增加切割图像边缘减除

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

@@ -70,6 +70,15 @@ public class TempleConfig {
     private ThreeChannelMatrix backGround;//背景面板
     private double backGroundError;//背景误差偏移量，0-255
     private Cutting cutting = new Cutting();
+    private double edge = 0;//边缘剪掉多少份
+
+    public double getEdge() {
+        return edge;
+    }
+
+    public void setEdge(double edge) {
+        this.edge = edge;
+    }
 
     public Cutting getCutting() {
         return cutting;

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

@@ -18,8 +18,8 @@ public class Watershed {
     private Matrix regionMap;//分区图
     private int xSize;//单元高度
     private int ySize;//单元宽度
-    private double th = Kernel.th;//灰度阈值
-    private int regionNub = Kernel.Region_Nub;//一张图分多少份
+    private double th;//灰度阈值
+    private int regionNub;//一张图分多少份
     private Map<Integer, RegionBody> regionBodyMap = new HashMap<>();
     private double rainTh = 0;
     private int xMax;
@@ -27,6 +27,7 @@ public class Watershed {
     private double maxRain;
     private double width;
     private double height;
+    private double edgeSize = 0;//边缘提取多少份
     private List<Specifications> specifications;
 
     public Watershed(Matrix matrix, List<Specifications> specifications, TempleConfig templeConfig) throws Exception {
@@ -37,6 +38,9 @@ public class Watershed {
             maxRain = cutting.getMaxRain();
             this.matrix = matrix;
             this.specifications = specifications;
+            if (templeConfig.getEdge() > 0) {
+                edgeSize = templeConfig.getEdge();
+            }
             width = matrix.getY();
             height = matrix.getX();
             xSize = matrix.getX() / regionNub;
@@ -216,11 +220,15 @@ public class Watershed {
         for (Specifications specification : specifications) {
             int width = maxY - minY;
             int height = maxX - minX;
-//            double h = this.height / 8;
-//            double w = this.width / 8;
-            // boolean isCenter = minX > h && minY > w && minX < (h * 4.5) && minY < (w * 4.5);
+            boolean isCenter = true;
+            if (edgeSize > 0) {
+                double h = this.height / edgeSize;
+                double w = this.width / edgeSize;
+                isCenter = maxX > h && maxY > w && maxX < (h * (edgeSize - 1)) && maxY < (w * (edgeSize - 1));
+            }
             if (width >= specification.getMinWidth() && height >= specification.getMinHeight()
-                    && width <= specification.getMaxWidth() && height <= specification.getMaxHeight()) {
+                    && width <= specification.getMaxWidth() && height <= specification.getMaxHeight()
+                    && isCenter) {
                 isRight = true;
                 break;
             }

src/test/java/coverTest/FoodTest.java

@@ -112,22 +112,12 @@ public class FoodTest {
         for (int i = 1; i <= 1; i++) {
             ThreeChannelMatrix threeChannelMatrix1 = picture.getThreeMatrix("/Users/lidapeng/Documents/paramterTest/a" + i + ".jpg");
             ThreeChannelMatrix threeChannelMatrix2 = picture.getThreeMatrix("/Users/lidapeng/Documents/paramterTest/b" + i + ".jpg");
-            operation.colorStudy(threeChannelMatrix1, 83, specificationsList);
+            operation.colorStudy(threeChannelMatrix1, 1, specificationsList);
             System.out.println("=======================================");
-            operation.colorStudy(threeChannelMatrix2, 86, specificationsList);
+            operation.colorStudy(threeChannelMatrix2, 2, specificationsList);
             System.out.println("=======================================" + i);
         }
-        ModelParameter modelParameter = templeConfig.getModel();
-        if (modelParameter.getKnnVector() != null) {
-            System.out.println("not null 1");
-        }
-        String tr = JSON.toJSONString(modelParameter);
-        System.out.println(tr);
-        ModelParameter modelParameter1 = JSON.parseObject(tr, ModelParameter.class);
-        if (modelParameter1.getKnnVector() != null) {
-            System.out.println("not null 2");
-        }
-        //test2(templeConfig);
+        test2(templeConfig);
     }
 
     public static void study() throws Exception {

src/test/java/org/wlld/LangTest.java

@@ -71,19 +71,20 @@ public class LangTest {
         //创建模板读取累
         TemplateReader templateReader = new TemplateReader();
         WordTemple wordTemple = new WordTemple();//初始化语言模版
-        wordTemple.setTreeNub(9);
-        // wordTemple.setSplitWord(true);
+        //wordTemple.setTreeNub(9);
+        //wordTemple.setTrustPunishment(0.5);
+        wordTemple.setSplitWord(true);
         //读取语言模版，第一个参数是模版地址，第二个参数是编码方式 (教程里的第三个参数已经省略)
         //同时也是学习过程
         templateReader.read("/Users/lidapeng/Desktop/myDocument/model.txt", "UTF-8", wordTemple);
         Talk talk = new Talk(wordTemple);
         //输入语句进行识别，若有标点符号会形成LIST中的每个元素
         //返回的集合中每个值代表了输入语句，每个标点符号前语句的分类
-//        List<List<String>> lists = talk.getSplitWord("空调坏了，帮我修一修");
-//        for (List<String> list : lists) {
-//            System.out.println(list);
-//        }
-        List<Integer> list = talk.talk("空调坏了，帮我修一修");
-        System.out.println(list);
+        List<List<String>> lists = talk.getSplitWord("空调坏了，帮我修一修");
+        for (List<String> list : lists) {
+            System.out.println(list);
+        }
+//        List<Integer> list = talk.talk("空调坏了，帮我修一修");
+//        System.out.println(list);
     }
 }