增加参数实体类

src/main/java/org/wlld/imageRecognition/Operation.java

@@ -30,13 +30,13 @@ public class Operation {//进行计算
 
     public Operation(TempleConfig templeConfig) {
         this.templeConfig = templeConfig;
-        dif = templeConfig.getShrink();
+        dif = templeConfig.getFood().getShrink();
     }
 
     public Operation(TempleConfig templeConfig, OutBack outBack) {
         this.templeConfig = templeConfig;
         this.outBack = outBack;
-        dif = templeConfig.getShrink();
+        dif = templeConfig.getFood().getShrink();
     }
 
     public List<Double> convolution(Matrix matrix, Map<Integer, Double> tagging) throws Exception {
@@ -72,7 +72,7 @@ public class Operation {//进行计算
         int ySize = maxY - minY;
         ThreeChannelMatrix threeChannelMatrix1 = convolution.getRegionMatrix(threeChannelMatrix, minX, minY, xSize, ySize);
         // convolution.filtering(threeChannelMatrix1);//光照过滤
-        int times = templeConfig.getTimes();
+        int times = templeConfig.getFood().getTimes();
         for (int i = 0; i < times; i++) {
             List<Double> feature = convolution.getCenterColor(threeChannelMatrix1, templeConfig.getPoolSize(),
                     templeConfig.getFeatureNub());

src/main/java/org/wlld/imageRecognition/TempleConfig.java

@@ -19,6 +19,8 @@ import org.wlld.nerveCenter.NerveManager;
 import org.wlld.nerveCenter.Normalization;
 import org.wlld.nerveEntity.ModelParameter;
 import org.wlld.nerveEntity.SensoryNerve;
+import org.wlld.param.Cutting;
+import org.wlld.param.Food;
 import org.wlld.tools.ArithUtil;
 
 import java.util.ArrayList;
@@ -60,16 +62,17 @@ public class TempleConfig {
     private int hiddenNerveNub = 9;//隐层神经元个数
     private boolean isSoftMax = false;//是否启用softMax层
     private int poolSize = 2;//池化尺寸
-    private int regionNub = 100;//一张图行或列分多少个区块
-    private double hTh = 0.88;//灰度阈值
-    private double maxRain = 340;//不降雨RGB阈值
     private int featureNub = 4;//聚类特征数量
+    private Food food = new Food();
     private Knn knn;//KNN分类器
     private int knnNub = 7;//KNN投票人数
-    private int times = 10;//聚类循环次数
-    private int shrink = 60;//收缩参数
     private ThreeChannelMatrix backGround;//背景面板
     private double backGroundError;//背景误差偏移量，0-255
+    private Cutting cutting = new Cutting();
+
+    public Cutting getCutting() {
+        return cutting;
+    }
 
     public double getBackGroundError() {
         return backGroundError;
@@ -87,20 +90,8 @@ public class TempleConfig {
         this.backGround = backGround;
     }
 
-    public int getShrink() {
-        return shrink;
-    }
-
-    public void setShrink(int shrink) {
-        this.shrink = shrink;
-    }
-
-    public int getTimes() {
-        return times;
-    }
-
-    public void setTimes(int times) {
-        this.times = times;
+    public Food getFood() {
+        return food;
     }
 
     public Knn getKnn() {
@@ -123,30 +114,6 @@ public class TempleConfig {
         this.featureNub = featureNub;
     }
 
-    public double getMaxRain() {
-        return maxRain;
-    }
-
-    public void setMaxRain(double maxRain) {
-        this.maxRain = maxRain;
-    }
-
-    public int getRegionNub() {
-        return regionNub;
-    }
-
-    public void setRegionNub(int regionNub) {
-        this.regionNub = regionNub;
-    }
-
-    public double gethTh() {
-        return hTh;
-    }
-
-    public void sethTh(double hTh) {
-        this.hTh = hTh;
-    }
-
     public int getPoolSize() {
         return poolSize;
     }

src/main/java/org/wlld/imageRecognition/segmentation/Watershed.java

@@ -3,6 +3,7 @@ package org.wlld.imageRecognition.segmentation;
 import org.wlld.MatrixTools.Matrix;
 import org.wlld.config.Kernel;
 import org.wlld.imageRecognition.TempleConfig;
+import org.wlld.param.Cutting;
 
 import java.util.*;
 
@@ -28,9 +29,10 @@ public class Watershed {
 
     public Watershed(Matrix matrix, List<Specifications> specifications, TempleConfig templeConfig) throws Exception {
         if (matrix != null && specifications != null && specifications.size() > 0) {
-            th = templeConfig.gethTh();
-            regionNub = templeConfig.getRegionNub();
-            maxRain = templeConfig.getMaxRain();
+            Cutting cutting = templeConfig.getCutting();
+            th = cutting.getTh();
+            regionNub = cutting.getRegionNub();
+            maxRain = cutting.getMaxRain();
             this.matrix = matrix;
             this.specifications = specifications;
             xSize = matrix.getX() / regionNub;

src/main/java/org/wlld/param/Cutting.java

@@ -0,0 +1,37 @@
+package org.wlld.param;
+
+/**
+ * @param
+ * @DATA
+ * @Author LiDaPeng
+ * @Description 图像切割参数实体类
+ */
+public class Cutting {
+    private int regionNub = 200;//一张图行或列分多少个区块
+    private double th = 0.88;//灰度阈值
+    private double maxRain = 340;//不降雨RGB阈值
+
+    public int getRegionNub() {
+        return regionNub;
+    }
+
+    public void setRegionNub(int regionNub) {
+        this.regionNub = regionNub;
+    }
+
+    public double getTh() {
+        return th;
+    }
+
+    public void setTh(double th) {
+        this.th = th;
+    }
+
+    public double getMaxRain() {
+        return maxRain;
+    }
+
+    public void setMaxRain(double maxRain) {
+        this.maxRain = maxRain;
+    }
+}

src/main/java/org/wlld/param/Food.java

@@ -0,0 +1,28 @@
+package org.wlld.param;
+
+/**
+ * @param
+ * @DATA
+ * @Author LiDaPeng
+ * @Description 菜品识别实体类
+ */
+public class Food {
+    private int shrink = 60;//收缩参数
+    private int times = 10;//聚类增强次数
+
+    public int getShrink() {
+        return shrink;
+    }
+
+    public void setShrink(int shrink) {
+        this.shrink = shrink;
+    }
+
+    public int getTimes() {
+        return times;
+    }
+
+    public void setTimes(int times) {
+        this.times = times;
+    }
+}

src/test/java/coverTest/CoverTest.java

@@ -23,12 +23,8 @@ import java.util.Map;
  */
 public class CoverTest {
     public static void main(String[] args) throws Exception {
-//        double a = 220;
-//        double b = 220;
-//        double c = 220;
-//        double d = Math.sqrt(Math.pow(a, 2) + Math.pow(b, 2) + Math.pow(c, 2));
-//        System.out.println(d);
-        cover();
+
+        //cover();
     }
 
     public static void insertModel(String model) throws Exception {//注入模型

src/test/java/coverTest/FoodTest.java

@@ -9,6 +9,8 @@ import org.wlld.imageRecognition.*;
 import org.wlld.imageRecognition.segmentation.RegionBody;
 import org.wlld.imageRecognition.segmentation.Specifications;
 import org.wlld.nerveEntity.ModelParameter;
+import org.wlld.param.Cutting;
+import org.wlld.param.Food;
 import org.wlld.tools.ArithUtil;
 
 import java.util.ArrayList;
@@ -18,7 +20,7 @@ public class FoodTest {
 
     public static void main(String[] args) throws Exception {
         //test2(null);
-        test();
+        //test();
     }
 
     public static void one(double[] test, double[] right, double[] wrong) {
@@ -67,14 +69,21 @@ public class FoodTest {
     public static TempleConfig getTemple() throws Exception {
         TempleConfig templeConfig = new TempleConfig();
         templeConfig.isShowLog(true);//是否打印日志
-        templeConfig.setMaxRain(320);//切割阈值
-        templeConfig.setFeatureNub(3);
-        templeConfig.sethTh(0.88);
+        Cutting cutting = templeConfig.getCutting();
+        Food food =templeConfig.getFood();
+        //切割
+        cutting.setMaxRain(320);//切割阈值
+        cutting.setTh(0.88);
+        cutting.setRegionNub(200);
+        //knn参数
         templeConfig.setKnnNub(3);
-        templeConfig.setPoolSize(2);
-        templeConfig.setRegionNub(200);
-        templeConfig.setShrink(60);
-        templeConfig.setTimes(2);//聚类数据增强
+        //池化比例
+        templeConfig.setPoolSize(2);//缩小比例
+        //聚类
+        templeConfig.setFeatureNub(3);//聚类特征数量
+        //菜品识别实体类
+        food.setShrink(60);//缩紧像素
+        food.setTimes(2);//聚类数据增强
         templeConfig.setClassifier(Classifier.KNN);
         templeConfig.init(StudyPattern.Cover_Pattern, true, 400, 400, 3);
         return templeConfig;