修复KNN模型注入及获取的BUG

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

@@ -17,6 +17,7 @@ import org.wlld.imageRecognition.modelEntity.LvqModel;
 import org.wlld.imageRecognition.modelEntity.MatrixModel;
 import org.wlld.nerveCenter.NerveManager;
 import org.wlld.nerveCenter.Normalization;
+import org.wlld.nerveEntity.BodyList;
 import org.wlld.nerveEntity.ModelParameter;
 import org.wlld.nerveEntity.SensoryNerve;
 import org.wlld.param.Cutting;
@@ -539,15 +540,18 @@ public class TempleConfig {
                 case Classifier.KNN:
                     if (knn != null) {
                         Map<Integer, List<Matrix>> listMap = knn.getFeatureMap();
-                        Map<Integer, List<List<Double>>> knnVector = new HashMap<>();
+                        List<BodyList> knnVector = new ArrayList<>();
                         for (Map.Entry<Integer, List<Matrix>> entry : listMap.entrySet()) {
                             List<Matrix> list = entry.getValue();
                             List<List<Double>> listFeature = new ArrayList<>();
+                            BodyList bodyList = new BodyList();
+                            bodyList.setLists(listFeature);
+                            bodyList.setType(entry.getKey());
                             for (Matrix matrix : list) {
                                 List<Double> list1 = MatrixOperation.rowVectorToList(matrix);
                                 listFeature.add(list1);
                             }
-                            knnVector.put(entry.getKey(), listFeature);
+                            knnVector.add(bodyList);
                         }
                         modelParameter.setKnnVector(knnVector);
                     }
@@ -662,11 +666,11 @@ public class TempleConfig {
                     nerveManager.insertModelParameter(modelParameter);
                     break;
                 case Classifier.KNN:
-                    Map<Integer, List<List<Double>>> knnVector = modelParameter.getKnnVector();
+                    List<BodyList> knnVector = modelParameter.getKnnVector();
                     if (knn != null && knnVector != null) {
-                        for (Map.Entry<Integer, List<List<Double>>> entry : knnVector.entrySet()) {
-                            List<List<Double>> featureList = entry.getValue();
-                            int type = entry.getKey();
+                        for (BodyList bodyList : knnVector) {
+                            int type = bodyList.getType();
+                            List<List<Double>> featureList = bodyList.getLists();
                             for (List<Double> list : featureList) {
                                 Matrix matrix = MatrixOperation.listToRowVector(list);
                                 knn.insertMatrix(matrix, type);

src/main/java/org/wlld/nerveEntity/BodyList.java

@@ -0,0 +1,24 @@
+package org.wlld.nerveEntity;
+
+import java.util.List;
+
+public class BodyList {
+    private int type;
+    private List<List<Double>> lists;
+
+    public int getType() {
+        return type;
+    }
+
+    public void setType(int type) {
+        this.type = type;
+    }
+
+    public List<List<Double>> getLists() {
+        return lists;
+    }
+
+    public void setLists(List<List<Double>> lists) {
+        this.lists = lists;
+    }
+}

src/main/java/org/wlld/nerveEntity/ModelParameter.java

@@ -23,15 +23,15 @@ public class ModelParameter {
     private Map<Integer, KBorder> borderMap = new HashMap<>();//边框距离模型
     private LvqModel lvqModel;//LVQ模型
     private Map<Integer, List<Double>> matrixK = new HashMap<>();//均值特征向量
-    private Map<Integer, List<List<Double>>> knnVector;//Knn模型
+    private List<BodyList> knnVector;//Knn模型
     private Frame frame;//先验边框
     private double dnnAvg;//
 
-    public Map<Integer, List<List<Double>>> getKnnVector() {
+    public List<BodyList> getKnnVector() {
         return knnVector;
     }
 
-    public void setKnnVector(Map<Integer, List<List<Double>>> knnVector) {
+    public void setKnnVector(List<BodyList> knnVector) {
         this.knnVector = knnVector;
     }
 

src/test/java/coverTest/FoodTest.java

@@ -1,6 +1,7 @@
 package coverTest;
 
 import com.alibaba.fastjson.JSON;
+import com.alibaba.fastjson.JSONObject;
 import org.wlld.MatrixTools.Matrix;
 import org.wlld.config.Classifier;
 import org.wlld.config.RZ;
@@ -19,7 +20,7 @@ import java.util.List;
 public class FoodTest {
 
     public static void main(String[] args) throws Exception {
-        //test();
+        test();
     }
 
     public static void one(double[] test, double[] right, double[] wrong) {
@@ -39,7 +40,7 @@ public class FoodTest {
 
     public static void test2(TempleConfig templeConfig) throws Exception {
         if (templeConfig == null) {
-            templeConfig = getTemple();
+            templeConfig = getTemple(null);
         }
         Picture picture = new Picture();
         List<Specifications> specificationsList = new ArrayList<>();
@@ -63,11 +64,11 @@ public class FoodTest {
         }
     }
 
-    public static TempleConfig getTemple() throws Exception {
+    public static TempleConfig getTemple(ModelParameter modelParameter) throws Exception {
         TempleConfig templeConfig = new TempleConfig();
-        templeConfig.isShowLog(true);//是否打印日志
+        //templeConfig.isShowLog(true);//是否打印日志
         Cutting cutting = templeConfig.getCutting();
-        Food food =templeConfig.getFood();
+        Food food = templeConfig.getFood();
         //切割
         cutting.setMaxRain(320);//切割阈值
         cutting.setTh(0.88);
@@ -83,12 +84,15 @@ public class FoodTest {
         food.setTimes(2);//聚类数据增强
         templeConfig.setClassifier(Classifier.KNN);
         templeConfig.init(StudyPattern.Cover_Pattern, true, 400, 400, 3);
+        if (modelParameter != null) {
+            templeConfig.insertModel(modelParameter);
+        }
         return templeConfig;
     }
 
     public static void test() throws Exception {
         Picture picture = new Picture();
-        TempleConfig templeConfig = getTemple();
+        TempleConfig templeConfig = getTemple(null);
         Operation operation = new Operation(templeConfig);
         List<Specifications> specificationsList = new ArrayList<>();
         Specifications specifications = new Specifications();
@@ -120,9 +124,12 @@ public class FoodTest {
             operation.colorStudy(threeChannelMatrix10, 10, specificationsList);
             System.out.println("=======================================" + i);
         }
-
-        templeConfig.finishStudy();
-        test2(templeConfig);
+        ModelParameter modelParameter = templeConfig.getModel();
+        String model = JSON.toJSONString(modelParameter);
+        System.out.println(model);
+        ModelParameter modelParameter1 = JSONObject.parseObject(model, ModelParameter.class);
+        //templeConfig.finishStudy();
+        test2(getTemple(modelParameter1));
     }
 
     public static void study() throws Exception {

src/test/java/coverTest/PicTest.java

@@ -1,8 +1,11 @@
 package coverTest;
 
+import com.alibaba.fastjson.JSON;
+import com.alibaba.fastjson.JSONObject;
 import org.wlld.Ma;
 import org.wlld.MatrixTools.Matrix;
 import org.wlld.MatrixTools.MatrixOperation;
+import org.wlld.ModelData;
 import org.wlld.config.Classifier;
 import org.wlld.config.RZ;
 import org.wlld.config.StudyPattern;
@@ -13,6 +16,7 @@ import org.wlld.imageRecognition.Operation;
 import org.wlld.imageRecognition.Picture;
 import org.wlld.imageRecognition.TempleConfig;
 import org.wlld.nerveCenter.NerveManager;
+import org.wlld.nerveEntity.ModelParameter;
 import org.wlld.nerveEntity.SensoryNerve;
 import org.wlld.tools.ArithUtil;
 
@@ -32,6 +36,13 @@ public class PicTest {
 
         //testImage(right, wrong, a, b);
         //test();
+        tm();
+    }
+
+    public static void tm() {
+        String model = ModelData.DATA4;
+        int index = model.indexOf("knnVector");
+
     }
 
     public static void test() throws Exception {//对图像进行识别测试