212 lines
6.7 KiB
C++
212 lines
6.7 KiB
C++
/* -*- C++ -*-
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*
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* This file is part of RawTherapee.
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*
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* Copyright (c) 2018 Alberto Griggio <alberto.griggio@gmail.com>
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*
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* RawTherapee is free software: you can redistribute it and/or modify
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* it under the terms of the GNU General Public License as published by
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* the Free Software Foundation, either version 3 of the License, or
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* (at your option) any later version.
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*
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* RawTherapee is distributed in the hope that it will be useful,
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* but WITHOUT ANY WARRANTY; without even the implied warranty of
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* MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
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* GNU General Public License for more details.
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*
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* You should have received a copy of the GNU General Public License
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* along with RawTherapee. If not, see <http://www.gnu.org/licenses/>.
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*/
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#include "rawimagesource.h"
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#include "rtthumbnail.h"
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#include "curves.h"
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#include "color.h"
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#include "rt_math.h"
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#include "iccstore.h"
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#include "../rtgui/mydiagonalcurve.h"
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#include "improcfun.h"
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#define BENCHMARK
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#include "StopWatch.h"
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#include <iostream>
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namespace rtengine {
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extern const Settings *settings;
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namespace {
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std::vector<int> getCdf(const IImage8 &img)
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{
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std::vector<int> ret(256);
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for (int y = 0; y < img.getHeight(); ++y) {
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for (int x = 0; x < img.getWidth(); ++x) {
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int lum = LIM(0, int(Color::rgbLuminance(float(img.r(y, x)), float(img.g(y, x)), float(img.b(y, x)))), 255);
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++ret[lum];
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}
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}
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int sum = 0;
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for (size_t i = 0; i < ret.size(); ++i) {
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sum += ret[i];
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ret[i] = sum;
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}
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return ret;
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}
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int findMatch(int val, const std::vector<int> &cdf, int j)
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{
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if (cdf[j] <= val) {
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for (; j < int(cdf.size()); ++j) {
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if (cdf[j] == val) {
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return j;
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} else if (cdf[j] > val) {
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return (cdf[j] - val <= val - cdf[j-1] ? j : j-1);
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}
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}
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return 255;
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} else {
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for (; j >= 0; --j) {
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if (cdf[j] == val) {
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return j;
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} else if (cdf[j] < val) {
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return (val - cdf[j] <= cdf[j+1] - val ? j : j+1);
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}
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}
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return 0;
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}
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}
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void mappingToCurve(const std::vector<int> &mapping, std::vector<double> &curve)
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{
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curve.clear();
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const int npoints = 8;
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int idx = 1;
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for (; idx < int(mapping.size()); ++idx) {
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if (mapping[idx] >= idx) {
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break;
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}
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}
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int step = max(int(mapping.size())/npoints, 1);
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auto coord = [](int v) -> double { return double(v)/255.0; };
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auto doit =
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[&](int start, int stop, int step, bool addstart) -> void
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{
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int prev = start;
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if (addstart) {
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curve.push_back(coord(start));
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curve.push_back(coord(mapping[start]));
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}
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for (int i = start; i < stop; ++i) {
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int v = mapping[i];
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bool change = i > 0 && v != mapping[i-1];
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int diff = i - prev;
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if (change && std::abs(diff - step) <= 1) {
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curve.push_back(coord(i));
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curve.push_back(coord(v));
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prev = i;
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}
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}
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};
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doit(0, idx, idx > step ? step : idx / 2, true);
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doit(idx, int(mapping.size()), step, idx - step > step / 2);
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if (curve.size() <= 2 || curve.back() < 0.99 || (1 - curve[curve.size()-2] > step / 512.0 && curve.back() < coord(mapping.back()))) {
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curve.emplace_back(1.0);
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curve.emplace_back(coord(mapping.back()));
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}
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if (curve.size() < 4) {
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curve = { DCT_Linear }; // not enough points, fall back to linear
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} else {
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curve.insert(curve.begin(), DCT_Spline);
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}
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}
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} // namespace
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void RawImageSource::getAutoMatchedToneCurve(std::vector<double> &outCurve)
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{
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BENCHFUN
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if (settings->verbose) {
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std::cout << "performing histogram matching for " << getFileName() << " on the embedded thumbnail" << std::endl;
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}
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outCurve = { DCT_Linear };
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ProcParams neutral;
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std::unique_ptr<IImage8> target;
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{
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int tr = TR_NONE;
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int fw, fh;
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getFullSize(fw, fh, tr);
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int skip = 10;
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PreviewProps pp(0, 0, fw, fh, skip);
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ColorTemp currWB = getWB();
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std::unique_ptr<Imagefloat> image(new Imagefloat(int(fw / skip), int(fh / skip)));
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getImage(currWB, tr, image.get(), pp, neutral.toneCurve, neutral.raw);
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// this could probably be made faster -- ideally we would need to just
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// perform the transformation from camera space to the output space
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// (taking gamma into account), but I couldn't find anything
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// ready-made, so for now this will do. Remember the famous quote:
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// "premature optimization is the root of all evil" :-)
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convertColorSpace(image.get(), neutral.icm, currWB);
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ImProcFunctions ipf(&neutral);
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LabImage tmplab(image->getWidth(), image->getHeight());
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ipf.rgb2lab(*image, tmplab, neutral.icm.working);
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image.reset(ipf.lab2rgbOut(&tmplab, 0, 0, tmplab.W, tmplab.H, neutral.icm));
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target.reset(image->to8());
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if (settings->verbose) {
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std::cout << "histogram matching: generated neutral rendering" << std::endl;
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}
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}
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std::unique_ptr<IImage8> source;
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{
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RawMetaDataLocation rml;
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eSensorType sensor_type;
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int w, h;
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std::unique_ptr<Thumbnail> thumb(Thumbnail::loadQuickFromRaw(getFileName(), rml, sensor_type, w, h, 1, false, true));
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if (!thumb) {
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if (settings->verbose) {
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std::cout << "histogram matching: no thumbnail found, generating a neutral curve" << std::endl;
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}
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return;
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}
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source.reset(thumb->quickProcessImage(neutral, target->getHeight(), TI_Nearest));
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if (settings->verbose) {
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std::cout << "histogram matching: extracted embedded thumbnail" << std::endl;
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}
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}
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if (target->getWidth() != source->getWidth() || target->getHeight() != source->getHeight()) {
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Image8 *tmp = new Image8(source->getWidth(), source->getHeight());
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target->resizeImgTo(source->getWidth(), source->getHeight(), TI_Nearest, tmp);
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target.reset(tmp);
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}
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std::vector<int> scdf = getCdf(*source);
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std::vector<int> tcdf = getCdf(*target);
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std::vector<int> mapping;
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int j = 0;
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for (size_t i = 0; i < tcdf.size(); ++i) {
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j = findMatch(tcdf[i], scdf, j);
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mapping.push_back(j);
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}
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mappingToCurve(mapping, outCurve);
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if (settings->verbose) {
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std::cout << "histogram matching: generated curve with " << outCurve.size()/2 << " control points" << std::endl;
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}
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}
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} // namespace rtengine
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