| 1 | // Aseprite Render Library | 
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| 2 | // Copyright (c)      2020 Igara Studio S.A. | 
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| 3 | // Copyright (c) 2001-2015 David Capello | 
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| 4 | // | 
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| 5 | // This file is released under the terms of the MIT license. | 
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| 6 | // Read LICENSE.txt for more information. | 
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| 7 |  | 
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| 8 | #ifndef RENDER_COLOR_HISTOGRAM_H_INCLUDED | 
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| 9 | #define RENDER_COLOR_HISTOGRAM_H_INCLUDED | 
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| 10 | #pragma once | 
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| 11 |  | 
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| 12 | #include <limits> | 
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| 13 | #include <vector> | 
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| 14 |  | 
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| 15 | #include "doc/color.h" | 
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| 16 | #include "doc/image.h" | 
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| 17 | #include "doc/image_traits.h" | 
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| 18 | #include "doc/palette.h" | 
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| 19 |  | 
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| 20 | #include "render/median_cut.h" | 
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| 21 |  | 
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| 22 | namespace render { | 
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| 23 | using namespace doc; | 
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| 24 |  | 
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| 25 | template<int RBits, // Number of bits for each component in the histogram | 
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| 26 | int GBits, | 
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| 27 | int BBits, | 
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| 28 | int ABits> | 
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| 29 | class ColorHistogram { | 
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| 30 | public: | 
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| 31 | // Number of elements in histogram for each RGB component | 
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| 32 | enum { | 
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| 33 | RElements = 1 << RBits, | 
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| 34 | GElements = 1 << GBits, | 
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| 35 | BElements = 1 << BBits, | 
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| 36 | AElements = 1 << ABits | 
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| 37 | }; | 
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| 38 |  | 
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| 39 | ColorHistogram() | 
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| 40 | : m_histogram(RElements*GElements*BElements*AElements, 0) | 
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| 41 | , m_useHighPrecision(true) { | 
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| 42 | } | 
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| 43 |  | 
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| 44 | // Returns the number of points in the specified histogram | 
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| 45 | // entry. Each rgba-index is in the range of the histogram, e.g. | 
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| 46 | // r=[0,RElements), g=[0,GElements), etc. | 
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| 47 | std::size_t at(int r, int g, int b, int a) const { | 
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| 48 | return m_histogram[histogramIndex(r, g, b, a)]; | 
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| 49 | } | 
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| 50 |  | 
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| 51 | // Add the specified "color" in the histogram as many times as the | 
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| 52 | // specified value in "count". | 
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| 53 | void addSamples(doc::color_t color, std::size_t count = 1) { | 
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| 54 | int i = histogramIndex(color); | 
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| 55 |  | 
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| 56 | if (m_histogram[i] < std::numeric_limits<std::size_t>::max()-count) // Avoid overflow | 
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| 57 | m_histogram[i] += count; | 
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| 58 | else | 
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| 59 | m_histogram[i] = std::numeric_limits<std::size_t>::max(); | 
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| 60 |  | 
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| 61 | // Accurate colors are used only for less than 256 colors.  If the | 
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| 62 | // image has more than 256 colors the m_histogram is used | 
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| 63 | // instead. | 
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| 64 | if (m_useHighPrecision) { | 
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| 65 | std::vector<doc::color_t>::iterator it = | 
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| 66 | std::find(m_highPrecision.begin(), m_highPrecision.end(), color); | 
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| 67 |  | 
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| 68 | // The color is not in the high-precision table | 
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| 69 | if (it == m_highPrecision.end()) { | 
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| 70 | if (m_highPrecision.size() < 256) { | 
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| 71 | m_highPrecision.push_back(color); | 
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| 72 | } | 
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| 73 | else { | 
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| 74 | // In this case we reach the limit for the high-precision histogram. | 
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| 75 | m_useHighPrecision = false; | 
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| 76 | } | 
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| 77 | } | 
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| 78 | } | 
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| 79 | } | 
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| 80 |  | 
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| 81 | // Creates a set of entries for the given palette in the given range | 
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| 82 | // with the more important colors in the histogram. Returns the | 
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| 83 | // number of used entries in the palette (maybe the range [from,to] | 
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| 84 | // is more than necessary). | 
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| 85 | int createOptimizedPalette(Palette* palette) { | 
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| 86 | // Can we use the high-precision table? | 
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| 87 | if (m_useHighPrecision && int(m_highPrecision.size()) <= palette->size()) { | 
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| 88 | for (int i=0; i<(int)m_highPrecision.size(); ++i) | 
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| 89 | palette->setEntry(i, m_highPrecision[i]); | 
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| 90 |  | 
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| 91 | return m_highPrecision.size(); | 
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| 92 | } | 
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| 93 | // OK, we have to use the histogram and some algorithm (like | 
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| 94 | // median-cut) to quantize "optimal" colors. | 
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| 95 | else { | 
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| 96 | std::vector<doc::color_t> result; | 
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| 97 | median_cut(*this, palette->size(), result); | 
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| 98 |  | 
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| 99 | for (int i=0; i<(int)result.size(); ++i) | 
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| 100 | palette->setEntry(i, result[i]); | 
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| 101 |  | 
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| 102 | return result.size(); | 
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| 103 | } | 
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| 104 | } | 
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| 105 |  | 
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| 106 | bool isHighPrecision() { return m_useHighPrecision; } | 
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| 107 | int highPrecisionSize() { return m_highPrecision.size(); } | 
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| 108 |  | 
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| 109 | private: | 
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| 110 | // Converts input color in a index for the histogram. It reduces | 
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| 111 | // each 8-bit component to the resolution given in the template | 
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| 112 | // parameters. | 
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| 113 | std::size_t histogramIndex(doc::color_t color) const { | 
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| 114 | return histogramIndex((rgba_getr(color) >> (8 - RBits)), | 
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| 115 | (rgba_getg(color) >> (8 - GBits)), | 
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| 116 | (rgba_getb(color) >> (8 - BBits)), | 
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| 117 | (rgba_geta(color) >> (8 - ABits))); | 
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| 118 | } | 
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| 119 |  | 
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| 120 | std::size_t histogramIndex(int r, int g, int b, int a) const { | 
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| 121 | return | 
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| 122 | r | 
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| 123 | | (g << RBits) | 
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| 124 | | (b << (RBits+GBits)) | 
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| 125 | | (a << (RBits+GBits+BBits)); | 
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| 126 | } | 
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| 127 |  | 
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| 128 | // 3D histogram (the index in the histogram is calculated through histogramIndex() function). | 
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| 129 | std::vector<std::size_t> m_histogram; | 
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| 130 |  | 
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| 131 | // High precision histogram to create an accurate palette if RGB | 
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| 132 | // source images contains less than 256 colors. | 
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| 133 | std::vector<doc::color_t> m_highPrecision; | 
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| 134 |  | 
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| 135 | // True if we can use m_highPrecision still (it means that the | 
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| 136 | // number of different samples is less than 256 colors still). | 
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| 137 | bool m_useHighPrecision; | 
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| 138 | }; | 
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| 139 |  | 
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| 140 | } // namespace render | 
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| 141 |  | 
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| 142 | #endif | 
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| 143 |  | 
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