commonMain.quantize.QuantizerCelebi.kt Maven / Gradle / Ivy

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Port of the Material You color generation algorithm for Kotlin

There is a newer version: 0.2.0

/*
 * Copyright (c) 2024, Google LLC, OpenSavvy and contributors.
 *
 * 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 opensavvy.material3.colors.quantize

/**
 * An image quantizer that improves on the quality of a standard K-Means algorithm by setting the
 * K-Means initial state to the output of a Wu quantizer, instead of random centroids. Improves on
 * speed by several optimizations, as implemented in Wsmeans, or Weighted Square Means, K-Means with
 * those optimizations.
 *
 *
 * This algorithm was designed by M. Emre Celebi, and was found in their 2011 paper, Improving
 * the Performance of K-Means for Color Quantization. https://arxiv.org/abs/1101.0395
 */
object QuantizerCelebi {
	/**
	 * Reduce the number of colors needed to represented the input, minimizing the difference between
	 * the original image and the recolored image.
	 *
	 * @param pixels Colors in ARGB format.
	 * @param maxColors The number of colors to divide the image into. A lower number of colors may be
	 * returned.
	 * @return Map with keys of colors in ARGB format, and values of number of pixels in the original
	 * image that correspond to the color in the quantized image.
	 */
	fun quantize(pixels: IntArray, maxColors: Int): Map {
		val wu: QuantizerWu = QuantizerWu()
		val wuResult: QuantizerResult = wu.quantize(pixels, maxColors)

		val wuClustersAsObjects: Set = wuResult.colorToCount.keys
		var index = 0
		val wuClusters = IntArray(wuClustersAsObjects.size)
		for (argb in wuClustersAsObjects) {
			wuClusters[index++] = argb
		}

		return QuantizerWsmeans.quantize(pixels, wuClusters, maxColors)
	}
}