diff --git a/src/main/java/org/wlld/imageRecognition/modelEntity/DeepMappingBody.java b/src/main/java/org/wlld/imageRecognition/modelEntity/DeepMappingBody.java
index b91c3de..a1c2550 100644
--- a/src/main/java/org/wlld/imageRecognition/modelEntity/DeepMappingBody.java
+++ b/src/main/java/org/wlld/imageRecognition/modelEntity/DeepMappingBody.java
@@ -1,11 +1,13 @@
 package org.wlld.imageRecognition.modelEntity;
 
+import org.wlld.MatrixTools.Matrix;
 import org.wlld.imageRecognition.TempleConfig;
 import org.wlld.imageRecognition.border.Knn;
 import org.wlld.imageRecognition.segmentation.DimensionMappingStudy;
 
-import java.util.HashMap;
-import java.util.Map;
+
+import java.util.List;
+import java.util.Set;
 
 /**
  * @param
@@ -16,11 +18,24 @@ import java.util.Map;
 public class DeepMappingBody {
     private DimensionMappingStudy dimensionAll;
     private TempleConfig templeConfig;
-    private Map<Integer, DimensionMappingStudy> mappingMap = new HashMap<>();
+    private List<KeyMapping> mappingList;
 
     public DeepMappingBody(TempleConfig templeConfig) throws Exception {
         this.templeConfig = templeConfig;
-        dimensionAll = new DimensionMappingStudy(templeConfig);
-        dimensionAll.start();
+        dimensionAll = new DimensionMappingStudy(templeConfig, true);
+        mappingList = dimensionAll.start();
+    }
+
+    public int getType(Matrix feature) throws Exception {
+        int type = dimensionAll.getType(feature);
+        for (KeyMapping keyMapping : mappingList) {
+            Set<Integer> region = keyMapping.getKeys();
+            if (region.contains(type)) {
+                DimensionMappingStudy mapping = keyMapping.getDimensionMapping();
+                type = mapping.getType(feature);
+                break;
+            }
+        }
+        return type;
     }
 }
diff --git a/src/main/java/org/wlld/imageRecognition/modelEntity/KeyMapping.java b/src/main/java/org/wlld/imageRecognition/modelEntity/KeyMapping.java
new file mode 100644
index 0000000..b3c1e19
--- /dev/null
+++ b/src/main/java/org/wlld/imageRecognition/modelEntity/KeyMapping.java
@@ -0,0 +1,32 @@
+package org.wlld.imageRecognition.modelEntity;
+
+import org.wlld.imageRecognition.segmentation.DimensionMappingStudy;
+
+import java.util.Set;
+
+/**
+ * @param
+ * @DATA
+ * @Author LiDaPeng
+ * @Description
+ */
+public class KeyMapping {
+    private Set<Integer> keys;
+    private DimensionMappingStudy dimensionMapping;
+
+    public Set<Integer> getKeys() {
+        return keys;
+    }
+
+    public void setKeys(Set<Integer> keys) {
+        this.keys = keys;
+    }
+
+    public DimensionMappingStudy getDimensionMapping() {
+        return dimensionMapping;
+    }
+
+    public void setDimensionMapping(DimensionMappingStudy dimensionMapping) {
+        this.dimensionMapping = dimensionMapping;
+    }
+}
diff --git a/src/main/java/org/wlld/imageRecognition/segmentation/DimensionMappingStudy.java b/src/main/java/org/wlld/imageRecognition/segmentation/DimensionMappingStudy.java
index 637a70a..e814cf2 100644
--- a/src/main/java/org/wlld/imageRecognition/segmentation/DimensionMappingStudy.java
+++ b/src/main/java/org/wlld/imageRecognition/segmentation/DimensionMappingStudy.java
@@ -3,6 +3,7 @@ package org.wlld.imageRecognition.segmentation;
 import org.wlld.MatrixTools.Matrix;
 import org.wlld.imageRecognition.TempleConfig;
 import org.wlld.imageRecognition.border.Knn;
+import org.wlld.imageRecognition.modelEntity.KeyMapping;
 import org.wlld.pso.PSO;
 
 import java.util.*;
@@ -19,10 +20,12 @@ public class DimensionMappingStudy {
     private Knn myKnn = new Knn(1);
     private double[] mappingSigma;//映射层
 
-    public DimensionMappingStudy(TempleConfig templeConfig) throws Exception {
+    public DimensionMappingStudy(TempleConfig templeConfig, boolean isClone) throws Exception {
         this.templeConfig = templeConfig;
         //深度克隆
-        myKnn.setFeatureMap(cloneFeature(templeConfig.getKnn().getFeatureMap()));
+        if (isClone) {
+            myKnn.setFeatureMap(cloneFeature(templeConfig.getKnn().getFeatureMap()));
+        }
     }
 
     public Knn getMyKnn() {
@@ -101,9 +104,9 @@ public class DimensionMappingStudy {
         return minSub;
     }
 
-    public void selfTest(int nub) throws Exception {//对模型数据进行自检测
-        Map<Integer, List<Matrix>> myFeatureMap = myKnn.getFeatureMap();//未映射的克隆的
-        Map<Integer, List<Matrix>> featureMap = templeConfig.getKnn().getFeatureMap();
+    public List<KeyMapping> selfTest(int nub) throws Exception {//对模型数据进行自检测
+        Map<Integer, List<Matrix>> myFeatureMap = templeConfig.getKnn().getFeatureMap();//未映射的克隆的
+        Map<Integer, List<Matrix>> featureMap = myKnn.getFeatureMap();
         MinTypeSort minTypeSort = new MinTypeSort();
         Map<Integer, List<MinType>> minMap = new HashMap<>();//保存与该类别最相似的类别,及距离值
         for (Map.Entry<Integer, List<Matrix>> entry : featureMap.entrySet()) {
@@ -137,13 +140,22 @@ public class DimensionMappingStudy {
             cups.add(cup);
         }
         List<Set<Integer>> setList = getTypeSet(cups);
+        List<KeyMapping> mappingList = new ArrayList<>();
         for (Set<Integer> set : setList) {
-            DimensionMappingStudy dimensionMappingStudy = new DimensionMappingStudy(templeConfig);
+            KeyMapping keyMapping = new KeyMapping();
+            DimensionMappingStudy dimension = new DimensionMappingStudy(templeConfig, false);
+            keyMapping.setDimensionMapping(dimension);
+            keyMapping.setKeys(set);
+            Knn knn = dimension.getMyKnn();
             for (int type : set) {
                 List<Matrix> features = myFeatureMap.get(type);
-
+                for (Matrix feature : features) {
+                    knn.insertMatrix(feature, type);
+                }
             }
+            dimension.mappingStart();
         }
+        return mappingList;
     }
 
     public List<Set<Integer>> getTypeSet(List<int[]> t) {
@@ -211,9 +223,12 @@ public class DimensionMappingStudy {
         return t1;
     }
 
+    public int getType(Matrix feature) throws Exception {
+        return myKnn.getType(feature);
+    }
 
     public void mappingStart() throws Exception {
-        Map<Integer, List<Matrix>> featureMap = templeConfig.getKnn().getFeatureMap();
+        Map<Integer, List<Matrix>> featureMap = myKnn.getFeatureMap();
         FeatureMapping featureMapping = new FeatureMapping(featureMap);
         int dimensionNub = templeConfig.getFeatureNub() * 3 * 2;//PSO维度
         //创建粒子群
@@ -236,9 +251,9 @@ public class DimensionMappingStudy {
         featureMapping(featureMap, mappingSigma, templeConfig);
     }
 
-    public void start() throws Exception {
+    public List<KeyMapping> start() throws Exception {
         mappingStart();
-        selfTest(3);
+        return selfTest(3);
     }
 
     private void featureMapping(Map<Integer, List<Matrix>> featureMap, double[] mapping
diff --git a/src/test/java/coverTest/FoodTest.java b/src/test/java/coverTest/FoodTest.java
index 285963c..ad5bda5 100644
--- a/src/test/java/coverTest/FoodTest.java
+++ b/src/test/java/coverTest/FoodTest.java
@@ -19,20 +19,7 @@ import java.util.*;
 public class FoodTest {
 
     public static void main(String[] args) throws Exception {
-        //test();
-        int[] a = new int[]{1, 4, 5, 7, 31};
-        int[] b = new int[]{4, 6, 7, 8, 21,};
-        int[] c = new int[]{12, 42, 54, 9};
-        int[] d = new int[]{63, 54, 99};
-        int[] e = new int[]{991, 123, 456};
-
-        List<int[]> t = new ArrayList<>();
-        t.add(a);
-        t.add(b);
-        t.add(c);
-        t.add(d);
-        t.add(e);
-        ab(t);
+        test();
     }
 
     public static void ab(List<int[]> t) {
@@ -235,7 +222,7 @@ public class FoodTest {
             operation.colorStudy(threeChannelMatrix23, 23, specificationsList, name);
             operation.colorStudy(threeChannelMatrix24, 24, specificationsList, name);
         }
-        DimensionMappingStudy dimensionMappingStudy = new DimensionMappingStudy(templeConfig);
+        DimensionMappingStudy dimensionMappingStudy = new DimensionMappingStudy(templeConfig, true);
         dimensionMappingStudy.start();//完成映射
         //dimensionMappingStudy.selfTest(6);//检查
         //System.out.println("========================");