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histmatching: fix cropping of the target (broken by recent refactoring)

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This commit is contained in:
Alberto Griggio 2018-01-30 10:24:19 +01:00
parent 71a3af0c86
commit 5effd15bb3
1 changed files with 28 additions and 39 deletions
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67
rtengine/histmatching.cc
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@ -194,58 +194,47 @@ void RawImageSource::getAutoMatchedToneCurve(std::vector<double> &outCurve)
std::unique_ptr<IImage8> target;
{
int tw = source->getWidth(), th = source->getHeight();
float thumb_ratio = float(std::max(tw, th)) / float(std::min(tw, th));
float target_ratio = float(std::max(fw, fh)) / float(std::min(fw, fh));
RawMetaDataLocation rml;
eSensorType sensor_type;
double scale;
int w = fw / skip, h = fh / skip;
std::unique_ptr<Thumbnail> thumb(Thumbnail::loadFromRaw(getFileName(), rml, sensor_type, w, h, 1, false, false));
target.reset(thumb->processImage(neutral, sensor_type, fh / skip, TI_Nearest, getMetaData(), scale, false));
int sw = source->getWidth(), sh = source->getHeight();
int tw = target->getWidth(), th = target->getHeight();
float thumb_ratio = float(std::max(sw, sh)) / float(std::min(sw, sh));
float target_ratio = float(std::max(tw, th)) / float(std::min(tw, th));
int cx = 0, cy = 0;
if (std::abs(thumb_ratio - target_ratio) > 0.01) {
if (thumb_ratio > target_ratio) {
// crop the height
int ch = fh - (fw * float(th) / float(tw));
int ch = th - (tw * float(sh) / float(sw));
cy += ch / 2;
fh -= ch;
th -= ch;
} else {
// crop the width
int cw = fw - (fh * float(tw) / float(th));
int cw = tw - (th * float(sw) / float(sh));
cx += cw / 2;
fw -= cw;
tw -= cw;
}
if (settings->verbose) {
std::cout << "histogram matching: cropping target to get an aspect ratio of " << std::fixed << std::setprecision(2) << thumb_ratio << ":1, new full size is " << fw << "x" << fh << std::endl;
std::cout << "histogram matching: cropping target to get an aspect ratio of " << std::fixed << std::setprecision(2) << thumb_ratio << ":1, new size is " << tw << "x" << th << std::endl;
}
}
PreviewProps pp(cx, cy, fw, fh, skip);
ColorTemp currWB = getWB();
{
RawMetaDataLocation rml;
eSensorType sensor_type;
double scale;
int w = fw / skip, h = fh / skip;
std::unique_ptr<Thumbnail> thumb(Thumbnail::loadFromRaw(getFileName(), rml, sensor_type, w, h, 1, false, false));
target.reset(thumb->processImage(neutral, sensor_type, fh / skip, TI_Nearest, getMetaData(), scale, false));
Image8 *tmp = new Image8(tw, th);
#ifdef _OPENMP
#pragma omp parallel for
#endif
for (int y = 0; y < th; ++y) {
for (int x = 0; x < tw; ++x) {
tmp->r(y, x) = target->r(y+cy, x+cx);
tmp->g(y, x) = target->g(y+cy, x+cx);
tmp->b(y, x) = target->b(y+cy, x+cx);
}
}
target.reset(tmp);
}
// std::unique_ptr<Imagefloat> image(new Imagefloat(int(fw / skip), int(fh / skip)));
// {
// RawImageSource rsrc;
// rsrc.load(getFileName());
// rsrc.preprocess(neutral.raw, neutral.lensProf, neutral.coarse, false);
// rsrc.demosaic(neutral.raw);
// rsrc.getImage(currWB, TR_NONE, image.get(), pp, neutral.toneCurve, neutral.raw);
// }
// this could probably be made faster -- ideally we would need to just
// perform the transformation from camera space to the output space
// (taking gamma into account), but I couldn't find anything
// ready-made, so for now this will do. Remember the famous quote:
// "premature optimization is the root of all evil" :-)
// convertColorSpace(image.get(), neutral.icm, currWB);
// ImProcFunctions ipf(&neutral);
// LabImage tmplab(image->getWidth(), image->getHeight());
// ipf.rgb2lab(*image, tmplab, neutral.icm.working);
// image.reset(ipf.lab2rgbOut(&tmplab, 0, 0, tmplab.W, tmplab.H, neutral.icm));
// target.reset(image->to8());
if (settings->verbose) {
std::cout << "histogram matching: generated neutral rendering" << std::endl;