基于BP神经网络的人脸识别(java源码).zip

import java.awt.image.BufferedImage; import java.io.File; import java.io.IOException; import java.util.Scanner; import javax.imageio.ImageIO; public class ANN { static int B = 16; // 输入层神经元个数 static int N = 2*B*B*2; // 隐含层神经元个数 static int L = B*B; // 输出层神经元个数 static int M = 16; // 进度控制产生 static double yiphxir = 0.001; // 学习率 static double arph = 0.2; static double a = -1.0; static double max = 255; // 输入层到隐含层的权值 static double[][] V = new double[N][L]; // 隐含层到输出层的权值 static double[][] W = new double[L][M]; // 隐含层的阈值 static double[] fai = new double[L]; // 输出层的阈值 static double[] sita = new double[M]; static double[][] deltaW = new double[L][M]; static double[] deltaSita = new double[M]; static double[][] deltaV = new double[N][L]; static double[] deltaFai = new double[L]; static double[] FE = new double[M]; static double[] getImagePixel(String image) { File file = new File(image); BufferedImage bi = null; try { bi = ImageIO.read(file); } catch (IOException e) { e.printStackTrace(); } int width = bi.getWidth()/2; int height = bi.getHeight()/2; double[] pixel = new double[N]; int cnt = 0; for(int y = height-B; y < height+B; y++) { for(int x = width-B; x < width+B; x++) { int t = bi.getRGB(x, y); t = (t & 0xff); pixel[cnt] = t/max; cnt++; } } return pixel; } static double FS(double x){ return 1.0/(1.0+Math.exp(a*x)); } static void init(){ for(int i=0; i<N; i++){ for(int j=0; j<L; j++){ V[i][j] = Math.random()*2.0-1.0; } } for(int j=0; j<L; j++){ for(int k=1; k<M; k++){ W[j][k] = Math.random()*2.0-1.0; } } for(int j=0; j<L; j++){ fai[j] = Math.random()*2.0-1.0; } for(int k=1; k<M; k++){ sita[k] = Math.random()*2.0-1.0; } } static boolean trainBP(double[] X, int[] D){ double[] H = new double[L]; for(int j=0; j<L; j++){ double derta = 0.0; for(int i=0; i<N; i++){ derta += X[i]*V[i][j]; } // System.out.print("derta"+Double.toString(derta)); // System.out.println(" derta-fai="+Double.toString(derta-fai[j])); H[j] = FS(derta+fai[j]); // System.out.println(Double.toString(H[j])+" "); } double[] Y = new double[M]; for(int k=1; k<M; k++){ double derta = 0.0; for(int j=0; j<L; j++){ derta += H[j]*W[j][k]; } // System.out.print("derta"+Double.toString(derta)); // System.out.println(" derta-sita="+Double.toString(derta-sita[k])); Y[k] = FS(derta+sita[k]); // System.out.print(Double.toString(Y[k])+" "); } // System.out.println(); double[] deltaK = new double[M]; double E = 0.0; for(int k=1; k<M; k++){ E += (D[k] - Y[k])*(D[k] - Y[k]); deltaK[k] = (D[k]-Y[k])*Y[k]*(1-Y[k]); } // System.out.print("E="); // System.out.println(E/2); if(E/2 < yiphxir) return true; double[] deltaJ = new double[L]; for(int j=0; j<L; j++){ double beta = 0.0; for(int k=1; k<M; k++){ beta += deltaK[k]*W[j][k]; } deltaJ[j] = H[j]*(1-H[j])*beta; } for(int j=0; j<L; j++){ for(int k=1; k<M; k++){ deltaW[j][k] = arph*deltaK[k]*H[j]; // deltaW[j][k] = (arph/(1+L))*(deltaW[j][k]+1)*deltaK[k]*H[j]; W[j][k] += deltaW[j][k]; } } for(int k=1; k<M; k++){ deltaSita[k] = arph*deltaK[k]; // deltaSita[k] = (arph/(1+L))*(detaSitla[k]+1)*deltaK[k]; sita[k] += deltaSita[k]; } for(int i=0; i<N; i++){ for(int j=0; j<L; j++){ deltaV[i][j] = arph*deltaJ[j]*X[i]; // deltaV[i][j] = (arph/(1+N))*(deltaV[i][j]+1)*deltaJ[j]*X[i]; V[i][j] += deltaV[i][j]; } } for(int j=0; j<L; j++){ deltaFai[j] = arph*deltaJ[j]; // deltaFai[j] = (arph/(1+N))*(deltaFai[j]+1)*deltaJ[j]; fai[j] += deltaFai[j]; } return false; } static int BP(double[] X){ int ans = 0; double[] H = new double[L]; for(int j=0; j<L; j++){ double derta = 0.0; for(int i=0; i<N; i++){ derta += X[i]*V[i][j]; } H[j] = FS(derta-fai[j]); } double[] Y = new double[M]; for(int k=1; k<M; k++){ double derta = 0.0; for(int j=0; j<L; j++){ derta += H[j]*W[j][k]; } Y[k] = FS(derta-sita[k]); } double min = Double.MAX_VALUE; for(int n=1; n<M; n++){ double E = 0.0; int[] D = new int[M]; D[n] = 1; for(int k=1; k<M; k++){ E += Math.abs((D[k] - Y[k])*(D[k] - Y[k])); } FE[n] = 1.0/Math.exp(E/2.0); if(E/2 < min){ min = E/2; ans = n; } } return ans; } @SuppressWarnings("resource") public static void main(String[] args) { init(); int temp = 0; while(temp < 100){ int t = 1; while(t <= 11){ int ca = 1; while(ca < M){ // System.out.println(t); // System.out.println(ca); String imagePath; if(ca >= 10){ // imagePath = "E:\\Java\\AAII\\src\\image\\subject01_10.bmp"; imagePath = "E:\\Java\\AAII\\src\\image\\"+"subject"+Integer.toString(ca)+"_"+Integer.toString(t)+".bmp"; } else imagePath = "E:\\Java\\AAII\\src\\image\\"+"subject0"+Integer.toString(ca)+"_"+Integer.toString(t)+".bmp"; double[] X = getImagePixel(imagePath); int[] D = new int[M]; D[ca] = 1; boolean flag = trainBP(X, D); if(flag) break; ca++; } t++; } temp++; } Scanner in = new Scanner(System.in); while(true){ System.out.println("请输入subject(t1)和_(t2):"); String t1 = in.next(); String t2 = in.next(); String imagePath = "E:\\Java\\AAII\\src\\image\\"+"subject"+t1+"_"+t2+".bmp"; double[] X = getImagePixel(imagePath); int ans = BP(X); System.out.println("(subject01~subject15)的匹配率如下："); for(int i=1; i<M; i++){ System.out.println("subject"+Integer.toString(i)+"："+String.format("%g", FE[i]*100)+"%"); } System.out.println(); System.out.print("综合结果为subject"); System.out.println(ans); System.out.println(); } } }