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增加粒子群
This commit is contained in:
lidapeng
parent
fd0353b3a3
commit
824874c078
@ -425,6 +425,7 @@ public class Matrix {
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if (this.x >= x && this.y >= y) {
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return matrix[x][y];
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} else {
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//System.out.println("x==" + x + ",y==" + y);
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throw new Exception("matrix length too little");
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}
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}
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7
src/main/java/org/wlld/i/PsoFunction.java
Normal file
7
src/main/java/org/wlld/i/PsoFunction.java
Normal file
@ -0,0 +1,7 @@
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package org.wlld.i;
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public interface PsoFunction {//粒子群回调函数
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//根据参数返回函数值
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double getResult(double[] parameter,int id) throws Exception;
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}
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@ -235,24 +235,24 @@ public class Convolution extends Frequency {
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rgb[twoNub + index] = sonB.getNumber(t, k) / 255;
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}
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}
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//900 200
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double dispersed = variance(h);
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if (dispersed < 900 && dispersed > 200) {
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for (int m = 0; m < nub; m++) {
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double[] color = new double[]{rgb[m], rgb[m + nub], rgb[m + twoNub]};
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meanClustering.setColor(color);
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}
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// meanClustering.setColor(rgb);
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}
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}
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}
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List<double[]> list = meanClustering.start(true);//开始聚类
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if (tag == 0) {//识别
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templeConfig.getFood().getkNerveManger().look(list);
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} else {//训练
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templeConfig.getFood().getkNerveManger().setFeature(tag, list);
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}
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//List<double[]> list = meanClustering.start(true);//开始聚类
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meanClustering.start(true);
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// if (tag == 0) {//识别
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// templeConfig.getFood().getkNerveManger().look(list);
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// } else {//训练
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// templeConfig.getFood().getkNerveManger().setFeature(tag, list);
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// }
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List<RGBNorm> rgbNorms = meanClustering.getMatrices();
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Collections.sort(rgbNorms, rgbSort);
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List<Double> features = new ArrayList<>();
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for (int i = 0; i < sqNub; i++) {
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double[] rgb = rgbNorms.get(i).getRgb();
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@ -84,12 +84,43 @@ public class MeanClustering {
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}
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}
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private double[] getListAvg(List<double[]> list) {
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int len = list.get(0).length;
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double[] sigma = new double[len];
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for (double[] rgb : list) {
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for (int i = 0; i < len; i++) {
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sigma[i] = sigma[i] + rgb[i];
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}
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}
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int size = list.size();
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for (int i = 0; i < len; i++) {
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sigma[i] = sigma[i] / size;
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}
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return sigma;
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}
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private List<double[]> listK(List<double[]> listOne, int nub) {
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int size = listOne.size();
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int oneSize = size / nub;//几份取一份平均值
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//System.out.println("oneSize==" + oneSize);
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List<double[]> allList = new ArrayList<>();
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for (int i = 0; i <= size - oneSize; i += oneSize) {
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double[] avg = getListAvg(listOne.subList(i, i + oneSize));
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allList.add(avg);
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}
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return allList;
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}
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private List<double[]> startBp() {
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int times = 2000;
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int index = 0;
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List<double[]> features = new ArrayList<>();
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List<List<double[]>> lists = new ArrayList<>();
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for (int j = 0; j < matrices.size(); j++) {
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List<double[]> list = matrices.get(j).getRgbs().subList(0, times);
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List<double[]> listOne = matrices.get(j).getRgbs();
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// List<double[]> list = listK(listOne, times);
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//System.out.println(listOne.size());
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List<double[]> list = listOne.subList(index, times + index);
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lists.add(list);
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}
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for (int j = 0; j < times; j++) {
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@ -137,7 +168,7 @@ public class MeanClustering {
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return features;
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}
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public List<double[]> start(boolean isRegression) throws Exception {//开始聚类
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public void start(boolean isRegression) throws Exception {//开始聚类
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if (matrixList.size() > 1) {
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Random random = new Random();
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for (int i = 0; i < speciesQuantity; i++) {//初始化均值向量
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@ -149,10 +180,10 @@ public class MeanClustering {
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}
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//进行两者的比较
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boolean isNext;
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for (int i = 0; i < 40; i++) {
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for (int i = 0; i < 50; i++) {
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averageMatrix();
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isNext = isNext();
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if (isNext && i < 39) {
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if (isNext && i < 49) {
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clear();
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} else {
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break;
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@ -160,15 +191,10 @@ public class MeanClustering {
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}
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RGBSort rgbSort = new RGBSort();
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Collections.sort(matrices, rgbSort);
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for (RGBNorm rgbNorm : matrices) {
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rgbNorm.finish();
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}
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// if (isRegression) {
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// return startRegression();
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// } else {
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// return null;
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// for (RGBNorm rgbNorm : matrices) {
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// rgbNorm.finish();
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// }
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return startBp();
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// return startBp();
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} else {
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throw new Exception("matrixList number less than 2");
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}
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@ -121,9 +121,9 @@ public class RGBNorm {
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o2Norm = o2Norm + Math.pow(o2[i], 2);
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}
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if (o1Norm > o2Norm) {
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return -1;
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} else if (o1Norm < o2Norm) {
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return 1;
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} else if (o1Norm < o2Norm) {
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return -1;
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}
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return 0;
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}
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@ -101,7 +101,7 @@ public class Knn {//KNN分类器
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compare(dists, types, dist, type);
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}
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}
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//System.out.println(Arrays.toString(types));
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System.out.println(Arrays.toString(types));
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Map<Integer, Integer> map = new HashMap<>();
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for (int i = 0; i < nub; i++) {
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int type = types[i];
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@ -11,10 +11,10 @@ import org.wlld.i.OutBack;
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*/
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public class RgbBack implements OutBack {
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private int id = 0;
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private double out = 0;
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private double out = -2;
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public void clear() {
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out = 0;
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out = -2;
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id = 0;
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}
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@ -33,20 +33,13 @@ public class KNerveManger {
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this.times = times;
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nerveManager = new NerveManager(sensoryNerveNub, 24, speciesNub,
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1, new Tanh(),//0.008 l1 0.02
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false, false, 0.008, RZ.L1, 0.01);
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false, false, 0.008, RZ.L1, 0.02);
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nerveManager.init(true, false, true, true);
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}
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private Map<Integer, Double> createTag(int tag) {//创建一个标注
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Map<Integer, Double> tagging = new HashMap<>();
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Set<Integer> set = featureMap.keySet();
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for (int key : set) {
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double value = 0.0;
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if (key == tag) {
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value = 1.0;
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}
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tagging.put(key, value);
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}
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tagging.put(tag, 1.0);
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return tagging;
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}
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@ -78,22 +71,24 @@ public class KNerveManger {
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}
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public void startStudy() throws Exception {
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for (int i = 0; i < times; i++) {
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for (Map.Entry<Integer, List<double[]>> entry : featureMap.entrySet()) {
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int type = entry.getKey();
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System.out.println("=============================" + type);
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Map<Integer, Double> tag = createTag(type);//标注
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double[] feature = entry.getValue().get(i);//数据
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post(feature, tag, true);
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for (int j = 0; j < 2; j++) {
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for (int i = 0; i < times; i++) {
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for (Map.Entry<Integer, List<double[]>> entry : featureMap.entrySet()) {
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int type = entry.getKey();
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System.out.println("=============================" + type);
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Map<Integer, Double> tag = createTag(type);//标注
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double[] feature = entry.getValue().get(i);//数据
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post(feature, tag, true);
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}
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}
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}
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// for (Map.Entry<Integer, List<double[]>> entry : featureMap.entrySet()) {
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// int type = entry.getKey();
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// System.out.println("=============================" + type);
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// List<double[]> list = entry.getValue();
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// look(list);
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// }
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for (Map.Entry<Integer, List<double[]>> entry : featureMap.entrySet()) {
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int type = entry.getKey();
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System.out.println("=============================" + type);
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List<double[]> list = entry.getValue();
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look(list);
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}
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}
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private void post(double[] data, Map<Integer, Double> tagging, boolean isStudy) throws Exception {
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@ -58,7 +58,7 @@ public class OutNerve extends Nerve {
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if (E.containsKey(getId())) {
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this.E = E.get(getId());
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} else {
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this.E = 0;
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this.E = -1;
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}
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if (isShowLog) {
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System.out.println("E==" + this.E + ",out==" + out + ",nerveId==" + getId());
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201
src/main/java/org/wlld/pso/PSO.java
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201
src/main/java/org/wlld/pso/PSO.java
Normal file
@ -0,0 +1,201 @@
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package org.wlld.pso;
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import org.wlld.i.PsoFunction;
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import javax.imageio.ImageIO;
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import java.awt.*;
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import java.awt.geom.Rectangle2D;
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import java.awt.image.BufferedImage;
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import java.io.File;
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import java.io.FileInputStream;
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import java.io.FileOutputStream;
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import java.util.ArrayList;
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import java.util.List;
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import java.util.Random;
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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 粒子群
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*/
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public class PSO {
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private double globalValue = -1;//当前全局最优值
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private int times;//迭代次数
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private List<Particle> allPar = new ArrayList<>();//全部粒子集合
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private PsoFunction psoFunction;//粒子群执行函数
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private double inertialFactor = 0.5;//惯性因子
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private double selfStudyFactor = 2;//个体学习因子
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private double socialStudyFactor = 2;//社会学习因子
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private boolean isMax;//取最大值还是最小值
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private double[] allBest;//全局最佳位置
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private Random random = new Random();
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private int[] minBorder, maxBorder;
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private double maxSpeed;
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public PSO(int dimensionNub, int[] minBorder, int[] maxBorder,
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int times, int particleNub, PsoFunction psoFunction,
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double inertialFactor, double selfStudyFactor, double socialStudyFactor
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, boolean isMax, double maxSpeed) {
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this.times = times;
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this.psoFunction = psoFunction;
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this.isMax = isMax;
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allBest = new double[dimensionNub];
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this.minBorder = minBorder;
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this.maxBorder = maxBorder;
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this.maxSpeed = maxSpeed;
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if (inertialFactor > 0) {
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this.inertialFactor = inertialFactor;
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}
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if (selfStudyFactor >= 0 && selfStudyFactor <= 4) {
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this.selfStudyFactor = selfStudyFactor;
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}
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if (socialStudyFactor >= 0 && socialStudyFactor <= 4) {
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this.socialStudyFactor = socialStudyFactor;
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}
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for (int i = 0; i < particleNub; i++) {//初始化生成粒子群
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Particle particle = new Particle(dimensionNub);
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allPar.add(particle);
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}
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}
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public void setAllPar(List<Particle> allPar) {//外置粒子群注入
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this.allPar = allPar;
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}
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public void start(int fatherX, int fatherY) throws Exception {//开始进行迭代
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int size = allPar.size();
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for (int i = 0; i < times; i++) {
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for (int j = 0; j < size; j++) {
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move(allPar.get(j), j);
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}
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}
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//粒子群移动结束
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draw("/Users/lidapeng/Desktop/test/testOne/e2.jpg", fatherX, fatherY);
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}
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private void draw(String path, int fatherX, int fatherY) throws Exception {
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File file = new File(path);
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FileInputStream fileInputStream = new FileInputStream(file);
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BufferedImage image2 = ImageIO.read(fileInputStream);
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int width = image2.getWidth();
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int height = image2.getHeight();
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BufferedImage bi = new BufferedImage(width, height, BufferedImage.TYPE_INT_RGB);
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Graphics2D g2 = (Graphics2D) bi.getGraphics();
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g2.setColor(Color.CYAN);
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g2.drawImage(image2, 0, 0, width, height, null);
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int size = allPar.size();
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for (int j = 0; j < size; j++) {//输出
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Particle particle = allPar.get(j);
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double[] parameter = particle.getParameter();
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int x = (int) (fatherX + parameter[0]);
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int y = (int) (fatherY + parameter[1]);
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Rectangle2D rect = new Rectangle2D.Double(y, x, 1, 1);//声明并创建矩形对象，矩形的左上角是(20，30)，宽是300，高是40
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g2.draw(rect);
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}
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String savePath = "/Users/lidapeng/Desktop/test/testTwo/a.jpg";
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ImageIO.write(bi, "JPEG", new FileOutputStream(savePath));
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}
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private void move(Particle particle, int id) throws Exception {//粒子群开始移动
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double[] parameter = particle.getParameter();//当前粒子的位置
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BestData[] bestData = particle.bestDataArray;//该粒子的信息
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double value = psoFunction.getResult(parameter, id);
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double selfValue = particle.selfBestValue;//局部最佳值
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if (isMax) {//取最大值
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if (value > globalValue) {//更新全局最大值
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globalValue = value;
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//更新全局最佳位置
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for (int i = 0; i < allBest.length; i++) {
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allBest[i] = parameter[i];
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}
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}
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if (value > selfValue) {//更新局部最大值
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particle.selfBestValue = value;
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//更新局部最佳位置
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for (int i = 0; i < bestData.length; i++) {
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bestData[i].selfBestPosition = parameter[i];
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}
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}
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} else {//取最小值
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if (globalValue < 0 || value < globalValue) {//更新全局最小值
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globalValue = value;
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//更新全局最佳位置
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for (int i = 0; i < allBest.length; i++) {
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allBest[i] = parameter[i];
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}
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}
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if (selfValue < 0 || value < selfValue) {//更新全局最小值
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particle.selfBestValue = value;
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//更新局部最佳位置
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for (int i = 0; i < bestData.length; i++) {
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bestData[i].selfBestPosition = parameter[i];
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}
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}
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}
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//先更新粒子每个维度的速度
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for (int i = 0; i < bestData.length; i++) {
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double speed = bestData[i].speed;//当前维度的速度
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double pid = bestData[i].selfBestPosition;//当前自己的最佳位置
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double selfPosition = parameter[i];//当前自己的位置
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double pgd = allBest[i];//当前维度的全局最佳位置
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//当前维度更新后的速度
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speed = inertialFactor * speed + selfStudyFactor * random.nextDouble() * (pid - selfPosition)
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+ socialStudyFactor * random.nextDouble() * (pgd - selfPosition);
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if (Math.abs(speed) > maxSpeed) {
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if (speed > 0) {
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speed = maxSpeed;
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} else {
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speed = -maxSpeed;
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}
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}
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bestData[i].speed = speed;
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//更新该粒子该维度新的位置
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double position = selfPosition + speed;
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if (position < minBorder[i]) {
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position = minBorder[i];
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}
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if (position > maxBorder[i]) {
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position = maxBorder[i];
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}
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bestData[i].selfPosition = position;
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}
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}
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class Particle {//粒子
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private BestData[] bestDataArray;
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private double selfBestValue = -1;//自身最优的值
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private double[] getParameter() {//获取粒子位置信息
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double[] parameter = new double[bestDataArray.length];
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for (int i = 0; i < parameter.length; i++) {
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parameter[i] = bestDataArray[i].selfPosition;
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}
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return parameter;
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}
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protected Particle(int dimensionNub) {//初始化随机位置
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bestDataArray = new BestData[dimensionNub];
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for (int i = 0; i < dimensionNub; i++) {
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int min = minBorder[i];
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int max = maxBorder[i];
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int region = max - min + 1;
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int position = random.nextInt(region) + min;//初始化该维度的位置
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bestDataArray[i] = new BestData(position);
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}
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}
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}
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class BestData {//数据保存
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|
||||
private BestData(double selfPosition) {
|
||||
this.selfBestPosition = selfPosition;
|
||||
this.selfPosition = selfPosition;
|
||||
}
|
||||
|
||||
private double speed = 1;//该粒子当前维度的速度
|
||||
private double selfBestPosition;//当前维度自身最优的历史位置/自己最优位置的值
|
||||
private double selfPosition;//当前维度自己现在的位置/也就是当前维度自己的值
|
||||
}
|
||||
}
|
||||
@ -82,11 +82,14 @@ public abstract class Frequency {//统计频数
|
||||
|
||||
public double dc(double... m) {//计算离散系数
|
||||
double ave = average(m);//先计算出平均值
|
||||
double allNub = 0;
|
||||
for (int i = 0; i < m.length; i++) {
|
||||
allNub = allNub + Math.pow(m[i] - ave, 2);
|
||||
double dc = 0;
|
||||
if (ave > 0) {
|
||||
double allNub = 0;
|
||||
for (int i = 0; i < m.length; i++) {
|
||||
allNub = allNub + Math.pow(m[i] - ave, 2);
|
||||
}
|
||||
dc = ArithUtil.div(Math.sqrt(ArithUtil.div(allNub, m.length)), ave);//离散系数
|
||||
}
|
||||
double dc = ArithUtil.div(Math.sqrt(ArithUtil.div(allNub, m.length)), ave);//离散系数
|
||||
return dc;
|
||||
}
|
||||
|
||||
|
||||
@ -24,17 +24,17 @@ public class DataObservation {
|
||||
public static void main(String[] args) throws Exception {
|
||||
//372,330,右 最大值 147.44
|
||||
//377 ,330右 最大值 69.6
|
||||
int xp = 123;
|
||||
int yp = 165;//290
|
||||
observation2("/Users/lidapeng/Desktop/test/testOne/a0.jpg", xp, yp);
|
||||
int xp = 100;
|
||||
int yp = 720;//290
|
||||
observation2("/Users/lidapeng/Desktop/test/testOne/e2.jpg", xp, yp);
|
||||
}
|
||||
|
||||
public static void observation2(String url, int xp, int yp) throws Exception {
|
||||
Picture picture = new Picture();
|
||||
ThreeChannelMatrix threeChannelMatrix = picture.getThreeMatrix(url);
|
||||
ThreeChannelMatrix myThreeChannelMatrix = convolution.getRegionMatrix(threeChannelMatrix, xp, yp, 270, 274);
|
||||
RegionFeature regionFeature = new RegionFeature(myThreeChannelMatrix, xp, yp);
|
||||
regionFeature.start();
|
||||
ThreeChannelMatrix myThreeChannelMatrix = convolution.getRegionMatrix(threeChannelMatrix, xp, yp, 300, 300);
|
||||
RegionCut regionCut = new RegionCut(myThreeChannelMatrix, xp, yp, 30);
|
||||
regionCut.start();
|
||||
}
|
||||
|
||||
public static void observation(String url, int xp, int yp, int size) throws Exception {
|
||||
|
||||
@ -68,16 +68,16 @@ public class FoodTest {
|
||||
cutting.setRegionNub(100);
|
||||
cutting.setMaxIou(2);
|
||||
//knn参数
|
||||
templeConfig.setKnnNub(1);
|
||||
templeConfig.setKnnNub(15);
|
||||
//池化比例
|
||||
templeConfig.setPoolSize(2);//缩小比例
|
||||
//聚类
|
||||
templeConfig.setFeatureNub(3);//聚类特征数量
|
||||
templeConfig.setFeatureNub(5);//聚类特征数量
|
||||
//菜品识别实体类
|
||||
food.setShrink(5);//缩紧像素
|
||||
food.setTimes(1);//聚类数据增强
|
||||
food.setRegionSize(5);
|
||||
KNerveManger kNerveManger = new KNerveManger(9, 24, 2000);
|
||||
KNerveManger kNerveManger = new KNerveManger(12, 24, 6000);
|
||||
food.setkNerveManger(kNerveManger);
|
||||
food.setRowMark(0.15);//0.12
|
||||
food.setColumnMark(0.15);//0.25
|
||||
@ -107,7 +107,7 @@ public class FoodTest {
|
||||
// ThreeChannelMatrix threeChannelMatrix = picture.getThreeMatrix("/Users/lidapeng/Desktop/myDocument/d.jpg");
|
||||
// operation.setTray(threeChannelMatrix);
|
||||
String name = "/Users/lidapeng/Desktop/test/testOne/";
|
||||
for (int i = 0; i < 1; i++) {
|
||||
for (int i = 0; i < 3; i++) {
|
||||
System.out.println("轮数============================" + i);
|
||||
ThreeChannelMatrix threeChannelMatrix1 = picture.getThreeMatrix(name + "a" + i + ".jpg");
|
||||
ThreeChannelMatrix threeChannelMatrix2 = picture.getThreeMatrix(name + "b" + i + ".jpg");
|
||||
@ -160,62 +160,88 @@ public class FoodTest {
|
||||
}
|
||||
System.out.println("========================");
|
||||
kNerveManger.startStudy();
|
||||
int i = 0;
|
||||
ThreeChannelMatrix threeChannelMatrix1 = picture.getThreeMatrix(name + "a" + i + ".jpg");
|
||||
ThreeChannelMatrix threeChannelMatrix2 = picture.getThreeMatrix(name + "b" + i + ".jpg");
|
||||
ThreeChannelMatrix threeChannelMatrix3 = picture.getThreeMatrix(name + "c" + i + ".jpg");
|
||||
ThreeChannelMatrix threeChannelMatrix4 = picture.getThreeMatrix(name + "d" + i + ".jpg");
|
||||
ThreeChannelMatrix threeChannelMatrix5 = picture.getThreeMatrix(name + "e" + i + ".jpg");
|
||||
ThreeChannelMatrix threeChannelMatrix6 = picture.getThreeMatrix(name + "f" + i + ".jpg");
|
||||
ThreeChannelMatrix threeChannelMatrix7 = picture.getThreeMatrix(name + "g" + i + ".jpg");
|
||||
ThreeChannelMatrix threeChannelMatrix8 = picture.getThreeMatrix(name + "h" + i + ".jpg");
|
||||
ThreeChannelMatrix threeChannelMatrix9 = picture.getThreeMatrix(name + "i" + i + ".jpg");
|
||||
ThreeChannelMatrix threeChannelMatrix10 = picture.getThreeMatrix(name + "j" + i + ".jpg");
|
||||
int i = 3;
|
||||
// ThreeChannelMatrix threeChannelMatrix1 = picture.getThreeMatrix(name + "a" + i + ".jpg");
|
||||
// ThreeChannelMatrix threeChannelMatrix2 = picture.getThreeMatrix(name + "b" + i + ".jpg");
|
||||
// ThreeChannelMatrix threeChannelMatrix3 = picture.getThreeMatrix(name + "c" + i + ".jpg");
|
||||
// ThreeChannelMatrix threeChannelMatrix4 = picture.getThreeMatrix(name + "d" + i + ".jpg");
|
||||
// ThreeChannelMatrix threeChannelMatrix5 = picture.getThreeMatrix(name + "e" + i + ".jpg");
|
||||
// ThreeChannelMatrix threeChannelMatrix6 = picture.getThreeMatrix(name + "f" + i + ".jpg");
|
||||
// ThreeChannelMatrix threeChannelMatrix7 = picture.getThreeMatrix(name + "g" + i + ".jpg");
|
||||
// ThreeChannelMatrix threeChannelMatrix8 = picture.getThreeMatrix(name + "h" + i + ".jpg");
|
||||
// ThreeChannelMatrix threeChannelMatrix9 = picture.getThreeMatrix(name + "i" + i + ".jpg");
|
||||
// ThreeChannelMatrix threeChannelMatrix10 = picture.getThreeMatrix(name + "j" + i + ".jpg");
|
||||
ThreeChannelMatrix threeChannelMatrix11 = picture.getThreeMatrix(name + "k" + i + ".jpg");
|
||||
ThreeChannelMatrix threeChannelMatrix12 = picture.getThreeMatrix(name + "l" + i + ".jpg");
|
||||
// ThreeChannelMatrix threeChannelMatrix12 = picture.getThreeMatrix(name + "l" + i + ".jpg");
|
||||
ThreeChannelMatrix threeChannelMatrix13 = picture.getThreeMatrix(name + "m" + i + ".jpg");
|
||||
ThreeChannelMatrix threeChannelMatrix14 = picture.getThreeMatrix(name + "n" + i + ".jpg");
|
||||
|
||||
ThreeChannelMatrix threeChannelMatrix15 = picture.getThreeMatrix(name + "o" + i + ".jpg");
|
||||
ThreeChannelMatrix threeChannelMatrix16 = picture.getThreeMatrix(name + "p" + i + ".jpg");
|
||||
ThreeChannelMatrix threeChannelMatrix17 = picture.getThreeMatrix(name + "q" + i + ".jpg");
|
||||
ThreeChannelMatrix threeChannelMatrix18 = picture.getThreeMatrix(name + "r" + i + ".jpg");
|
||||
ThreeChannelMatrix threeChannelMatrix19 = picture.getThreeMatrix(name + "s" + i + ".jpg");
|
||||
ThreeChannelMatrix threeChannelMatrix20 = picture.getThreeMatrix(name + "t" + i + ".jpg");
|
||||
ThreeChannelMatrix threeChannelMatrix21 = picture.getThreeMatrix(name + "u" + i + ".jpg");
|
||||
ThreeChannelMatrix threeChannelMatrix22 = picture.getThreeMatrix(name + "v" + i + ".jpg");
|
||||
ThreeChannelMatrix threeChannelMatrix23 = picture.getThreeMatrix(name + "w" + i + ".jpg");
|
||||
ThreeChannelMatrix threeChannelMatrix24 = picture.getThreeMatrix(name + "x" + i + ".jpg");
|
||||
operation.colorLook(threeChannelMatrix1, specificationsList);
|
||||
operation.colorLook(threeChannelMatrix2, specificationsList);
|
||||
operation.colorLook(threeChannelMatrix3, specificationsList);
|
||||
operation.colorLook(threeChannelMatrix4, specificationsList);
|
||||
operation.colorLook(threeChannelMatrix5, specificationsList);
|
||||
operation.colorLook(threeChannelMatrix6, specificationsList);
|
||||
operation.colorLook(threeChannelMatrix7, specificationsList);
|
||||
operation.colorLook(threeChannelMatrix8, specificationsList);
|
||||
operation.colorLook(threeChannelMatrix9, specificationsList);
|
||||
operation.colorLook(threeChannelMatrix10, specificationsList);
|
||||
// ThreeChannelMatrix threeChannelMatrix14 = picture.getThreeMatrix(name + "n" + i + ".jpg");
|
||||
//
|
||||
// ThreeChannelMatrix threeChannelMatrix15 = picture.getThreeMatrix(name + "o" + i + ".jpg");
|
||||
// ThreeChannelMatrix threeChannelMatrix16 = picture.getThreeMatrix(name + "p" + i + ".jpg");
|
||||
// ThreeChannelMatrix threeChannelMatrix17 = picture.getThreeMatrix(name + "q" + i + ".jpg");
|
||||
// ThreeChannelMatrix threeChannelMatrix18 = picture.getThreeMatrix(name + "r" + i + ".jpg");
|
||||
// ThreeChannelMatrix threeChannelMatrix19 = picture.getThreeMatrix(name + "s" + i + ".jpg");
|
||||
// ThreeChannelMatrix threeChannelMatrix20 = picture.getThreeMatrix(name + "t" + i + ".jpg");
|
||||
// ThreeChannelMatrix threeChannelMatrix21 = picture.getThreeMatrix(name + "u" + i + ".jpg");
|
||||
// ThreeChannelMatrix threeChannelMatrix22 = picture.getThreeMatrix(name + "v" + i + ".jpg");
|
||||
// ThreeChannelMatrix threeChannelMatrix23 = picture.getThreeMatrix(name + "w" + i + ".jpg");
|
||||
// ThreeChannelMatrix threeChannelMatrix24 = picture.getThreeMatrix(name + "x" + i + ".jpg");
|
||||
// operation.colorLook(threeChannelMatrix1, specificationsList);
|
||||
// operation.colorLook(threeChannelMatrix2, specificationsList);
|
||||
// operation.colorLook(threeChannelMatrix3, specificationsList);
|
||||
// operation.colorLook(threeChannelMatrix4, specificationsList);
|
||||
// operation.colorLook(threeChannelMatrix5, specificationsList);
|
||||
// operation.colorLook(threeChannelMatrix6, specificationsList);
|
||||
// operation.colorLook(threeChannelMatrix7, specificationsList);
|
||||
// operation.colorLook(threeChannelMatrix8, specificationsList);
|
||||
// operation.colorLook(threeChannelMatrix9, specificationsList);
|
||||
// operation.colorLook(threeChannelMatrix10, specificationsList);
|
||||
operation.colorLook(threeChannelMatrix11, specificationsList);
|
||||
operation.colorLook(threeChannelMatrix12, specificationsList);
|
||||
// operation.colorLook(threeChannelMatrix12, specificationsList);
|
||||
operation.colorLook(threeChannelMatrix13, specificationsList);
|
||||
operation.colorLook(threeChannelMatrix14, specificationsList);
|
||||
operation.colorLook(threeChannelMatrix15, specificationsList);
|
||||
operation.colorLook(threeChannelMatrix16, specificationsList);
|
||||
operation.colorLook(threeChannelMatrix17, specificationsList);
|
||||
operation.colorLook(threeChannelMatrix18, specificationsList);
|
||||
operation.colorLook(threeChannelMatrix19, specificationsList);
|
||||
operation.colorLook(threeChannelMatrix20, specificationsList);
|
||||
operation.colorLook(threeChannelMatrix21, specificationsList);
|
||||
operation.colorLook(threeChannelMatrix22, specificationsList);
|
||||
operation.colorLook(threeChannelMatrix23, specificationsList);
|
||||
operation.colorLook(threeChannelMatrix24, specificationsList);
|
||||
// operation.colorLook(threeChannelMatrix14, specificationsList);
|
||||
// operation.colorLook(threeChannelMatrix15, specificationsList);
|
||||
// operation.colorLook(threeChannelMatrix16, specificationsList);
|
||||
// operation.colorLook(threeChannelMatrix17, specificationsList);
|
||||
// operation.colorLook(threeChannelMatrix18, specificationsList);
|
||||
// operation.colorLook(threeChannelMatrix19, specificationsList);
|
||||
// operation.colorLook(threeChannelMatrix20, specificationsList);
|
||||
// operation.colorLook(threeChannelMatrix21, specificationsList);
|
||||
// operation.colorLook(threeChannelMatrix22, specificationsList);
|
||||
// operation.colorLook(threeChannelMatrix23, specificationsList);
|
||||
// operation.colorLook(threeChannelMatrix24, specificationsList);
|
||||
//
|
||||
// test3(threeChannelMatrix1, operation, specificationsList, 1);
|
||||
// test3(threeChannelMatrix2, operation, specificationsList, 2);
|
||||
// test3(threeChannelMatrix3, operation, specificationsList, 3);
|
||||
// test3(threeChannelMatrix4, operation, specificationsList, 4);
|
||||
// test3(threeChannelMatrix5, operation, specificationsList, 5);
|
||||
// test3(threeChannelMatrix6, operation, specificationsList, 6);
|
||||
// test3(threeChannelMatrix7, operation, specificationsList, 7);
|
||||
// test3(threeChannelMatrix8, operation, specificationsList, 8);
|
||||
// test3(threeChannelMatrix9, operation, specificationsList, 9);
|
||||
// test3(threeChannelMatrix10, operation, specificationsList, 10);
|
||||
// test3(threeChannelMatrix11, operation, specificationsList, 11);
|
||||
// test3(threeChannelMatrix12, operation, specificationsList, 12);
|
||||
// test3(threeChannelMatrix13, operation, specificationsList, 13);
|
||||
// test3(threeChannelMatrix14, operation, specificationsList, 14);
|
||||
// test3(threeChannelMatrix15, operation, specificationsList, 15);
|
||||
// test3(threeChannelMatrix16, operation, specificationsList, 16);
|
||||
// test3(threeChannelMatrix17, operation, specificationsList, 17);
|
||||
// test3(threeChannelMatrix18, operation, specificationsList, 18);
|
||||
// test3(threeChannelMatrix19, operation, specificationsList, 19);
|
||||
// test3(threeChannelMatrix20, operation, specificationsList, 20);
|
||||
// test3(threeChannelMatrix21, operation, specificationsList, 21);
|
||||
// test3(threeChannelMatrix22, operation, specificationsList, 22);
|
||||
// test3(threeChannelMatrix23, operation, specificationsList, 23);
|
||||
//test3(threeChannelMatrix24, operation, specificationsList, 24);
|
||||
|
||||
}
|
||||
|
||||
private static void test3(ThreeChannelMatrix threeChannelMatrix, Operation operation, List<Specifications> specifications) throws Exception {
|
||||
private static void test3(ThreeChannelMatrix threeChannelMatrix, Operation operation, List<Specifications> specifications,
|
||||
int realType) throws Exception {
|
||||
int type = operation.colorLook(threeChannelMatrix, specifications).get(0).getType();
|
||||
System.out.println(type);
|
||||
System.out.println(type + ",realType==" + realType);
|
||||
}
|
||||
|
||||
public static void study() throws Exception {
|
||||
|
||||
56
src/test/java/coverTest/regionCut/ColorFunction.java
Normal file
56
src/test/java/coverTest/regionCut/ColorFunction.java
Normal file
@ -0,0 +1,56 @@
|
||||
package coverTest.regionCut;
|
||||
|
||||
import org.wlld.MatrixTools.Matrix;
|
||||
import org.wlld.i.PsoFunction;
|
||||
import org.wlld.imageRecognition.ThreeChannelMatrix;
|
||||
import org.wlld.tools.Frequency;
|
||||
|
||||
import java.util.ArrayList;
|
||||
import java.util.HashMap;
|
||||
import java.util.List;
|
||||
import java.util.Map;
|
||||
|
||||
/**
|
||||
* @param
|
||||
* @DATA
|
||||
* @Author LiDaPeng
|
||||
* @Description
|
||||
*/
|
||||
public class ColorFunction extends Frequency implements PsoFunction {
|
||||
private Matrix matrixR;
|
||||
private Matrix matrixG;
|
||||
private Matrix matrixB;
|
||||
private Map<Integer, double[]> pixels = new HashMap<>();
|
||||
|
||||
public ColorFunction(ThreeChannelMatrix threeChannelMatrix) {
|
||||
matrixR = threeChannelMatrix.getMatrixR();
|
||||
matrixG = threeChannelMatrix.getMatrixG();
|
||||
matrixB = threeChannelMatrix.getMatrixB();
|
||||
}
|
||||
|
||||
@Override
|
||||
public double getResult(double[] parameter, int id) throws Exception {
|
||||
int x = (int) parameter[0];
|
||||
int y = (int) parameter[1];
|
||||
double[] rgb = new double[]{matrixR.getNumber(x, y) / 255, matrixG.getNumber(x, y) / 255,
|
||||
matrixB.getNumber(x, y) / 255};
|
||||
pixels.put(id, rgb);
|
||||
//计算当前方差
|
||||
return getDist();
|
||||
}
|
||||
|
||||
private double getDist() {//计算当前均方误差
|
||||
double[] r = new double[pixels.size()];
|
||||
double[] g = new double[pixels.size()];
|
||||
double[] b = new double[pixels.size()];
|
||||
for (Map.Entry<Integer, double[]> entry : pixels.entrySet()) {
|
||||
double[] rgb = entry.getValue();
|
||||
int key = entry.getKey();
|
||||
r[key] = rgb[0];
|
||||
g[key] = rgb[1];
|
||||
b[key] = rgb[2];
|
||||
}
|
||||
return dc(r) + dc(g) + dc(b);
|
||||
}
|
||||
|
||||
}
|
||||
@ -1,12 +1,10 @@
|
||||
package coverTest.regionCut;
|
||||
|
||||
import org.wlld.Ma;
|
||||
import org.wlld.MatrixTools.Matrix;
|
||||
import org.wlld.config.Kernel;
|
||||
import org.wlld.imageRecognition.ThreeChannelMatrix;
|
||||
import org.wlld.pso.PSO;
|
||||
|
||||
import java.util.HashMap;
|
||||
import java.util.Map;
|
||||
import java.util.*;
|
||||
|
||||
/**
|
||||
* @param
|
||||
@ -15,8 +13,7 @@ import java.util.Map;
|
||||
* @Description 分区切割
|
||||
*/
|
||||
public class RegionCut {
|
||||
private Matrix matrixH;
|
||||
private Matrix regionMatrix;//分区地图
|
||||
private ThreeChannelMatrix threeChannelMatrix;
|
||||
private int fatherX;
|
||||
private int fatherY;
|
||||
private int size;
|
||||
@ -24,261 +21,43 @@ public class RegionCut {
|
||||
private Map<Integer, Double> minMap = new HashMap<>();//保存最小值
|
||||
private Map<Integer, Double> maxMap = new HashMap<>();//保存最大值
|
||||
|
||||
public RegionCut(Matrix matrixH, int fatherX, int fatherY, int size) {
|
||||
this.matrixH = matrixH;
|
||||
public RegionCut(ThreeChannelMatrix threeChannelMatrix, int fatherX, int fatherY, int size) {
|
||||
this.fatherX = fatherX;
|
||||
this.fatherY = fatherY;
|
||||
this.size = size;
|
||||
regionMatrix = new Matrix(matrixH.getX(), matrixH.getY());
|
||||
this.threeChannelMatrix = threeChannelMatrix;
|
||||
}
|
||||
|
||||
private void setLimit(int id, double pixel) {
|
||||
double min = minMap.get(id);
|
||||
double max = maxMap.get(id);
|
||||
if (pixel > max) {
|
||||
maxMap.put(id, pixel);
|
||||
}
|
||||
if (pixel < min) {
|
||||
minMap.put(id, pixel);
|
||||
}
|
||||
}
|
||||
|
||||
private void firstCut() throws Exception {//进行第一次切割
|
||||
int x = matrixH.getX();
|
||||
int y = matrixH.getY();
|
||||
int size = x * y;
|
||||
System.out.println("像素数量：" + size);
|
||||
for (int i = 0; i < x; i++) {
|
||||
for (int j = 0; j < y; j++) {
|
||||
double regionId = regionMatrix.getNumber(i, j);
|
||||
if (regionId < 0.5) {//该像素没有被连接
|
||||
boolean isStop;
|
||||
double self = matrixH.getNumber(i, j);//灰度值
|
||||
regionMatrix.setNub(i, j, id);
|
||||
minMap.put(id, self);
|
||||
maxMap.put(id, self);
|
||||
//System.out.println(regionMatrix.getString());
|
||||
int xi = i;
|
||||
int yj = j;
|
||||
do {
|
||||
double mySelf = matrixH.getNumber(xi, yj);//灰度值
|
||||
int pixel = pixelLine(xi, yj, mySelf);
|
||||
int column = pixel & 0xfff;
|
||||
int row = (pixel >> 12) & 0xfff;
|
||||
double type = regionMatrix.getNumber(row, column);
|
||||
if (type < 0.5) {//可以连接
|
||||
regionMatrix.setNub(row, column, id);//进行连接
|
||||
setLimit(id, mySelf);
|
||||
double mySelfSon = matrixH.getNumber(row, column);//灰度值
|
||||
int pixelOther = pixelLine(row, column, mySelfSon);
|
||||
int column2 = pixelOther & 0xfff;
|
||||
int row2 = (pixelOther >> 12) & 0xfff;
|
||||
isStop = row2 == xi && column2 == yj;
|
||||
xi = row;
|
||||
yj = column;
|
||||
} else {//已经被连接了，跳出
|
||||
isStop = true;
|
||||
}
|
||||
} while (!isStop);
|
||||
id++;
|
||||
}
|
||||
}
|
||||
}
|
||||
System.out.println("第一次选区数量：" + id);
|
||||
ColorFunction colorFunction = new ColorFunction(threeChannelMatrix);
|
||||
int[] minBorder = new int[]{0, 0};
|
||||
int[] maxBorder = new int[]{299, 299};
|
||||
PSO pso = new PSO(2, minBorder, maxBorder, 400, 200,
|
||||
colorFunction, 0.1, 0.1, 0.1, true, 10);
|
||||
pso.start(fatherX, fatherY);
|
||||
// Matrix matrixR = threeChannelMatrix.getMatrixR();
|
||||
// Matrix matrixG = threeChannelMatrix.getMatrixG();
|
||||
// Matrix matrixB = threeChannelMatrix.getMatrixB();
|
||||
// Matrix matrixRGB = threeChannelMatrix.getMatrixRGB();
|
||||
// int x = matrixR.getX();
|
||||
// int y = matrixR.getY();
|
||||
// int index = 0;
|
||||
// for (int i = 0; i <= x - size; i += size) {
|
||||
// for (int j = 0; j <= y - size; j += size) {
|
||||
// Matrix matrixRs = matrixR.getSonOfMatrix(i, j, size, size);
|
||||
// Matrix matrixGs = matrixG.getSonOfMatrix(i, j, size, size);
|
||||
// Matrix matrixBs = matrixB.getSonOfMatrix(i, j, size, size);
|
||||
// index++;
|
||||
// }
|
||||
// }
|
||||
|
||||
|
||||
}
|
||||
|
||||
public void secondCut() throws Exception {//二切
|
||||
int x = matrixH.getX();
|
||||
int y = matrixH.getY();
|
||||
for (int i = 0; i < x; i++) {
|
||||
for (int j = 0; j < y; j++) {
|
||||
double key = regionMatrix.getNumber(i, j);//与周围八方向比较看是否有异类
|
||||
getOther(i, j, (int) key, matrixH.getNumber(i, j));
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
private void updateType(int type, int toType) throws Exception {
|
||||
int x = regionMatrix.getX();
|
||||
int y = regionMatrix.getY();
|
||||
for (int i = 0; i < x; i++) {
|
||||
for (int j = 0; j < y; j++) {
|
||||
if (regionMatrix.getNumber(i, j) == type) {
|
||||
regionMatrix.setNub(i, j, toType);
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
private void getOther(int x, int y, int key, double self) throws Exception {
|
||||
double[] pixels = getPixels(x, y, false);
|
||||
for (int i = 0; i < pixels.length; i++) {
|
||||
int pix = (int) pixels[i];
|
||||
if (pix > 0 && pix != key) {//接壤的非同类
|
||||
double min = minMap.get(pix);
|
||||
double max = maxMap.get(pix);
|
||||
double maxDist = max - min;
|
||||
int row = x;
|
||||
int column = y;
|
||||
switch (i) {
|
||||
case 0://上
|
||||
row = x - 1;
|
||||
break;
|
||||
case 1://左
|
||||
column = y - 1;
|
||||
break;
|
||||
case 2://下
|
||||
row = x + 1;
|
||||
break;
|
||||
case 3://右
|
||||
column = y + 1;
|
||||
break;
|
||||
case 4://左上
|
||||
column = y - 1;
|
||||
row = x - 1;
|
||||
break;
|
||||
case 5://左下
|
||||
column = y - 1;
|
||||
row = x + 1;
|
||||
break;
|
||||
case 6://右下
|
||||
column = y + 1;
|
||||
row = x + 1;
|
||||
break;
|
||||
case 7://右上
|
||||
column = y + 1;
|
||||
row = x - 1;
|
||||
break;
|
||||
}
|
||||
double dist = Math.abs(matrixH.getNumber(row, column) - self);
|
||||
if (dist < maxDist * 0.2) {//两个选区可以合并
|
||||
setLimit(key, min);
|
||||
setLimit(key, max);
|
||||
updateType(pix, key);
|
||||
id--;
|
||||
}
|
||||
break;
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
public void start() throws Exception {
|
||||
firstCut();//初切
|
||||
System.out.println("区域数量1：" + id);
|
||||
for (int i = 0; i < 1; i++) {
|
||||
secondCut();//二切
|
||||
}
|
||||
System.out.println("区域数量2：" + id);
|
||||
System.out.println(regionMatrix.getString());
|
||||
firstCut();
|
||||
}
|
||||
|
||||
private int pixelLine(int x, int y, double self) throws Exception {
|
||||
double[] pixels = getPixels(x, y, true);
|
||||
int minIndex = getMinIndex(pixels, self);
|
||||
int row = x;
|
||||
int column = y;
|
||||
switch (minIndex) {
|
||||
case 0://上
|
||||
row = x - 1;
|
||||
break;
|
||||
case 1://左
|
||||
column = y - 1;
|
||||
break;
|
||||
case 2://下
|
||||
row = x + 1;
|
||||
break;
|
||||
case 3://右
|
||||
column = y + 1;
|
||||
break;
|
||||
case 4://左上
|
||||
column = y - 1;
|
||||
row = x - 1;
|
||||
break;
|
||||
case 5://左下
|
||||
column = y - 1;
|
||||
row = x + 1;
|
||||
break;
|
||||
case 6://右下
|
||||
column = y + 1;
|
||||
row = x + 1;
|
||||
break;
|
||||
case 7://右上
|
||||
column = y + 1;
|
||||
row = x - 1;
|
||||
break;
|
||||
}
|
||||
return row << 12 | column;
|
||||
}
|
||||
|
||||
private double[] getPixels(int x, int y, boolean isFirst) throws Exception {
|
||||
double left = 1, leftTop = 1, leftBottom = 1, right = 1, rightTop = 1, rightBottom = 1, top = 1, bottom = 1;
|
||||
Matrix matrix;
|
||||
if (isFirst) {
|
||||
matrix = matrixH;
|
||||
} else {
|
||||
matrix = regionMatrix;
|
||||
}
|
||||
if (x == 0) {
|
||||
top = -1;
|
||||
leftTop = -1;
|
||||
rightTop = -1;
|
||||
}
|
||||
if (y == 0) {
|
||||
leftTop = -1;
|
||||
left = -1;
|
||||
leftBottom = -1;
|
||||
}
|
||||
if (x == size - 1) {
|
||||
leftBottom = -1;
|
||||
bottom = -1;
|
||||
rightBottom = -1;
|
||||
}
|
||||
if (y == size - 1) {
|
||||
rightTop = -1;
|
||||
right = -1;
|
||||
rightBottom = -1;
|
||||
}
|
||||
if (top > 0) {
|
||||
top = matrix.getNumber(x - 1, y);
|
||||
}
|
||||
if (left > 0) {
|
||||
left = matrix.getNumber(x, y - 1);
|
||||
}
|
||||
if (right > 0) {
|
||||
right = matrix.getNumber(x, y + 1);
|
||||
}
|
||||
if (bottom > 0) {
|
||||
bottom = matrix.getNumber(x + 1, y);
|
||||
}
|
||||
if (leftTop > 0) {
|
||||
leftTop = matrix.getNumber(x - 1, y - 1);
|
||||
}
|
||||
if (leftBottom > 0) {
|
||||
leftBottom = matrix.getNumber(x + 1, y - 1);
|
||||
}
|
||||
if (rightTop > 0) {
|
||||
rightTop = matrix.getNumber(x - 1, y + 1);
|
||||
}
|
||||
if (rightBottom > 0) {
|
||||
rightBottom = matrix.getNumber(x + 1, y + 1);
|
||||
}
|
||||
return new double[]{top, left, bottom, right, leftTop, leftBottom, rightBottom, rightTop};
|
||||
|
||||
}
|
||||
|
||||
private int getMinIndex(double[] array, double self) {//获取最小值
|
||||
double min = -1;
|
||||
int minIdx = 0;
|
||||
for (int i = 0; i < array.length; i++) {
|
||||
double nub = array[i];
|
||||
if (nub > 0) {
|
||||
nub = Math.abs(nub - self);
|
||||
if (min < 0 || nub < min) {
|
||||
min = nub;
|
||||
minIdx = i;
|
||||
}
|
||||
}
|
||||
}
|
||||
return minIdx;
|
||||
}
|
||||
}
|
||||
|
||||
@ -1,8 +1,5 @@
|
||||
package coverTest.regionCut;
|
||||
|
||||
import java.util.ArrayList;
|
||||
import java.util.List;
|
||||
|
||||
/**
|
||||
* @param
|
||||
* @DATA
|
||||
@ -10,6 +7,11 @@ import java.util.List;
|
||||
* @Description
|
||||
*/
|
||||
public class RegionCutBody {
|
||||
private List<Integer> pixels = new ArrayList<>();
|
||||
private double feature;//特征值
|
||||
private int x;
|
||||
private int y;
|
||||
private int id;
|
||||
private int minId;//最近id
|
||||
private int channel;//渠道
|
||||
|
||||
}
|
||||
|
||||
@ -17,9 +17,6 @@ import java.util.Arrays;
|
||||
*/
|
||||
public class RegionFeature extends Frequency {
|
||||
private Matrix matrix;
|
||||
private Matrix matrixR;
|
||||
private Matrix matrixG;
|
||||
private Matrix matrixB;
|
||||
private Matrix kernel = Kernel.Big;
|
||||
private int fatherX;
|
||||
private int fatherY;
|
||||
@ -29,9 +26,6 @@ public class RegionFeature extends Frequency {
|
||||
this.matrix = threeChannelMatrix.getMatrixRGB();
|
||||
this.fatherX = fatherX;
|
||||
this.fatherY = fatherY;
|
||||
matrixR = threeChannelMatrix.getMatrixR();
|
||||
matrixG = threeChannelMatrix.getMatrixG();
|
||||
matrixB = threeChannelMatrix.getMatrixB();
|
||||
}
|
||||
|
||||
private double getMatrixVar(Matrix matrix) throws Exception {
|
||||
|
||||
Loading…
Reference in New Issue
Block a user