-vc120-mt-gd-1_59.lib")
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#pragma comment(lib, "glogd.lib")
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#pragma comment(lib, "gflagsd.lib")
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#pragma comment(lib, "libprotobufd.lib")
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#pragma comment(lib, "libhdf5_hl_D.lib")
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#pragma comment(lib, "libhdf5_D.lib")
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#pragma comment(lib, "zlibstaticd.lib")
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#pragma comment(lib, "libopenblas.dll.a")
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#pragma comment(lib, "cudart.lib")
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#pragma comment(lib, "curand.lib")
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#pragma comment(lib, "cublas.lib")
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#pragma comment(lib, "cudnn.lib")
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#pragma comment(lib, "opencv_core" CV_VERSION_STR CV_EXT_STR)
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#pragma comment(lib, "opencv_imgcodecs" CV_VERSION_STR CV_EXT_STR)
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#pragma comment(lib, "opencv_imgproc" CV_VERSION_STR CV_EXT_STR)
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//#pragma comment(lib, "IlmImf" CV_EXT_STR)
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//#pragma comment(lib, "libjasper" CV_EXT_STR)
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//#pragma comment(lib, "libjpeg" CV_EXT_STR)
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//#pragma comment(lib, "libpng" CV_EXT_STR)
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//#pragma comment(lib, "libtiff" CV_EXT_STR)
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//#pragma comment(lib, "libwebp" CV_EXT_STR)
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//#pragma comment(lib, "ippicvmt.lib")
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#pragma comment(lib, "libboost_iostreams-vc120-mt-gd-1_59.lib")
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#else
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#pragma comment(lib, "caffe.lib")
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#pragma comment(lib, "proto.lib")
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#pragma comment(lib, "libboost_system-vc120-mt-1_59.lib")
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#pragma comment(lib, "libboost_thread-vc120-mt-1_59.lib")
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#pragma comment(lib, "libboost_filesystem-vc120-mt-1_59.lib")
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#pragma comment(lib, "glog.lib")
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#pragma comment(lib, "gflags.lib")
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#pragma comment(lib, "libprotobuf.lib")
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||
#pragma comment(lib, "libhdf5_hl.lib")
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||
#pragma comment(lib, "libhdf5.lib")
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#pragma comment(lib, "zlibstatic.lib")
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#pragma comment(lib, "libopenblas.dll.a")
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#pragma comment(lib, "cudart.lib")
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#pragma comment(lib, "curand.lib")
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#pragma comment(lib, "cublas.lib")
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#pragma comment(lib, "cudnn.lib")
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#pragma comment(lib, "opencv_core" CV_VERSION_STR CV_EXT_STR)
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#pragma comment(lib, "opencv_imgcodecs" CV_VERSION_STR CV_EXT_STR)
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#pragma comment(lib, "opencv_imgproc" CV_VERSION_STR CV_EXT_STR)
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//#pragma comment(lib, "IlmImf" CV_EXT_STR)
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//#pragma comment(lib, "libjasper" CV_EXT_STR)
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//#pragma comment(lib, "libjpeg" CV_EXT_STR)
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//#pragma comment(lib, "libpng" CV_EXT_STR)
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//#pragma comment(lib, "libtiff" CV_EXT_STR)
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//#pragma comment(lib, "libwebp" CV_EXT_STR)
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//#pragma comment(lib, "ippicvmt.lib")
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#pragma comment(lib, "libboost_iostreams-vc120-mt-1_59.lib")
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#endif
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#endif
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// “ü—͉摜‚̃IƒtƒZƒbƒg
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const int offset = 0;
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// srcnn.prototxt‚Å’è‹`‚³‚ꂽƒŒƒCƒ„<C692>[‚Ì<E2809A>”
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const int layer_num = 7;
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const int ConvertMode = CV_RGB2YUV;
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const int ConvertInverseMode = CV_YUV2RGB;
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// <20>Å’áŒÀ•K—v‚ÈCUDAƒhƒ‰ƒCƒo<C692>[‚̃o<C692>[ƒWƒ‡ƒ“
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const int MinCudaDriverVersion = 7050;
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// float‚ȉ摜‚ðuint8_t‚ȉ摜‚É•ÏŠ·‚·‚é<E2809A>Û‚ÌŽlŽÌŒÜ“ü‚ÉŽg‚¤’l
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// https://github.com/nagadomi/waifu2x/commit/797b45ae23665a1c5e3c481c018e48e6f0d0e383
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const double clip_eps8 = (1.0 / 255.0) * 0.5 - (1.0e-7 * (1.0 / 255.0) * 0.5);
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const double clip_eps16 = (1.0 / 65535.0) * 0.5 - (1.0e-7 * (1.0 / 65535.0) * 0.5);
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const double clip_eps32 = 1.0 * 0.5 - (1.0e-7 * 0.5);
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const int kProtoReadBytesLimit = INT_MAX; // Max size of 2 GB minus 1 byte.
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static std::once_flag waifu2x_once_flag;
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static std::once_flag waifu2x_cudnn_once_flag;
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static std::once_flag waifu2x_cuda_once_flag;
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const std::vector<Waifu2x::stOutputExtentionElement> Waifu2x::OutputExtentionList =
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{
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{ L".png", { 8, 16 }, boost::optional<int>(), boost::optional<int>(), boost::optional<int>(), boost::optional<int>() },
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{ L".bmp", { 8 }, boost::optional<int>(), boost::optional<int>(), boost::optional<int>(), boost::optional<int>() },
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{ L".jpg", { 8 }, 0, 100, 95, cv::IMWRITE_JPEG_QUALITY },
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{ L".jp2", { 8, 16 }, boost::optional<int>(), boost::optional<int>(), boost::optional<int>(), boost::optional<int>() },
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{ L".sr", { 8 }, boost::optional<int>(), boost::optional<int>(), boost::optional<int>(), boost::optional<int>() },
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{ L".tif", { 8, 16, 32 }, boost::optional<int>(), boost::optional<int>(), boost::optional<int>(), boost::optional<int>() },
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{ L".hdr", { 8, 16, 32 }, boost::optional<int>(), boost::optional<int>(), boost::optional<int>(), boost::optional<int>() },
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{ L".exr", { 8, 16, 32 }, boost::optional<int>(), boost::optional<int>(), boost::optional<int>(), boost::optional<int>() },
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{ L".ppm", { 8, 16 }, boost::optional<int>(), boost::optional<int>(), boost::optional<int>(), boost::optional<int>() },
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{ L".webp", { 8 }, 1, 100, 100, cv::IMWRITE_WEBP_QUALITY },
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{ L".tga", { 8 }, 0, 1, 0, 0 },
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};
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#ifndef CUDA_CHECK_WAIFU2X
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#define CUDA_CHECK_WAIFU2X(condition) \
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do { \
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cudaError_t error = condition; \
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if(error != cudaSuccess) throw error; \
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} while (0)
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#endif
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#define CUDA_HOST_SAFE_FREE(ptr) \
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do { \
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if (ptr) { \
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cudaFreeHost(ptr); \
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ptr = nullptr; \
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} \
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} while (0)
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#define SAFE_DELETE_WAIFU2X(ptr) \
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do { \
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if (ptr) { \
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delete [] ptr; \
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ptr = nullptr; \
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} \
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} while (0)
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namespace
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{
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class IgnoreErrorCV
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{
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private:
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static int handleError(int status, const char* func_name,
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const char* err_msg, const char* file_name,
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int line, void* userdata)
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{
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return 0;
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}
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public:
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IgnoreErrorCV()
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{
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cv::redirectError(handleError);
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}
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};
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IgnoreErrorCV g_IgnoreErrorCV;
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}
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template<typename BufType>
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static bool writeFile(boost::iostreams::stream<boost::iostreams::file_descriptor> &os, const std::vector<BufType> &buf)
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{
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if (!os)
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return false;
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const auto WriteSize = sizeof(BufType) * buf.size();
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os.write((const char *)buf.data(), WriteSize);
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if (os.fail())
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return false;
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return true;
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}
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template<typename BufType>
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static bool writeFile(const boost::filesystem::path &path, std::vector<BufType> &buf)
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{
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boost::iostreams::stream<boost::iostreams::file_descriptor> os;
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try
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{
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os.open(path, std::ios_base::out | std::ios_base::binary | std::ios_base::trunc);
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}
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catch (...)
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{
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return false;
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}
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return writeFile(os, buf);
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}
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template<typename BufType>
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static bool readFile(boost::iostreams::stream<boost::iostreams::file_descriptor_source> &is, std::vector<BufType> &buf)
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{
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if (!is)
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return false;
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const auto size = is.seekg(0, std::ios::end).tellg();
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is.seekg(0, std::ios::beg);
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buf.resize((size / sizeof(BufType)) + (size % sizeof(BufType)));
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is.read(buf.data(), size);
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if (is.gcount() != size)
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return false;
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return true;
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}
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template<typename BufType>
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static bool readFile(const boost::filesystem::path &path, std::vector<BufType> &buf)
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{
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boost::iostreams::stream<boost::iostreams::file_descriptor_source> is;
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try
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{
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is.open(path, std::ios_base::in | std::ios_base::binary);
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}
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catch (...)
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{
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return false;
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}
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return readFile(is, buf);
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}
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static Waifu2x::eWaifu2xError readProtoText(const boost::filesystem::path &path, ::google::protobuf::Message* proto)
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{
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boost::iostreams::stream<boost::iostreams::file_descriptor_source> is;
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try
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{
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is.open(path, std::ios_base::in);
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}
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catch (...)
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{
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return Waifu2x::eWaifu2xError_FailedOpenModelFile;
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}
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if (!is)
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return Waifu2x::eWaifu2xError_FailedOpenModelFile;
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std::vector<char> tmp;
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if (!readFile(is, tmp))
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return Waifu2x::eWaifu2xError_FailedParseModelFile;
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google::protobuf::io::ArrayInputStream input(tmp.data(), tmp.size());
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const bool success = google::protobuf::TextFormat::Parse(&input, proto);
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if (!success)
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return Waifu2x::eWaifu2xError_FailedParseModelFile;
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return Waifu2x::eWaifu2xError_OK;
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}
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static Waifu2x::eWaifu2xError readProtoBinary(const boost::filesystem::path &path, ::google::protobuf::Message* proto)
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{
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boost::iostreams::stream<boost::iostreams::file_descriptor_source> is;
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try
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{
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is.open(path, std::ios_base::in | std::ios_base::binary);
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}
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catch (...)
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{
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return Waifu2x::eWaifu2xError_FailedOpenModelFile;
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}
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if (!is)
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return Waifu2x::eWaifu2xError_FailedOpenModelFile;
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std::vector<char> tmp;
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if (!readFile(is, tmp))
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return Waifu2x::eWaifu2xError_FailedParseModelFile;
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google::protobuf::io::ArrayInputStream input(tmp.data(), tmp.size());
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google::protobuf::io::CodedInputStream coded_input(&input);
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coded_input.SetTotalBytesLimit(kProtoReadBytesLimit, 536870912);
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const bool success = proto->ParseFromCodedStream(&coded_input);
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if (!success)
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return Waifu2x::eWaifu2xError_FailedParseModelFile;
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return Waifu2x::eWaifu2xError_OK;
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}
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static Waifu2x::eWaifu2xError writeProtoBinary(const ::google::protobuf::Message& proto, const boost::filesystem::path &path)
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{
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boost::iostreams::stream<boost::iostreams::file_descriptor> os;
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try
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{
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os.open(path, std::ios_base::out | std::ios_base::binary | std::ios_base::trunc);
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}
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catch (...)
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{
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return Waifu2x::eWaifu2xError_FailedOpenModelFile;
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}
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if (!os)
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return Waifu2x::eWaifu2xError_FailedWriteModelFile;
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if (!proto.SerializePartialToOstream(&os))
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return Waifu2x::eWaifu2xError_FailedWriteModelFile;
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return Waifu2x::eWaifu2xError_OK;
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}
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Waifu2x::Waifu2x() : is_inited(false), isCuda(false), input_block(nullptr), dummy_data(nullptr), output_block(nullptr)
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{
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}
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Waifu2x::~Waifu2x()
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{
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destroy();
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}
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// cuDNN‚ªŽg‚¦‚é‚©ƒ`ƒFƒbƒN<C692>BŒ»<C592>óWindows‚Ì‚Ý
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Waifu2x::eWaifu2xcuDNNError Waifu2x::can_use_cuDNN()
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{
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static eWaifu2xcuDNNError cuDNNFlag = eWaifu2xcuDNNError_NotFind;
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std::call_once(waifu2x_cudnn_once_flag, [&]()
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{
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#if defined(WIN32) || defined(WIN64)
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HMODULE hModule = LoadLibrary(TEXT(CUDNN_DLL_NAME));
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if (hModule != NULL)
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{
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typedef cudnnStatus_t(__stdcall * cudnnCreateType)(cudnnHandle_t *);
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typedef cudnnStatus_t(__stdcall * cudnnDestroyType)(cudnnHandle_t);
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typedef uint64_t(__stdcall * cudnnGetVersionType)();
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cudnnCreateType cudnnCreateFunc = (cudnnCreateType)GetProcAddress(hModule, "cudnnCreate");
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cudnnDestroyType cudnnDestroyFunc = (cudnnDestroyType)GetProcAddress(hModule, "cudnnDestroy");
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cudnnGetVersionType cudnnGetVersionFunc = (cudnnGetVersionType)GetProcAddress(hModule, "cudnnGetVersion");
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if (cudnnCreateFunc != nullptr && cudnnDestroyFunc != nullptr && cudnnGetVersionFunc != nullptr)
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{
|
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if (cudnnGetVersionFunc() >= 3000)
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{
|
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cudnnHandle_t h;
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if (cudnnCreateFunc(&h) == CUDNN_STATUS_SUCCESS)
|
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{
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if (cudnnDestroyFunc(h) == CUDNN_STATUS_SUCCESS)
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cuDNNFlag = eWaifu2xcuDNNError_OK;
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else
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cuDNNFlag = eWaifu2xcuDNNError_CannotCreate;
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}
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else
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cuDNNFlag = eWaifu2xcuDNNError_CannotCreate;
|
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}
|
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else
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cuDNNFlag = eWaifu2xcuDNNError_OldVersion;
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}
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else
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cuDNNFlag = eWaifu2xcuDNNError_NotFind;
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|
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FreeLibrary(hModule);
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}
|
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#endif
|
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});
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return cuDNNFlag;
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}
|
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|
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// CUDA‚ªŽg‚¦‚é‚©ƒ`ƒFƒbƒN
|
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Waifu2x::eWaifu2xCudaError Waifu2x::can_use_CUDA()
|
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{
|
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static eWaifu2xCudaError CudaFlag = eWaifu2xCudaError_NotFind;
|
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std::call_once(waifu2x_cuda_once_flag, [&]()
|
||
{
|
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int driverVersion = 0;
|
||
if (cudaDriverGetVersion(&driverVersion) == cudaSuccess)
|
||
{
|
||
if (driverVersion > 0)
|
||
{
|
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int runtimeVersion;
|
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if (cudaRuntimeGetVersion(&runtimeVersion) == cudaSuccess)
|
||
{
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if (runtimeVersion >= MinCudaDriverVersion && driverVersion >= runtimeVersion)
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CudaFlag = eWaifu2xCudaError_OK;
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else
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CudaFlag = eWaifu2xCudaError_OldVersion;
|
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}
|
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else
|
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CudaFlag = eWaifu2xCudaError_NotFind;
|
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}
|
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else
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CudaFlag = eWaifu2xCudaError_NotFind;
|
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}
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else
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CudaFlag = eWaifu2xCudaError_NotFind;
|
||
});
|
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|
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return CudaFlag;
|
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}
|
||
|
||
void Waifu2x::init_liblary()
|
||
{
|
||
}
|
||
|
||
void Waifu2x::quit_liblary()
|
||
{
|
||
}
|
||
|
||
cv::Mat Waifu2x::LoadMat(const boost::filesystem::path &path)
|
||
{
|
||
cv::Mat mat;
|
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LoadMat(mat, path);
|
||
|
||
return mat;
|
||
}
|
||
|
||
Waifu2x::eWaifu2xError Waifu2x::AlphaMakeBorder(std::vector<cv::Mat> &planes, const cv::Mat &alpha, const int offset)
|
||
{
|
||
// ‚±‚̃J<C692>[ƒlƒ‹‚Ɖ摜‚Ì<E2809A>ô<EFBFBD>ž‚Ý‚ð<E2809A>s‚¤‚Æ<E2809A>A(x, y)‚ð’†<E28099>S‚Æ‚µ‚½3<C2BD>~3—̈æ‚Ì<E2809A>‡Œv’l‚ª‹<C2AA>‚Ü‚é
|
||
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); // ƒAƒ‹ƒtƒ@ƒ`ƒƒƒ“ƒlƒ‹‚ð“ñ’l‰»‚µ‚ă}ƒXƒN‚Æ‚µ‚Ĉµ‚¤
|
||
|
||
cv::Mat mask_nega;
|
||
cv::threshold(mask, mask_nega, 0.0, 1.0, cv::THRESH_BINARY_INV); // ”½“]‚µ‚½ƒ}ƒXƒN<C692>i’l‚ª1‚̉Ó<E280B0>Š‚ÍŠ®‘S“§–¾‚Å‚È‚¢—LŒø‚ȉæ‘f‚Æ‚È‚é<E2809A>j
|
||
|
||
for (auto &p : planes) // Š®‘S‚É“§–¾‚ȃsƒNƒZƒ‹‚É‚ ‚éƒSƒ~‚ðŽæ‚é
|
||
{
|
||
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); // ƒ}ƒXƒN‚Ì3<C38C>~3—̈æ‚Ì<E2809A>‡Œv’l‚ð‹<C3B0>‚ß‚é
|
||
|
||
cv::Mat mask_nega_u8;
|
||
mask_nega.convertTo(mask_nega_u8, CV_8U, 255.0, clip_eps8); // mask_nega‚ÌCV_U8”Å<E2809D>iOpenCV‚ÌAPI<50>ã•K—v‚É‚È‚é<E2809A>j
|
||
|
||
for (auto &p : planes) // 1ƒ`ƒƒƒ“ƒlƒ‹‚¸‚Â<E2809A>ˆ—<CB86>
|
||
{
|
||
// ƒ`ƒƒƒ“ƒlƒ‹‚Ì3<C38C>~3—̈æ“à‚Ì—LŒø‰æ‘f‚Ì•½‹Ï’l‚ð‹<C3B0>‚ß‚é
|
||
cv::Mat border;
|
||
cv::filter2D(p, border, -1, sum2d_kernel, cv::Point(-1, -1), 0, cv::BORDER_DEFAULT);
|
||
border /= mask_weight;
|
||
|
||
// ƒ`ƒƒƒ“ƒlƒ‹‚Ì—LŒø‚ȉæ‘f‚Ì•”•ª‚É<E2809A>AŒvŽZ‚µ‚½•½‹Ï’l‚ðƒRƒs<C692>[
|
||
border.copyTo(p, mask_nega_u8);
|
||
}
|
||
|
||
// ƒ}ƒXƒN‚ð1‰ñ–c’£‚³‚¹‚½‚à‚Ì‚ð<E2809A>V‚µ‚¢ƒ}ƒXƒN‚Æ‚·‚é(ƒ}ƒXƒN‚Ì3<C38C>~3—̈æ‚Ì<E2809A>‡Œv’l‚ð‹<C3B0>‚ß‚½‚à‚Ì‚Ì”ñ0—̈æ‚Í<E2809A>Aƒ}ƒXƒN‚ð1‰ñ–c’£‚³‚¹‚½‚à‚̗̂̈æ‚É“™‚µ‚¢)
|
||
cv::threshold(mask_weight, mask, 0.0, 1.0, cv::THRESH_BINARY);
|
||
// <20>V‚µ‚¢ƒ}ƒXƒN‚Ì”½“]‚µ‚½ƒ}ƒXƒN‚ðŒvŽZ
|
||
cv::threshold(mask, mask_nega, 0.0, 1.0, cv::THRESH_BINARY_INV);
|
||
}
|
||
|
||
// ‰æ‘f‚ð0‚©‚ç1‚ɃNƒŠƒbƒsƒ“ƒO
|
||
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;
|
||
}
|
||
|
||
// ‰æ‘œ‚ð“Ç‚Ý<E2809A>ž‚ñ‚Å’l‚ð0.0f<EFBFBD>`1.0f‚͈̔͂ɕϊ·
|
||
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; // Œ³‚©‚ç0.0<EFBFBD>`1.0‚Ì‚Í‚¸‚È‚Ì‚Å•ÏŠ·‚Í•K—v‚È‚¢
|
||
break;
|
||
}
|
||
|
||
original_image.release();
|
||
|
||
if (convert.channels() == 1)
|
||
cv::cvtColor(convert, convert, cv::COLOR_GRAY2BGR);
|
||
else if (convert.channels() == 4)
|
||
{
|
||
// ƒAƒ‹ƒtƒ@ƒ`ƒƒƒ“ƒlƒ‹•t‚«‚¾‚Á‚½‚瓧–¾‚ȃsƒNƒZƒ‹‚Ì‚Æ•s“§–¾‚ȃsƒNƒZƒ‹‚Ì‹«ŠE•”•ª‚Ì<E2809A>F‚ð<E2809A>L‚°‚é
|
||
|
||
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, 0);
|
||
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‚¾‚©‚çBGR‚É•ÏŠ·
|
||
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;
|
||
}
|
||
|
||
// ‰æ‘œ‚©‚ç‹P“x‚̉摜‚ðŽæ‚è<E2809A>o‚·
|
||
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;
|
||
}
|
||
|
||
// “ü—͉摜‚Ì(Photoshop‚Å‚¢‚¤)ƒLƒƒƒ“ƒoƒXƒTƒCƒY‚ðoutput_size‚Ì”{<7B>”‚É•Ï<E280A2>X
|
||
// ‰æ‘œ‚Í<E2809A>¶<EFBFBD>ã”z’u<E28099>A—]”’‚Ícv::BORDER_REPLICATE‚Å–„‚ß‚é
|
||
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;
|
||
}
|
||
|
||
// ‰æ‘œ‚ðcv::INTER_NEAREST‚Å“ñ”{‚ÉŠg‘債‚Ä<E2809A>APaddingImage()‚ŃpƒfƒBƒ“ƒO‚·‚é
|
||
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);
|
||
}
|
||
|
||
// “ü—͉摜‚ðzoom_size‚Ì‘å‚«‚³‚Écv::INTER_CUBIC‚ÅŠg‘債<E2809A>A<EFBFBD>F<EFBFBD>î•ñ‚Ì‚Ý‚ðŽc‚·
|
||
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();
|
||
|
||
// ‚±‚ÌY<C38C>¬•ª‚ÍŽg‚í‚È‚¢‚̂ʼnð•ú
|
||
cubic_planes[0].release();
|
||
|
||
return eWaifu2xError_OK;
|
||
}
|
||
|
||
// ƒ‚ƒfƒ‹ƒtƒ@ƒCƒ‹‚©‚çƒlƒbƒgƒ<67><C692>[ƒN‚ð<E2809A>\’z
|
||
// process‚Åcudnn‚ªŽw’肳‚ê‚È‚©‚Á‚½<E2809A>ê<EFBFBD>‡‚ÍcuDNN‚ªŒÄ‚Ñ<E2809A>o‚³‚ê‚È‚¢‚悤‚É•Ï<E280A2>X‚·‚é
|
||
Waifu2x::eWaifu2xError Waifu2x::ConstractNet(boost::shared_ptr<caffe::Net<float>> &net, const boost::filesystem::path &model_path, const boost::filesystem::path ¶m_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, ¶m_model);
|
||
const auto retParamBin = readProtoBinary(caffemodel_path, ¶m_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(), ¶m_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 ¶m, 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 ¶m_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, ¶m);
|
||
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(¶m);
|
||
|
||
ret = writeProtoBinary(param, caffemodel_path);
|
||
if (ret != eWaifu2xError_OK)
|
||
return ret;
|
||
}
|
||
catch (...)
|
||
{
|
||
return eWaifu2xError_FailedConstructModel;
|
||
}
|
||
|
||
input_plane = inputPlane;
|
||
|
||
return eWaifu2xError_OK;
|
||
}
|
||
|
||
// ƒlƒbƒgƒ<67><C692>[ƒN‚ðŽg‚Á‚ĉ摜‚ð<E2809A>Ä<EFBFBD>\’z‚·‚é
|
||
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;
|
||
|
||
// ‰æ‘œ‚Í(<28>Á”ïƒ<C3AF>ƒ‚ƒŠ‚Ì“s<E2809C>‡<EFBFBD>ã)output_size*output_size‚É•ª‚¯‚Ä<E2809A>Ä<EFBFBD>\’z‚·‚é
|
||
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;
|
||
// ‰æ‘œ‚𒆉›‚ɃpƒfƒBƒ“ƒO<C692>B—]”’‚Ícv::BORDER_REPLICATE‚Å–„‚ß‚é
|
||
// ŽÀ‚Íim‚ʼnæ‘f‚ª‘¶<E28098>Ý‚·‚é•”•ª‚Í—]”’‚Æ”FŽ¯‚³‚ê‚È‚¢‚ª<E2809A>Ainner_padding‚ªlayer_num‚Åouter_padding‚ª1ˆÈ<CB86>ã‚È‚ç‚»‚±‚Ì•”•ª‚̉æ‘f‚ÍŒ‹‰Ê‰æ‘œ‚Æ‚µ‚ÄŽæ‚è<E2809A>o‚·•”•ª‚ɂ͉e‹¿‚µ‚È‚¢
|
||
cv::copyMakeBorder(someimg, someborderimg, top, bottom, left, right, cv::BORDER_REPLICATE);
|
||
someimg.release();
|
||
|
||
// ‰æ‘œ‚ð’¼—ñ‚É•ÏŠ·
|
||
{
|
||
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);
|
||
|
||
// ƒlƒbƒgƒ<67><C692>[ƒN‚ɉ摜‚ð“ü—Í
|
||
input_blob->set_cpu_data(input_block);
|
||
|
||
// ŒvŽZ
|
||
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);
|
||
|
||
// Œ‹‰Ê‚ð<E2809A>o—͉摜‚ɃRƒs<C692>[
|
||
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“™‚Ì<E2809A>‰Šú‰»
|
||
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‚ªŽg‚¦‚»‚¤‚È‚çcuDNN‚ðŽg‚¤
|
||
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‚ª‘Š‘΃pƒX‚È‚ç<E2809A>â‘΃pƒX‚É’¼‚·
|
||
{
|
||
// ‚Ü‚¸‚̓JƒŒƒ“ƒgƒfƒBƒŒƒNƒgƒŠ‰º‚É‚ ‚é‚©’T‚·
|
||
mode_dir_path = boost::filesystem::absolute(model_dir);
|
||
if (!boost::filesystem::exists(mode_dir_path) && argc >= 1) // –³‚©‚Á‚½‚çargv[0]‚©‚çŽÀ<C5BD>sƒtƒ@ƒCƒ‹‚Ì‚ ‚éƒtƒHƒ‹ƒ_‚ð<E2809A>„’肵<E2809A>A‚»‚̃tƒHƒ‹ƒ_‰º‚É‚ ‚é‚©’T‚·
|
||
{
|
||
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—pƒoƒbƒtƒ@‚ɃRƒs<C692>[(‚ ‚é‚¢‚̓pƒfƒBƒ“ƒO‚ð‚Æ‚é)
|
||
{
|
||
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‚ðRGB‚É•À‚Ñ‘Ö‚¦
|
||
{
|
||
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;
|
||
|
||
// RLEˆ³<CB86>k‚Ì<E2809A>Ý’è
|
||
bool isSet = false;
|
||
const auto &OutputExtentionList = Waifu2x::OutputExtentionList;
|
||
for (const auto &elm : OutputExtentionList)
|
||
{
|
||
if (elm.ext == L".tga")
|
||
{
|
||
if (elm.imageQualitySettingVolume && output_quality)
|
||
{
|
||
stbi_write_tga_with_rle = *output_quality;
|
||
isSet = true;
|
||
}
|
||
|
||
break;
|
||
}
|
||
}
|
||
|
||
// <20>ݒ肳‚ê‚È‚©‚Á‚½‚̂ŃfƒtƒHƒ‹ƒg‚É‚·‚é
|
||
if (!isSet)
|
||
stbi_write_tga_with_rle = 1;
|
||
|
||
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‚©‚çRGB‚É‚·‚é
|
||
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;
|
||
|
||
// ƒpƒfƒBƒ“ƒO‚ðŽæ‚è•¥‚¤
|
||
im = im(cv::Rect(offset, offset, image_size.width, image_size.height));
|
||
|
||
// ’l‚ð0<C3B0>`1‚ɃNƒŠƒbƒsƒ“ƒO
|
||
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;
|
||
|
||
// ƒpƒfƒBƒ“ƒO‚ðŽæ‚è•¥‚¤
|
||
im = im(cv::Rect(offset, offset, image_size.width, image_size.height));
|
||
|
||
// ’l‚ð0<C3B0>`1‚ɃNƒŠƒbƒsƒ“ƒO
|
||
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) // •<>’Ê‚É<E2809A>ˆ—<CB86>
|
||
{
|
||
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>‚’¼Ž²”½“]
|
||
|
||
ret = ReconstructFloatMat(isReconstructNoise, isReconstructScale, cancel_func, in, in);
|
||
if (ret != eWaifu2xError_OK)
|
||
return ret;
|
||
|
||
if (i >= 4)
|
||
cv::flip(in, in, 1); // <20>‚’¼Ž²”½“]
|
||
|
||
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); // ‚±‚Ì’n“_‚Å‚Í‚Ü‚¾RGB‚È‚±‚Æ‚É’<C389>ˆÓ
|
||
}
|
||
|
||
// ’l‚ð0<C3B0>`1‚ɃNƒŠƒbƒsƒ“ƒO
|
||
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>Ä<EFBFBD>\’z‚µ‚½‹P“x‰æ‘œ‚ÆCreateZoomColorImage()‚Å<E2809A>ì<EFBFBD>¬‚µ‚½<E2809A>F<EFBFBD>î•ñ‚ðƒ}<7D>[ƒW‚µ‚Ä’Ê<E28099>í‚̉摜‚É•ÏŠ·‚µ<E2809A>A<EFBFBD>‘‚«<E2809A>ž‚Þ
|
||
|
||
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‚©‚çBGR‚É’¼‚·
|
||
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];
|
||
}
|
||
|
||
// ƒAƒ‹ƒtƒ@ƒ`ƒƒƒ“ƒlƒ‹‚ª‚ ‚Á‚½‚çƒAƒ‹ƒtƒ@‚ð•t‰Á‚·‚é
|
||
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);
|
||
}
|
||
|
||
// ’l‚ð0<C3B0>`1‚ɃNƒŠƒbƒsƒ“ƒO
|
||
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::waifu2xConvetedMat(const bool isJpeg, const cv::Mat &inMat, cv::Mat &outMat, const waifu2xCancelFunc cancel_func)
|
||
{
|
||
Waifu2x::eWaifu2xError ret;
|
||
|
||
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 reconstruct_image;
|
||
ret = Reconstruct(isReconstructNoise, isReconstructScale, cancel_func, inMat, reconstruct_image);
|
||
if (ret != eWaifu2xError_OK)
|
||
return ret;
|
||
|
||
cv::Mat process_image;
|
||
ret = AfterReconstructFloatMatProcess(isReconstructScale, cancel_func, inMat, reconstruct_image, process_image);
|
||
if (ret != eWaifu2xError_OK)
|
||
return ret;
|
||
|
||
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—Í‚ªfloatŒ`Ž®‚È‚ç•ÏŠ·‚µ‚È‚¢
|
||
process_image.convertTo(write_iamge, cv_depth, max_val, eps);
|
||
else
|
||
write_iamge = process_image;
|
||
|
||
process_image.release();
|
||
|
||
// Š®‘S“§–¾‚̃sƒNƒZƒ‹‚Ì<E2809A>F‚ð<E2809A>Á‚·(<28>ˆ—<CB86>‚Ì“s<E2809C>‡<EFBFBD>ã<EFBFBD>AŠ®‘S“§–¾‚̃sƒNƒZƒ‹‚É‚à<E2809A>F‚ð•t‚¯‚½‚©‚ç)
|
||
// ƒ‚ƒfƒ‹‚É‚æ‚Á‚Ă͉摜‘Sˆæ‚ÌŠ®‘S“§–¾‚Ì<E2809A>ê<EFBFBD>Š‚É‚²‚<E2809A>¬‚³‚¢’l‚̃Aƒ‹ƒtƒ@‚ª<E2809A>L‚ª‚邱‚Æ‚ª‚ ‚é<E2809A>B‚»‚ê‚ð<E2809A>Á‚·‚½‚ß‚Écv_depth‚Ö•ÏŠ·‚µ‚Ä‚©‚炱‚Ì<E2809A>ˆ—<CB86>‚ð<E2809A>s‚¤‚±‚Æ‚É‚µ‚½
|
||
// (‚½‚¾‚µcv_depth‚ª32‚Ì<E2809A>ê<EFBFBD>‡‚¾‚ƈӖ¡‚Í–³‚¢‚ª)
|
||
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); // ƒAƒ‹ƒtƒ@ƒ`ƒƒƒ“ƒlƒ‹‚ð“ñ’l‰»‚µ‚ă}ƒXƒN‚Æ‚µ‚Ĉµ‚¤
|
||
|
||
// ƒAƒ‹ƒtƒ@ƒ`ƒƒƒ“ƒlƒ‹‚ª0‚Ì‚Æ‚±‚ë‚Ì<E2809A>F‚ð<E2809A>Á‚·
|
||
planes[0] = planes[0].mul(mask);
|
||
planes[1] = planes[1].mul(mask);
|
||
planes[2] = planes[2].mul(mask);
|
||
|
||
cv::merge(planes, write_iamge);
|
||
}
|
||
|
||
outMat = write_iamge;
|
||
|
||
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");
|
||
|
||
cv::Mat float_image;
|
||
ret = LoadMat(float_image, input_file);
|
||
if (ret != eWaifu2xError_OK)
|
||
return ret;
|
||
|
||
cv::Mat write_iamge;
|
||
ret = waifu2xConvetedMat(isJpeg, float_image, write_iamge, cancel_func);
|
||
if (ret != eWaifu2xError_OK)
|
||
return ret;
|
||
|
||
ret = WriteMat(write_iamge, output_file, output_quality);
|
||
if (ret != eWaifu2xError_OK)
|
||
return ret;
|
||
|
||
return eWaifu2xError_OK;
|
||
}
|
||
|
||
Waifu2x::eWaifu2xError Waifu2x::waifu2x(double factor, const void* source, void* dest, int width, int height, int in_channel, int in_stride, int out_channel, int out_stride)
|
||
{
|
||
Waifu2x::eWaifu2xError ret;
|
||
|
||
if (!is_inited)
|
||
return eWaifu2xError_NotInitialized;
|
||
|
||
if (output_depth != 8) // <20>o—Í<E28094>[“x‚Í8bit‚¾‚¯
|
||
return eWaifu2xError_InvalidParameter;
|
||
|
||
cv::Mat float_image;
|
||
|
||
// Mat‚Ö•ÏŠ·
|
||
{
|
||
cv::Mat original_image(cv::Size(width, height), CV_MAKETYPE(CV_8U, in_channel), (void *)source, in_stride);
|
||
|
||
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; // Œ³‚©‚ç0.0<EFBFBD>`1.0‚Ì‚Í‚¸‚È‚Ì‚Å•ÏŠ·‚Í•K—v‚È‚¢
|
||
break;
|
||
}
|
||
|
||
original_image.release();
|
||
|
||
if (convert.channels() == 1)
|
||
cv::cvtColor(convert, convert, cv::COLOR_GRAY2BGR);
|
||
else if (convert.channels() == 4)
|
||
{
|
||
// ƒAƒ‹ƒtƒ@ƒ`ƒƒƒ“ƒlƒ‹•t‚«‚¾‚Á‚½‚瓧–¾‚ȃsƒNƒZƒ‹‚Ì‚Æ•s“§–¾‚ȃsƒNƒZƒ‹‚Ì‹«ŠE•”•ª‚Ì<E2809A>F‚ð<E2809A>L‚°‚é
|
||
|
||
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;
|
||
}
|
||
|
||
const auto oldScale = scale_ratio;
|
||
scale_ratio = factor;
|
||
|
||
cv::Mat write_iamge;
|
||
ret = waifu2xConvetedMat(false, float_image, write_iamge);
|
||
|
||
scale_ratio = oldScale;
|
||
|
||
if (ret != eWaifu2xError_OK)
|
||
return ret;
|
||
|
||
float_image.release();
|
||
|
||
// <20>o—Í”z—ñ‚Ö<E2809A>‘‚«<E2809A>ž‚Ý
|
||
{
|
||
const auto width = write_iamge.size().width;
|
||
const auto stride = write_iamge.step1();
|
||
for (int i = 0; i < write_iamge.size().height; i++)
|
||
memcpy((uint8_t *)dest + out_stride * i, write_iamge.data + stride * i, stride);
|
||
}
|
||
|
||
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;
|
||
}
|
||
|
||
// •s–¾‚¾‚¯‚Ç‚Æ‚è‚ ‚¦‚¸CV_8U‚ð•Ô‚µ‚Ä‚¨‚
|
||
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;
|
||
}
|
||
|
||
// •s–¾‚¾‚¯‚Ç‚Æ‚è‚ ‚¦‚¸255.0‚ð•Ô‚µ‚Ä‚¨‚
|
||
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;
|
||
}
|
||
|
||
// •s–¾‚¾‚¯‚Ç‚Æ‚è‚ ‚¦‚¸clip_eps8•Ô‚µ‚Ä‚¨‚
|
||
return clip_eps8;
|
||
}
|