cm: Add private copy of Palette (a68e4c67) · Commits · e / os / android_frameworks_base

core/java/com/android/internal/util/cm/palette/ColorCutQuantizer.java

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		/*
		* Copyright 2014 The Android Open Source Project
		*
		* Licensed under the Apache License, Version 2.0 (the "License");
		* you may not use this file except in compliance with the License.
		* You may obtain a copy of the License at
		*
		* http://www.apache.org/licenses/LICENSE-2.0
		*
		* Unless required by applicable law or agreed to in writing, software
		* distributed under the License is distributed on an "AS IS" BASIS,
		* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
		* See the License for the specific language governing permissions and
		* limitations under the License.
		*/

		package com.android.internal.util.cm.palette;

		import android.graphics.Color;
		import com.android.internal.util.cm.palette.Palette.Swatch;
		import android.util.TimingLogger;

		import java.util.ArrayList;
		import java.util.Arrays;
		import java.util.Collection;
		import java.util.Comparator;
		import java.util.List;
		import java.util.PriorityQueue;

		/**
		* An color quantizer based on the Median-cut algorithm, but optimized for picking out distinct
		* colors rather than representation colors.
		*
		* The color space is represented as a 3-dimensional cube with each dimension being an RGB
		* component. The cube is then repeatedly divided until we have reduced the color space to the
		* requested number of colors. An average color is then generated from each cube.
		*
		* What makes this different to median-cut is that median-cut divided cubes so that all of the cubes
		* have roughly the same population, where this quantizer divides boxes based on their color volume.
		* This means that the color space is divided into distinct colors, rather than representative
		* colors.
		*
		* @hide
		*/
		final class ColorCutQuantizer {

		private static final String LOG_TAG = "ColorCutQuantizer";
		private static final boolean LOG_TIMINGS = false;

		private static final int COMPONENT_RED = -3;
		private static final int COMPONENT_GREEN = -2;
		private static final int COMPONENT_BLUE = -1;

		private static final int QUANTIZE_WORD_WIDTH = 5;
		private static final int QUANTIZE_WORD_MASK = (1 << QUANTIZE_WORD_WIDTH) - 1;

		final int[] mColors;
		final int[] mHistogram;
		final List<Swatch> mQuantizedColors;
		final TimingLogger mTimingLogger;
		final Palette.Filter[] mFilters;

		private final float[] mTempHsl = new float[3];

		/**
		* Constructor.
		*
		* @param pixels histogram representing an image's pixel data
		* @param maxColors The maximum number of colors that should be in the result palette.
		* @param filters Set of filters to use in the quantization stage
		*/
		ColorCutQuantizer(final int[] pixels, final int maxColors, final Palette.Filter[] filters) {
		mTimingLogger = LOG_TIMINGS ? new TimingLogger(LOG_TAG, "Creation") : null;
		mFilters = filters;

		final int[] hist = mHistogram = new int[1 << (QUANTIZE_WORD_WIDTH * 3)];
		for (int i = 0; i < pixels.length; i++) {
		final int quantizedColor = quantizeFromRgb888(pixels[i]);
		// Now update the pixel value to the quantized value
		pixels[i] = quantizedColor;
		// And update the histogram
		hist[quantizedColor]++;
		}

		if (LOG_TIMINGS) {
		mTimingLogger.addSplit("Histogram created");
		}

		// Now let's count the number of distinct colors
		int distinctColorCount = 0;
		for (int color = 0; color < hist.length; color++) {
		if (hist[color] > 0 && shouldIgnoreColor(color)) {
		// If we should ignore the color, set the population to 0
		hist[color] = 0;
		}
		if (hist[color] > 0) {
		// If the color has population, increase the distinct color count
		distinctColorCount++;
		}
		}

		if (LOG_TIMINGS) {
		mTimingLogger.addSplit("Filtered colors and distinct colors counted");
		}

		// Now lets go through create an array consisting of only distinct colors
		final int[] colors = mColors = new int[distinctColorCount];
		int distinctColorIndex = 0;
		for (int color = 0; color < hist.length; color++) {
		if (hist[color] > 0) {
		colors[distinctColorIndex++] = color;
		}
		}

		if (LOG_TIMINGS) {
		mTimingLogger.addSplit("Distinct colors copied into array");
		}

		if (distinctColorCount <= maxColors) {
		// The image has fewer colors than the maximum requested, so just return the colors
		mQuantizedColors = new ArrayList<>();
		for (int color : colors) {
		mQuantizedColors.add(new Swatch(approximateToRgb888(color), hist[color]));
		}

		if (LOG_TIMINGS) {
		mTimingLogger.addSplit("Too few colors present. Copied to Swatches");
		mTimingLogger.dumpToLog();
		}
		} else {
		// We need use quantization to reduce the number of colors
		mQuantizedColors = quantizePixels(maxColors);

		if (LOG_TIMINGS) {
		mTimingLogger.addSplit("Quantized colors computed");
		mTimingLogger.dumpToLog();
		}
		}
		}

		/**
		* @return the list of quantized colors
		*/
		List<Swatch> getQuantizedColors() {
		return mQuantizedColors;
		}

		private List<Swatch> quantizePixels(int maxColors) {
		// Create the priority queue which is sorted by volume descending. This means we always
		// split the largest box in the queue
		final PriorityQueue<Vbox> pq = new PriorityQueue<>(maxColors, VBOX_COMPARATOR_VOLUME);

		// To start, offer a box which contains all of the colors
		pq.offer(new Vbox(0, mColors.length - 1));

		// Now go through the boxes, splitting them until we have reached maxColors or there are no
		// more boxes to split
		splitBoxes(pq, maxColors);

		// Finally, return the average colors of the color boxes
		return generateAverageColors(pq);
		}

		/**
		* Iterate through the {@link java.util.Queue}, popping
		* {@link ColorCutQuantizer.Vbox} objects from the queue
		* and splitting them. Once split, the new box and the remaining box are offered back to the
		* queue.
		*
		* @param queue {@link java.util.PriorityQueue} to poll for boxes
		* @param maxSize Maximum amount of boxes to split
		*/
		private void splitBoxes(final PriorityQueue<Vbox> queue, final int maxSize) {
		while (queue.size() < maxSize) {
		final Vbox vbox = queue.poll();

		if (vbox != null && vbox.canSplit()) {
		// First split the box, and offer the result
		queue.offer(vbox.splitBox());

		if (LOG_TIMINGS) {
		mTimingLogger.addSplit("Box split");
		}
		// Then offer the box back
		queue.offer(vbox);
		} else {
		if (LOG_TIMINGS) {
		mTimingLogger.addSplit("All boxes split");
		}
		// If we get here then there are no more boxes to split, so return
		return;
		}
		}
		}

		private List<Swatch> generateAverageColors(Collection<Vbox> vboxes) {
		ArrayList<Swatch> colors = new ArrayList<>(vboxes.size());
		for (Vbox vbox : vboxes) {
		Swatch swatch = vbox.getAverageColor();
		if (!shouldIgnoreColor(swatch)) {
		// As we're averaging a color box, we can still get colors which we do not want, so
		// we check again here
		colors.add(swatch);
		}
		}
		return colors;
		}

		/**
		* Represents a tightly fitting box around a color space.
		*/
		private class Vbox {
		// lower and upper index are inclusive
		private int mLowerIndex;
		private int mUpperIndex;
		// Population of colors within this box
		private int mPopulation;

		private int mMinRed, mMaxRed;
		private int mMinGreen, mMaxGreen;
		private int mMinBlue, mMaxBlue;

		Vbox(int lowerIndex, int upperIndex) {
		mLowerIndex = lowerIndex;
		mUpperIndex = upperIndex;
		fitBox();
		}

		final int getVolume() {
		return (mMaxRed - mMinRed + 1) * (mMaxGreen - mMinGreen + 1) *
		(mMaxBlue - mMinBlue + 1);
		}

		final boolean canSplit() {
		return getColorCount() > 1;
		}

		final int getColorCount() {
		return 1 + mUpperIndex - mLowerIndex;
		}

		/**
		* Recomputes the boundaries of this box to tightly fit the colors within the box.
		*/
		final void fitBox() {
		final int[] colors = mColors;
		final int[] hist = mHistogram;

		// Reset the min and max to opposite values
		int minRed, minGreen, minBlue;
		minRed = minGreen = minBlue = Integer.MAX_VALUE;
		int maxRed, maxGreen, maxBlue;
		maxRed = maxGreen = maxBlue = Integer.MIN_VALUE;
		int count = 0;

		for (int i = mLowerIndex; i <= mUpperIndex; i++) {
		final int color = colors[i];
		count += hist[color];

		final int r = quantizedRed(color);
		final int g = quantizedGreen(color);
		final int b = quantizedBlue(color);
		if (r > maxRed) {
		maxRed = r;
		}
		if (r < minRed) {
		minRed = r;
		}
		if (g > maxGreen) {
		maxGreen = g;
		}
		if (g < minGreen) {
		minGreen = g;
		}
		if (b > maxBlue) {
		maxBlue = b;
		}
		if (b < minBlue) {
		minBlue = b;
		}
		}

		mMinRed = minRed;
		mMaxRed = maxRed;
		mMinGreen = minGreen;
		mMaxGreen = maxGreen;
		mMinBlue = minBlue;
		mMaxBlue = maxBlue;
		mPopulation = count;
		}

		/**
		* Split this color box at the mid-point along it's longest dimension
		*
		* @return the new ColorBox
		*/
		final Vbox splitBox() {
		if (!canSplit()) {
		throw new IllegalStateException("Can not split a box with only 1 color");
		}

		// find median along the longest dimension
		final int splitPoint = findSplitPoint();

		Vbox newBox = new Vbox(splitPoint + 1, mUpperIndex);

		// Now change this box's upperIndex and recompute the color boundaries
		mUpperIndex = splitPoint;
		fitBox();

		return newBox;
		}

		/**
		* @return the dimension which this box is largest in
		*/
		final int getLongestColorDimension() {
		final int redLength = mMaxRed - mMinRed;
		final int greenLength = mMaxGreen - mMinGreen;
		final int blueLength = mMaxBlue - mMinBlue;

		if (redLength >= greenLength && redLength >= blueLength) {
		return COMPONENT_RED;
		} else if (greenLength >= redLength && greenLength >= blueLength) {
		return COMPONENT_GREEN;
		} else {
		return COMPONENT_BLUE;
		}
		}

		/**
		* Finds the point within this box's lowerIndex and upperIndex index of where to split.
		*
		* This is calculated by finding the longest color dimension, and then sorting the
		* sub-array based on that dimension value in each color. The colors are then iterated over
		* until a color is found with at least the midpoint of the whole box's dimension midpoint.
		*
		* @return the index of the colors array to split from
		*/
		final int findSplitPoint() {
		final int longestDimension = getLongestColorDimension();
		final int[] colors = mColors;
		final int[] hist = mHistogram;

		// We need to sort the colors in this box based on the longest color dimension.
		// As we can't use a Comparator to define the sort logic, we modify each color so that
		// it's most significant is the desired dimension
		modifySignificantOctet(colors, longestDimension, mLowerIndex, mUpperIndex);

		// Now sort... Arrays.sort uses a exclusive toIndex so we need to add 1
		Arrays.sort(colors, mLowerIndex, mUpperIndex + 1);

		// Now revert all of the colors so that they are packed as RGB again
		modifySignificantOctet(colors, longestDimension, mLowerIndex, mUpperIndex);

		final int midPoint = mPopulation / 2;
		for (int i = mLowerIndex, count = 0; i <= mUpperIndex; i++) {
		count += hist[colors[i]];
		if (count >= midPoint) {
		return i;
		}
		}

		return mLowerIndex;
		}

		/**
		* @return the average color of this box.
		*/
		final Swatch getAverageColor() {
		final int[] colors = mColors;
		final int[] hist = mHistogram;
		int redSum = 0;
		int greenSum = 0;
		int blueSum = 0;
		int totalPopulation = 0;

		for (int i = mLowerIndex; i <= mUpperIndex; i++) {
		final int color = colors[i];
		final int colorPopulation = hist[color];

		totalPopulation += colorPopulation;
		redSum += colorPopulation * quantizedRed(color);
		greenSum += colorPopulation * quantizedGreen(color);
		blueSum += colorPopulation * quantizedBlue(color);
		}

		final int redMean = Math.round(redSum / (float) totalPopulation);
		final int greenMean = Math.round(greenSum / (float) totalPopulation);
		final int blueMean = Math.round(blueSum / (float) totalPopulation);

		return new Swatch(approximateToRgb888(redMean, greenMean, blueMean), totalPopulation);
		}
		}

		/**
		* Modify the significant octet in a packed color int. Allows sorting based on the value of a
		* single color component. This relies on all components being the same word size.
		*
		* @see Vbox#findSplitPoint()
		*/
		private static void modifySignificantOctet(final int[] a, final int dimension,
		final int lower, final int upper) {
		switch (dimension) {
		case COMPONENT_RED:
		// Already in RGB, no need to do anything
		break;
		case COMPONENT_GREEN:
		// We need to do a RGB to GRB swap, or vice-versa
		for (int i = lower; i <= upper; i++) {
		final int color = a[i];
		a[i] = quantizedGreen(color) << (QUANTIZE_WORD_WIDTH + QUANTIZE_WORD_WIDTH)
		\| quantizedRed(color) << QUANTIZE_WORD_WIDTH
		\| quantizedBlue(color);
		}
		break;
		case COMPONENT_BLUE:
		// We need to do a RGB to BGR swap, or vice-versa
		for (int i = lower; i <= upper; i++) {
		final int color = a[i];
		a[i] = quantizedBlue(color) << (QUANTIZE_WORD_WIDTH + QUANTIZE_WORD_WIDTH)
		\| quantizedGreen(color) << QUANTIZE_WORD_WIDTH
		\| quantizedRed(color);
		}
		break;
		}
		}

		private boolean shouldIgnoreColor(int color565) {
		final int rgb = approximateToRgb888(color565);
		ColorUtils.colorToHSL(rgb, mTempHsl);
		return shouldIgnoreColor(rgb, mTempHsl);
		}

		private boolean shouldIgnoreColor(Swatch color) {
		return shouldIgnoreColor(color.getRgb(), color.getHsl());
		}

		private boolean shouldIgnoreColor(int rgb, float[] hsl) {
		if (mFilters != null && mFilters.length > 0) {
		for (int i = 0, count = mFilters.length; i < count; i++) {
		if (!mFilters[i].isAllowed(rgb, hsl)) {
		return true;
		}
		}
		}
		return false;
		}

		/**
		* Comparator which sorts {@link Vbox} instances based on their volume, in descending order
		*/
		private static final Comparator<Vbox> VBOX_COMPARATOR_VOLUME = new Comparator<Vbox>() {
		@Override
		public int compare(Vbox lhs, Vbox rhs) {
		return rhs.getVolume() - lhs.getVolume();
		}
		};

		/**
		* Quantized a RGB888 value to have a word width of {@value #QUANTIZE_WORD_WIDTH}.
		*/
		private static int quantizeFromRgb888(int color) {
		int r = modifyWordWidth(Color.red(color), 8, QUANTIZE_WORD_WIDTH);
		int g = modifyWordWidth(Color.green(color), 8, QUANTIZE_WORD_WIDTH);
		int b = modifyWordWidth(Color.blue(color), 8, QUANTIZE_WORD_WIDTH);
		return r << (QUANTIZE_WORD_WIDTH + QUANTIZE_WORD_WIDTH) \| g << QUANTIZE_WORD_WIDTH \| b;
		}

		/**
		* Quantized RGB888 values to have a word width of {@value #QUANTIZE_WORD_WIDTH}.
		*/
		private static int approximateToRgb888(int r, int g, int b) {
		return Color.rgb(modifyWordWidth(r, QUANTIZE_WORD_WIDTH, 8),
		modifyWordWidth(g, QUANTIZE_WORD_WIDTH, 8),
		modifyWordWidth(b, QUANTIZE_WORD_WIDTH, 8));
		}

		private static int approximateToRgb888(int color) {
		return approximateToRgb888(quantizedRed(color), quantizedGreen(color), quantizedBlue(color));
		}

		/**
		* @return red component of the quantized color
		*/
		private static int quantizedRed(int color) {
		return (color >> (QUANTIZE_WORD_WIDTH + QUANTIZE_WORD_WIDTH)) & QUANTIZE_WORD_MASK;
		}

		/**
		* @return green component of a quantized color
		*/
		private static int quantizedGreen(int color) {
		return (color >> QUANTIZE_WORD_WIDTH) & QUANTIZE_WORD_MASK;
		}

		/**
		* @return blue component of a quantized color
		*/
		private static int quantizedBlue(int color) {
		return color & QUANTIZE_WORD_MASK;
		}

		private static int modifyWordWidth(int value, int currentWidth, int targetWidth) {
		final int newValue;
		if (targetWidth > currentWidth) {
		// If we're approximating up in word width, we'll shift up
		newValue = value << (targetWidth - currentWidth);
		} else {
		// Else, we will just shift and keep the MSB
		newValue = value >> (currentWidth - targetWidth);
		}
		return newValue & ((1 << targetWidth) - 1);
		}

		}

core/java/com/android/internal/util/cm/palette/ColorUtils.java

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core/java/com/android/internal/util/cm/palette/DefaultGenerator.java

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core/java/com/android/internal/util/cm/palette/Palette.java

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