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;
// パディングを取り払う
im = im(cv::Rect(offset, offset, image_size.width, image_size.height));
// 値を0〜1にクリッピング
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;
// パディングを取り払う
im = im(cv::Rect(offset, offset, image_size.width, image_size.height));
// 値を0〜1にクリッピング
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::waifu2x(int factor, const uint32_t* source, uint32_t* dest, int width, int height)
{
Waifu2x::eWaifu2xError ret;
if (!is_inited)
return eWaifu2xError_NotInitialized;
cv::Mat float_image;
ret = LoadMat(float_image, source, width, height);
if (ret != eWaifu2xError_OK)
return ret;
cv::Mat im;
if (input_plane == 1)
return eWaifu2xError_NotInitialized;
else
{
std::vector<cv::Mat> planes;
cv::split(float_image, planes);
if (float_image.channels() == 4)
planes.resize(3);
// BGRからRGBにする
//std::swap(planes[0], planes[2]);
cv::merge(planes, im);
}
cv::Size_<int> image_size = im.size();
const bool isReconstructNoise = mode == "noise" || mode == "noise_scale" || mode == "auto_scale";
const bool isReconstructScale = mode == "scale" || mode == "noise_scale";
if (isReconstructNoise)
{
PaddingImage(im, im);
ret = ReconstructImage(net_noise, im);
if (ret != eWaifu2xError_OK)
return ret;
// パディングを取り払う
im = im(cv::Rect(offset, offset, image_size.width, image_size.height));
}
const int scale2 = ceil(log2((double)factor));
const double shrinkRatio = (double)factor / std::pow(2.0, (double)scale2);
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;
// パディングを取り払う
im = im(cv::Rect(offset, offset, image_size.width, image_size.height));
}
}
cv::Mat process_image;
if (input_plane == 1)
{
// 再構築した輝度画像とCreateZoomColorImage()で作成した色情報をマージして通常の画像に変換し、書き込む
std::vector<cv::Mat> color_planes;
CreateZoomColorImage(float_image, image_size, color_planes);
float_image.release();
color_planes[0] = im;
im.release();
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(im, planes);
// RGBからBGRに直す
//std::swap(planes[0], planes[2]);
cv::merge(planes, process_image);
}
cv::Mat alpha;
if (float_image.channels() == 4)
{
std::vector<cv::Mat> planes;
cv::split(float_image, planes);
alpha = planes[3];
cv::resize(alpha, alpha, image_size, 0.0, 0.0, cv::INTER_CUBIC);
}
// アルファチャンネルがあったら、アルファを付加してカラーからアルファの影響を抜く
if (!alpha.empty())
{
std::vector<cv::Mat> planes;
cv::split(process_image, planes);
process_image.release();
planes.push_back(alpha);
cv::Mat w2 = planes[3];
planes[0] = (planes[0]).mul(1.0 / w2);
planes[1] = (planes[1]).mul(1.0 / w2);
planes[2] = (planes[2]).mul(1.0 / w2);
cv::merge(planes, process_image);
}
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);
cv::Mat write_iamge;
process_image.convertTo(write_iamge, CV_8U, 255.0);
process_image.release();
/*
ret = WriteMat(write_iamge, output_file);
if (ret != eWaifu2xError_OK)
return ret;
write_iamge.release();
*/
{
const auto width = write_iamge.size().width;
const auto stride = write_iamge.step1();
for (int i = 0; i < write_iamge.size().height; i++)
memcpy(dest + width * i, write_iamge.data + stride * i, stride);
}
return eWaifu2xError_OK;
}
