diff --git a/.idea/compiler.xml b/.idea/compiler.xml
index 6aa88ff..d280c68 100644
--- a/.idea/compiler.xml
+++ b/.idea/compiler.xml
@@ -6,8 +6,8 @@
-
+
diff --git a/src/main/java/org/wlld/imageRecognition/KMatrix.java b/src/main/java/org/wlld/imageRecognition/KMatrix.java
deleted file mode 100644
index 6a2ff48..0000000
--- a/src/main/java/org/wlld/imageRecognition/KMatrix.java
+++ /dev/null
@@ -1,64 +0,0 @@
-package org.wlld.imageRecognition;
-
-import org.wlld.MatrixTools.Matrix;
-import org.wlld.MatrixTools.MatrixOperation;
-import org.wlld.tools.ArithUtil;
-
-/**
- * @author lidapeng
- * @description K均值聚类矩阵
- * @date 9:05 上午 2020/2/1
- */
-public class KMatrix {
- private Matrix sigmaMatrix;//矩阵和
- private int nub;//加和次数
- private boolean isFinish = false;//是否结算
-
- KMatrix(int x, int y) {
- sigmaMatrix = new Matrix(x, y);
- }
-
- public boolean isFinish() {
- return isFinish;
- }
-
- public void setFinish(boolean finish) {
- isFinish = finish;
- }
-
- public Matrix getSigmaMatrix() {
- return sigmaMatrix;
- }
-
- public double getEDist(Matrix matrix) throws Exception {//返回欧式距离
- if (isFinish && matrix.getX() == sigmaMatrix.getX()
- && matrix.getY() == sigmaMatrix.getY()) {
- double sigma = 0;
- for (int i = 0; i < matrix.getX(); i++) {
- for (int j = 0; j < matrix.getY(); j++) {
- double sub = ArithUtil.sub(matrix.getNumber(i, j), sigmaMatrix.getNumber(i, j));
- sigma = ArithUtil.add(Math.pow(sub, 2), sigma);
- }
- }
- sigma = Math.sqrt(sigma);
- return sigma;
- } else {
- throw new Exception("K is not finish or matrix not equal");
- }
- }
-
- public void addMatrix(Matrix matrix) throws Exception {
- sigmaMatrix = MatrixOperation.add(sigmaMatrix, matrix);
- nub++;
- }
-
- public void getK() throws Exception {//结算K均值
- if (nub != 0) {
- double aNub = ArithUtil.div(1, nub);
- MatrixOperation.mathMul(sigmaMatrix, aNub);
- isFinish = true;
- } else {
- throw new Exception("not value");
- }
- }
-}
diff --git a/src/main/java/org/wlld/imageRecognition/Operation.java b/src/main/java/org/wlld/imageRecognition/Operation.java
index 6519382..0733046 100644
--- a/src/main/java/org/wlld/imageRecognition/Operation.java
+++ b/src/main/java/org/wlld/imageRecognition/Operation.java
@@ -135,9 +135,9 @@ public class Operation {//进行计算
intoNerve2(eventId, frameBody.getMatrix(), templeConfig.getConvolutionNerveManager().getSensoryNerves(),
false, -1, matrixBack);
Matrix myMatrix = matrixBack.getMatrix();
- //卷积层输出即边框回归的输入的特征向量
+ //卷积层输出即边框回归的输入的特征向量 TODO 这地有BUG 要改
frameBody.setEndMatrix(myMatrix);
- int id = getClassificationId(myMatrix);
+ int id = getClassificationId2(myMatrix);
frameBody.setId(id);
}
return toPosition(frameBodies, frame.getWidth(), frame.getHeight());
@@ -186,6 +186,21 @@ public class Operation {//进行计算
return map;
}
+ private Matrix getBoxMatrix(Matrix matrix, Map boxMap) throws Exception {
+ Matrix positionMatrix = null;
+ double endDist = 0;
+ for (Map.Entry entry : boxMap.entrySet()) {
+ Box box = entry.getValue();
+ Matrix boxMatrix = box.getMatrix();
+ double dist = MatrixOperation.getEDist(matrix, boxMatrix);
+ if (endDist == 0 || dist < endDist) {
+ endDist = dist;
+ positionMatrix = box.getMatrixPosition();
+ }
+ }
+ return positionMatrix;
+ }
+
//获得预测边框
private void getBox(FrameBody frameBody, int width, int height) throws Exception {
if (templeConfig.isBoxReady()) {
@@ -193,24 +208,16 @@ public class Operation {//进行计算
int id = frameBody.getId();
int x = frameBody.getX();
int y = frameBody.getY();
- Map borderBodyMap = templeConfig.getBorderBodyMap();
- BorderBody borderBody = borderBodyMap.get(id);
- //都是列向量，将参数转化为行向量最后再加1
- Matrix xw = borderBody.getxW();
- Matrix yw = borderBody.getyW();
- Matrix hw = borderBody.gethW();
- Matrix ww = borderBody.getwW();
+ KClustering kClustering = templeConfig.getkClusteringMap().get(id);
+ Map boxMap = kClustering.getPositionMap();
//将矩阵化为向量
matrix = MatrixOperation.matrixToVector(matrix, true);
- //最后加一层池化
- matrix = MatrixOperation.getPoolVector(matrix);
- //将参数矩阵的末尾填1
- matrix = MatrixOperation.push(matrix, 1, true);
+ Matrix positionMatrix = getBoxMatrix(matrix, boxMap);
//锚点坐标及长宽预测值
- double tx = MatrixOperation.mulMatrix(matrix, xw).getNumber(0, 0);
- double ty = MatrixOperation.mulMatrix(matrix, yw).getNumber(0, 0);
- double th = MatrixOperation.mulMatrix(matrix, hw).getNumber(0, 0);
- double tw = MatrixOperation.mulMatrix(matrix, ww).getNumber(0, 0);
+ double tx = positionMatrix.getNumber(0, 0);
+ double ty = positionMatrix.getNumber(0, 1);
+ double th = positionMatrix.getNumber(0, 3);
+ double tw = positionMatrix.getNumber(0, 2);
//修正相对位置
double realX = ArithUtil.add(ArithUtil.mul(tx, height), x);
double realY = ArithUtil.add(ArithUtil.mul(ty, width), y);
@@ -304,22 +311,6 @@ public class Operation {//进行计算
return id;
}
- private int getClassificationId(Matrix myMatrix) throws Exception {
- int id = 0;
- double distEnd = 0;
- Map kMatrixMap = templeConfig.getkMatrixMap();
- for (Map.Entry entry : kMatrixMap.entrySet()) {
- int key = entry.getKey();
- KMatrix kMatrix = entry.getValue();
- double dist = kMatrix.getEDist(myMatrix);
- if (distEnd == 0 || dist < distEnd) {
- id = key;
- distEnd = dist;
- }
- }
- return id;
- }
-
private List sub(Matrix matrix) throws Exception {//
List list = new ArrayList<>();
int x = matrix.getX() - 1;
diff --git a/src/main/java/org/wlld/imageRecognition/TempleConfig.java b/src/main/java/org/wlld/imageRecognition/TempleConfig.java
index 1b73514..1414069 100644
--- a/src/main/java/org/wlld/imageRecognition/TempleConfig.java
+++ b/src/main/java/org/wlld/imageRecognition/TempleConfig.java
@@ -5,9 +5,7 @@ import org.wlld.MatrixTools.MatrixOperation;
import org.wlld.config.StudyPattern;
import org.wlld.function.ReLu;
import org.wlld.function.Sigmod;
-import org.wlld.imageRecognition.border.BorderBody;
-import org.wlld.imageRecognition.border.Frame;
-import org.wlld.imageRecognition.border.LVQ;
+import org.wlld.imageRecognition.border.*;
import org.wlld.nerveCenter.NerveManager;
import org.wlld.nerveEntity.ModelParameter;
import org.wlld.nerveEntity.SensoryNerve;
@@ -29,14 +27,18 @@ public class TempleConfig {
private int classificationNub = 1;//分类的数量
private int studyPattern;//学习模式
private boolean isHavePosition = false;//是否需要锁定物体位置
- private Map borderBodyMap = new HashMap<>();//border特征集合
- private Map kMatrixMap = new HashMap<>();//K均值矩阵集合
private LVQ lvq;
private Frame frame;//先验边框
private double th = 0.6;//标准阈值
private boolean boxReady = false;//边框已经学习完毕
private double iouTh = 0.5;//IOU阈值
private int lvqNub = 50;//lvq循环次数，默认50
+ //边框聚类集合
+ private Map kClusteringMap = new HashMap<>();
+
+ public Map getkClusteringMap() {
+ return kClusteringMap;
+ }
public int getLvqNub() {
return lvqNub;
@@ -74,20 +76,6 @@ public class TempleConfig {
this.frame = frame;
}
- public Map getBorderBodyMap() {
- return borderBodyMap;
- }
-
- public Map getkMatrixMap() {
- return kMatrixMap;
- }
-
- public void clustering() throws Exception {//进行聚类结算
- for (Map.Entry kMatrixEntry : kMatrixMap.entrySet()) {
- kMatrixEntry.getValue().getK();
- }
- }
-
public void startLvq() throws Exception {//进行量化
lvq.start();
}
@@ -96,34 +84,15 @@ public class TempleConfig {
return lvq;
}
- private void border(BorderBody borderBody) throws Exception {
- Matrix parameter = borderBody.getX();//参数矩阵
- Matrix tx = borderBody.getTx();
- Matrix ty = borderBody.getTy();
- Matrix th = borderBody.getTh();
- Matrix tw = borderBody.getTw();
- borderBody.setxW(MatrixOperation.getLinearRegression(parameter, tx));
- borderBody.setyW(MatrixOperation.getLinearRegression(parameter, ty));
- borderBody.setwW(MatrixOperation.getLinearRegression(parameter, tw));
- borderBody.sethW(MatrixOperation.getLinearRegression(parameter, th));
- boxReady = true;
- }
-
public void boxStudy() throws Exception {//边框回归 学习结束之后最后进行调用
- if (borderBodyMap.size() > 0) {
- for (Map.Entry entry : borderBodyMap.entrySet()) {
- border(entry.getValue());
+ if (isHavePosition) {
+ for (Map.Entry entry : kClusteringMap.entrySet()) {
+ entry.getValue().start();
}
- } else {
- throw new Exception("boder not study");
}
}
- public void setBorderBodyMap(Map borderBodyMap) {
- this.borderBodyMap = borderBodyMap;
- }
-
public NerveManager getNerveManager() {
return nerveManager;
}
@@ -152,6 +121,11 @@ public class TempleConfig {
, int classificationNub) throws Exception {//初始化配置模板
this.classificationNub = classificationNub;
this.studyPattern = studyPattern;
+ if (isHavePosition) {
+ for (int i = 1; i < classificationNub + 1; i++) {
+ kClusteringMap.put(i, new KClustering(20));
+ }
+ }
switch (studyPattern) {
case StudyPattern.Speed_Pattern://速度学习模式
initModelVision(initPower, width, height);
@@ -195,10 +169,8 @@ public class TempleConfig {
//加载各识别分类的期望矩阵
matrixMap.put(0, new Matrix(height, width));
double nub = 10;//每个分类期望参数的跨度
- kMatrixMap.put(0, new KMatrix(height, width));
for (int k = 0; k < classificationNub; k++) {
Matrix matrix = new Matrix(height, width);//初始化期望矩阵
- kMatrixMap.put(k + 1, new KMatrix(height, width));
double t = (k + 1) * nub;//期望矩阵的分类参数数值
for (int i = 0; i < height; i++) {//给期望矩阵注入期望参数
for (int j = 0; j < width - 1; j++) {
@@ -241,19 +213,13 @@ public class TempleConfig {
ModelParameter modelParameter1 = convolutionNerveManager.getModelParameter();
modelParameter.setDymNerveStudies(modelParameter1.getDymNerveStudies());
modelParameter.setDymOutNerveStudy(modelParameter1.getDymOutNerveStudy());
- Map> matrixMap = new HashMap<>();
- for (Map.Entry entry : kMatrixMap.entrySet()) {
- List list = getFeatureList(entry.getValue().getSigmaMatrix());
- matrixMap.put(entry.getKey(), list);
- }
- modelParameter.setkMatrixList(matrixMap);
+
} else if (studyPattern == StudyPattern.Speed_Pattern) {
ModelParameter modelParameter1 = nerveManager.getModelParameter();
modelParameter.setDepthNerves(modelParameter1.getDepthNerves());
modelParameter.setOutNevers(modelParameter1.getOutNevers());
}
if (isHavePosition) {//存在边框学习模型参数
- modelParameter.setBorderBodyMap(borderBodyMap);
modelParameter.setFrame(frame);
}
return modelParameter;
@@ -293,24 +259,10 @@ public class TempleConfig {
public void insertModel(ModelParameter modelParameter) throws Exception {
if (studyPattern == StudyPattern.Accuracy_Pattern) {
convolutionNerveManager.insertModelParameter(modelParameter);
- Map> kMatrixs = modelParameter.getkMatrixList();
- if (kMatrixs != null && kMatrixs.size() == kMatrixMap.size()) {
- for (Map.Entry entry : kMatrixMap.entrySet()) {
- KMatrix kMatrix = entry.getValue();
- insertKMatrix(kMatrix.getSigmaMatrix(), kMatrixs.get(entry.getKey()));
- kMatrix.setFinish(true);
- }
- }
} else if (studyPattern == StudyPattern.Speed_Pattern) {
nerveManager.insertModelParameter(modelParameter);
}
Frame frame = modelParameter.getFrame();
- Map borderBodyMap = modelParameter.getBorderBodyMap();
- if (frame != null && borderBodyMap != null && borderBodyMap.size() > 0) {
- isHavePosition = true;
- this.frame = frame;
- this.borderBodyMap = borderBodyMap;
- }
}
public void setCutThreshold(double cutThreshold) {
diff --git a/src/main/java/org/wlld/imageRecognition/border/Border.java b/src/main/java/org/wlld/imageRecognition/border/Border.java
index fcb12ee..e964625 100644
--- a/src/main/java/org/wlld/imageRecognition/border/Border.java
+++ b/src/main/java/org/wlld/imageRecognition/border/Border.java
@@ -48,51 +48,23 @@ public class Border {
public void end(Matrix matrix, int id) throws Exception {//长宽
height = maxX - minX;
width = maxY - minY;
- Map borderBodyMap = templeConfig.getBorderBodyMap();
- BorderBody borderBody = borderBodyMap.get(id);
- if (borderBody == null) {
- borderBody = new BorderBody();
- borderBodyMap.put(id, borderBody);
- }
- //拿到参数矩阵
- Matrix matrixX = borderBody.getX();
- Matrix matrixTx = borderBody.getTx();
- Matrix matrixTy = borderBody.getTy();
- Matrix matrixTw = borderBody.getTw();
- Matrix matrixTh = borderBody.getTh();
+ KClustering kClustering = templeConfig.getkClusteringMap().get(id);
+ Matrix positionMatrix = new Matrix(1, 4);
//多元线性回归的四个输出值
double tx = ArithUtil.div(minX, modelHeight);
double ty = ArithUtil.div(minY, modelWidth);
double tw = Math.log(ArithUtil.div(width, modelWidth));
double th = Math.log(ArithUtil.div(height, modelHeight));
+ Box box = new Box();
//进行参数汇集 矩阵转化为行向量
matrix = MatrixOperation.matrixToVector(matrix, true);
- //最后给一层池化层
- matrix = MatrixOperation.getPoolVector(matrix);
- //将参数矩阵的末尾填1
- matrix = MatrixOperation.push(matrix, 1, true);
- if (matrixX == null) {//如果是第一次直接赋值
- matrixX = matrix;
- matrixTx = new Matrix(1, 1);
- matrixTy = new Matrix(1, 1);
- matrixTw = new Matrix(1, 1);
- matrixTh = new Matrix(1, 1);
- matrixTx.setNub(0, 0, tx);
- matrixTy.setNub(0, 0, ty);
- matrixTw.setNub(0, 0, tw);
- matrixTh.setNub(0, 0, th);
- } else {//将新的参数矩阵添加到原来的末尾
- matrixX = MatrixOperation.pushVector(matrixX, matrix, true);
- matrixTx = MatrixOperation.push(matrixTx, tx, false);
- matrixTy = MatrixOperation.push(matrixTy, ty, false);
- matrixTw = MatrixOperation.push(matrixTw, tw, false);
- matrixTh = MatrixOperation.push(matrixTh, th, false);
- }
- borderBody.setX(matrixX);
- borderBody.setTh(matrixTh);
- borderBody.setTw(matrixTw);
- borderBody.setTx(matrixTx);
- borderBody.setTy(matrixTy);
+ positionMatrix.setNub(0, 0, tx);
+ positionMatrix.setNub(0, 1, ty);
+ positionMatrix.setNub(0, 2, tw);
+ positionMatrix.setNub(0, 3, th);
+ box.setMatrix(matrix);
+ box.setMatrixPosition(positionMatrix);
+ kClustering.setMatrixList(box);
}
}
diff --git a/src/main/java/org/wlld/imageRecognition/border/BorderBody.java b/src/main/java/org/wlld/imageRecognition/border/BorderBody.java
deleted file mode 100644
index c80e67a..0000000
--- a/src/main/java/org/wlld/imageRecognition/border/BorderBody.java
+++ /dev/null
@@ -1,93 +0,0 @@
-package org.wlld.imageRecognition.border;
-
-import org.wlld.MatrixTools.Matrix;
-
-/**
- * @author lidapeng
- * @description
- *
- * @date 8:49 上午 2020/1/24
- */
-public class BorderBody {
- private Matrix xW;//平移X权重
- private Matrix yW;//平移Y权重
- private Matrix wW;//缩放宽度权重
- private Matrix hW;//缩放高度权重
- private Matrix x;//参数矩阵
- private Matrix tx;//X轴偏移量
- private Matrix ty;//Y轴偏移量
- private Matrix tw;//W缩放量
- private Matrix th;//H缩放量
-
- public Matrix getxW() {
- return xW;
- }
-
- public void setxW(Matrix xW) {
- this.xW = xW;
- }
-
- public Matrix getyW() {
- return yW;
- }
-
- public void setyW(Matrix yW) {
- this.yW = yW;
- }
-
- public Matrix getwW() {
- return wW;
- }
-
- public void setwW(Matrix wW) {
- this.wW = wW;
- }
-
- public Matrix gethW() {
- return hW;
- }
-
- public void sethW(Matrix hW) {
- this.hW = hW;
- }
-
- public Matrix getX() {
- return x;
- }
-
- public void setX(Matrix x) {
- this.x = x;
- }
-
- public Matrix getTx() {
- return tx;
- }
-
- public void setTx(Matrix tx) {
- this.tx = tx;
- }
-
- public Matrix getTy() {
- return ty;
- }
-
- public void setTy(Matrix ty) {
- this.ty = ty;
- }
-
- public Matrix getTw() {
- return tw;
- }
-
- public void setTw(Matrix tw) {
- this.tw = tw;
- }
-
- public Matrix getTh() {
- return th;
- }
-
- public void setTh(Matrix th) {
- this.th = th;
- }
-}
diff --git a/src/main/java/org/wlld/imageRecognition/border/Box.java b/src/main/java/org/wlld/imageRecognition/border/Box.java
index fa6b630..ea6929f 100644
--- a/src/main/java/org/wlld/imageRecognition/border/Box.java
+++ b/src/main/java/org/wlld/imageRecognition/border/Box.java
@@ -9,7 +9,7 @@ import org.wlld.MatrixTools.Matrix;
*/
public class Box {
private Matrix matrix;//特征向量
- private Matrix matrixFather;//坐标向量
+ private Matrix matrixPosition;//坐标向量
public Matrix getMatrix() {
return matrix;
@@ -19,11 +19,11 @@ public class Box {
this.matrix = matrix;
}
- public Matrix getMatrixFather() {
- return matrixFather;
+ public Matrix getMatrixPosition() {
+ return matrixPosition;
}
- public void setMatrixFather(Matrix matrixFather) {
- this.matrixFather = matrixFather;
+ public void setMatrixPosition(Matrix matrixPosition) {
+ this.matrixPosition = matrixPosition;
}
}
diff --git a/src/main/java/org/wlld/imageRecognition/border/KClustering.java b/src/main/java/org/wlld/imageRecognition/border/KClustering.java
index eefa921..03be10d 100644
--- a/src/main/java/org/wlld/imageRecognition/border/KClustering.java
+++ b/src/main/java/org/wlld/imageRecognition/border/KClustering.java
@@ -17,13 +17,14 @@ public class KClustering {
private int speciesQuantity;//种类数量
private Matrix[] matrices;//均值K
private Map> clusterMap = new HashMap<>();//簇
+ private Map positionMap = new HashMap<>();
+ private boolean isReady = false;
- public Matrix[] getMatrices() {
- return matrices;
- }
-
- public Map> getClusterMap() {
- return clusterMap;
+ public Map getPositionMap() throws Exception {
+ if (!isReady) {
+ throw new Exception("not ready");
+ }
+ return positionMap;
}
public KClustering(int speciesQuantity) {
@@ -76,6 +77,29 @@ public class KClustering {
return matrices2;
}
+ private Matrix averagePosition(List boxes) throws Exception {
+ double nub = ArithUtil.div(1, boxes.size());
+ Matrix matrix = new Matrix(1, 4);
+ for (Box box : boxes) {
+ matrix = MatrixOperation.add(matrix, box.getMatrixPosition());
+ }
+ MatrixOperation.mathMul(matrix, nub);
+ return matrix;
+ }
+
+ private void position() throws Exception {
+ for (Map.Entry> entry : clusterMap.entrySet()) {
+ List boxList = entry.getValue();
+ int key = entry.getKey();
+ Box box = new Box();
+ Matrix position = averagePosition(boxList);
+ Matrix kMatrix = matrices[key];
+ box.setMatrix(kMatrix);
+ box.setMatrixPosition(position);
+ positionMap.put(key, box);
+ }
+ }
+
private void clear() {
for (Map.Entry> entry : clusterMap.entrySet()) {
entry.getValue().clear();
@@ -116,7 +140,8 @@ public class KClustering {
while (!isEqual);
//聚类结束，进行坐标均值矩阵计算
System.out.println("聚类循环次数：" + nub);
-
+ position();
+ isReady = true;
} else {
throw new Exception("matrixList number less than 2");
}
diff --git a/src/main/java/org/wlld/nerveEntity/ModelParameter.java b/src/main/java/org/wlld/nerveEntity/ModelParameter.java
index cf3eea8..6bf5b29 100644
--- a/src/main/java/org/wlld/nerveEntity/ModelParameter.java
+++ b/src/main/java/org/wlld/nerveEntity/ModelParameter.java
@@ -1,8 +1,5 @@
package org.wlld.nerveEntity;
-import org.wlld.MatrixTools.Matrix;
-import org.wlld.imageRecognition.KMatrix;
-import org.wlld.imageRecognition.border.BorderBody;
import org.wlld.imageRecognition.border.Frame;
import java.util.ArrayList;
@@ -21,26 +18,8 @@ public class ModelParameter {
private List outNevers = new ArrayList<>();//输出神经元
private List dymNerveStudies = new ArrayList<>();//动态神经元隐层
private DymNerveStudy dymOutNerveStudy = new DymNerveStudy();//动态神经元输出层
- private Map borderBodyMap = new HashMap<>();//border特征集合
- private Map> kMatrixList = new HashMap<>();//K均值矩阵集合
private Frame frame;//先验边框
- public Map> getkMatrixList() {
- return kMatrixList;
- }
-
- public void setkMatrixList(Map> kMatrixList) {
- this.kMatrixList = kMatrixList;
- }
-
- public Map getBorderBodyMap() {
- return borderBodyMap;
- }
-
- public void setBorderBodyMap(Map borderBodyMap) {
- this.borderBodyMap = borderBodyMap;
- }
-
public Frame getFrame() {
return frame;
}
diff --git a/src/test/java/org/wlld/MatrixTest.java b/src/test/java/org/wlld/MatrixTest.java
index fbb7cf0..2469bf4 100644
--- a/src/test/java/org/wlld/MatrixTest.java
+++ b/src/test/java/org/wlld/MatrixTest.java
@@ -2,9 +2,6 @@ package org.wlld;
import org.wlld.MatrixTools.Matrix;
import org.wlld.MatrixTools.MatrixOperation;
-import org.wlld.imageRecognition.border.BorderBody;
-
-import java.util.Random;
/**
* @author lidapeng