lidapeng
4 years ago
parent
824874c078
commit
f399fac619
@ -0,0 +1,35 @@
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package org.wlld.imageRecognition.modelEntity;
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/**
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* @param
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* @DATA
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* @Author LiDaPeng
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* @Description 映射体
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*/
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public class MappingBody {
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private double[] feature;//特征
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private double mappingNub;//映射好的值
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public MappingBody(double[] mapping, double[] feature) {
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this.feature = feature;
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double sigma = 0;
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for (int i = 0; i < mapping.length; i++) {
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sigma = sigma + Math.pow(mapping[i], 2);
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}
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sigma = Math.sqrt(sigma);//映射维度的莫
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double s = 0;
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for (int j = 0; j < feature.length; j++) {
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s = s + feature[j] * mapping[j];
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}
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mappingNub = s / sigma;
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}
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public double[] getFeature() {
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return feature;
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}
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public double getMappingNub() {
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return mappingNub;
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}
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}
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@ -0,0 +1,72 @@
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package org.wlld.imageRecognition.segmentation;
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import org.wlld.MatrixTools.Matrix;
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import org.wlld.i.PsoFunction;
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import org.wlld.imageRecognition.ThreeChannelMatrix;
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import org.wlld.tools.Frequency;
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import java.util.HashMap;
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import java.util.Map;
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/**
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* @param
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* @DATA
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* @Author LiDaPeng
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* @Description
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*/
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public class ColorFunction extends Frequency implements PsoFunction {
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private Matrix matrixR;
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private Matrix matrixG;
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private Matrix matrixB;
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private Map<Integer, double[]> pixels = new HashMap<>();
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public ColorFunction(ThreeChannelMatrix threeChannelMatrix) {
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matrixR = threeChannelMatrix.getMatrixR();
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matrixG = threeChannelMatrix.getMatrixG();
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matrixB = threeChannelMatrix.getMatrixB();
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}
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@Override
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public double getResult(double[] parameter, int id) throws Exception {
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int x = (int) parameter[0];
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int y = (int) parameter[1];
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double[] rgb = new double[]{matrixR.getNumber(x, y) / 255, matrixG.getNumber(x, y) / 255,
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matrixB.getNumber(x, y) / 255};
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pixels.put(id, rgb);
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//计算当前方差
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return getDist();
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//return getRegression();
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}
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private double getRegression() throws Exception {
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RgbRegression rgbRegression = new RgbRegression(pixels.size());
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for (Map.Entry<Integer, double[]> entry : pixels.entrySet()) {
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double[] rgb = entry.getValue();
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rgbRegression.insertRGB(rgb);
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}
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double sigma = 0;
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if (rgbRegression.regression()) {
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for (Map.Entry<Integer, double[]> entry : pixels.entrySet()) {
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double[] rgb = entry.getValue();
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sigma = sigma + rgbRegression.getDisError(rgb);
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}
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sigma = sigma / pixels.size();
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}
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return sigma;
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}
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private double getDist() {//计算当前均方误差
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double[] r = new double[pixels.size()];
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double[] g = new double[pixels.size()];
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double[] b = new double[pixels.size()];
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for (Map.Entry<Integer, double[]> entry : pixels.entrySet()) {
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double[] rgb = entry.getValue();
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int key = entry.getKey();
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r[key] = rgb[0];
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g[key] = rgb[1];
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b[key] = rgb[2];
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}
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return dc(r) + dc(g) + dc(b);
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}
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}
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@ -0,0 +1,41 @@
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package org.wlld.imageRecognition.segmentation;
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import org.wlld.i.PsoFunction;
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import org.wlld.tools.Frequency;
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import java.util.List;
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/**
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* @param
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* @DATA
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* @Author LiDaPeng
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* @Description 维度映射
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*/
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public class DimensionMapping extends Frequency implements PsoFunction {
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private List<double[]> features;
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private int size;
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public DimensionMapping(List<double[]> features) {
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this.features = features;
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size = features.size();
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}
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@Override
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public double getResult(double[] parameter, int id) throws Exception {
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double sigma = 0;
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for (int i = 0; i < parameter.length; i++) {
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sigma = sigma + Math.pow(parameter[i], 2);
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}
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sigma = Math.sqrt(sigma);
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double[] mapping = new double[size];//在新维度的映射集合
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for (int i = 0; i < size; i++) {
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double[] feature = features.get(i);
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double s = 0;
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for (int j = 0; j < feature.length; j++) {
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s = s + feature[j] * parameter[j];
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}
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mapping[i] = s / sigma;
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}
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return variance(mapping);
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}
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}
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