Knn算法智能识别验证码数字

#coding=utf-8
import urllib
import re
import time
import socket
#USER_AGENT='Mozilla/5.0 (X11;Ubuntu;Linux x86_64;rv:40.0)Gecko/20100101 Firefox/40.0'
#HEADERS='User-agent:'+USER_AGENT
#print HEADERS
def getHtml(url):
page = urllib.urlopen(url)
html = page.read()
return html

def Schedule(a, b, c):
'''
a:已经下载的数据块
b:数据库块的大小
c:远程文件的大小
'''
per = 100.0 * a * b / c
if per > 100:
per = 100
print('%.2f%%' % per)

def auto_down(url,filename,Schedule):
x=0
try:
urllib.urlretrieve(url,filename,Schedule)
except urllib.ContentTooShortError:
if x<5:
print 'Network conditions is not good.Reloading...%s' %x
auto_down(url, filename, Schedule)
x+=1
else:
print 'Download failed.Connecting to next image.'
return False
except socket.error:
if x<5:
print 'Socket error.Reloading...%s' %x
auto_down(url, filename, Schedule)
x+=1
else:
print 'Download failed.Connecting to next image.'
return False
'''else:
if x<5:
print 'Unknown error.Reloading...%s' %x
auto_down(url, filename, Schedule)
x+=1
else:
print 'Download failed.Connecting to next image.'
return False'''
return True

def getImg(html):
reg = r'src="(.+?\.jpg)" pic_ext'
imgre = re.compile(reg)
imglist = re.findall(imgre,html)
x = 1
success_num=0
failed_num=0
for imgurl in imglist:
print '=============Image No.%s=============' % x
rst=auto_down(imgurl,'C:/Joe_Workspace/reptile_workspace/jpg/%s.jpg' % x,Schedule)
print 'Image No.%s download finish.' % x
x+=1
if rst:
success_num+=1
else:
failed_num+=1
#time.sleep(2)
rst_val=success_num/(success_num+failed_num)*100
if rst_val ==100:
print "[result] All %s images have been downloaded successfully." %success_num
else:
print "[result] %s/%s images have been downloaded successfully." %success_num %(success_num+failed_num)
return imglist

html = getHtml("http://tieba.baidu.com/p/2460150866")

print getImg(html)

import java.awt.Color;
import java.awt.Font;
import java.awt.Graphics2D;
import java.awt.image.BufferedImage;
import java.io.File;
import java.io.FileNotFoundException;
import java.io.FileOutputStream;
import java.io.IOException;
import java.io.OutputStream;
import java.util.Random;

import javax.imageio.ImageIO;

//import org.junit.Test;

/**
* @author : Administrator
* @function :
*/
public class VerificationCode {
private int w = 32;
private int h = 32;
private String text;
private Random r = new Random();
public static String[] fontNames_all = {"Arial","BatangChe","Bell MT","Arial Narrow","Arial Rounded MT Bold","Bookman Old Style","Bookshelf Symbil 7","Calbri Light","Calibri","Arial Black","Batang","Bodoni MT Black"};
Color bgColor = new Color(255, 255, 255);
public static String[] fontNames=new String[1];;
public static String codes="";

public static void main(String[] args){
for (int num=0;num<10;num++){
for (int i=0;i<fontNames_all.length;i++){
fontNames[0]=fontNames_all[i];
codes=""+num;
test_fun(num,i);
}
}
}
/**
*
*/
//@Test
public static void test_fun(int num,int i) {
VerificationCode vc = new VerificationCode();
BufferedImage image = vc.getImage();
try {
VerificationCode.output(image, new FileOutputStream(new File(
"C:\\Joe_Workspace\\image\\"+num+"_"+i+".jpg")));
} catch (FileNotFoundException e) {
e.printStackTrace();
}
System.out.println(vc.getText());
}

/**
*
*/
public BufferedImage getImage() {
BufferedImage image = createImage();
Graphics2D g2 = (Graphics2D) image.getGraphics();
StringBuilder sb = new StringBuilder();

for (int i = 0; i < 1; ++i) {
String s = randomChar() + "";
sb.append(s);
float x = i * 1.0F * w / 4 +9;
g2.setFont(randomFont());
g2.setColor(randomColor());
g2.drawString(s, x, h - 7);
}

this.text = sb.toString();
//drawLine(image);
return image;

}

/**
* @return
*/
public String getText() {
return text;
}

/**
* @param image
* @param out
*
*/
public static void output(BufferedImage image, OutputStream out) {
try {
ImageIO.write(image, "jpeg", out);
} catch (IOException e) {
e.printStackTrace();
}
}

private void drawLine(BufferedImage image) {
Graphics2D g2 = (Graphics2D) image.getGraphics();
for (int i = 0; i < 3; ++i) {
int x1 = r.nextInt(w);
int y1 = r.nextInt(h);
int x2 = r.nextInt(w);
int y2 = r.nextInt(h);
g2.setColor(Color.BLUE);
g2.drawLine(x1, y1, x2, y2);
}
}

private Color randomColor() {
int red = r.nextInt(150);
int green = r.nextInt(150);
int blue = r.nextInt(150);
return new Color(0, 0, 0);
}

private Font randomFont() {
int index = r.nextInt(fontNames.length);
String fontName = fontNames[index];
int style = r.nextInt(4);
int size = r.nextInt(5) + 24;
return new Font(fontName, style, size);
}

private char randomChar() {
int index = r.nextInt(codes.length());
return codes.charAt(index);
}

private BufferedImage createImage() {
BufferedImage image = new BufferedImage(w, h,
BufferedImage.TYPE_INT_RGB);
Graphics2D g2 = (Graphics2D) image.getGraphics();
g2.setColor(this.bgColor);
g2.fillRect(0, 0, w, h);

return image;
}

}

from PIL import Image
import os
from os import listdir

def img2txt_func(img_path_1,txt_path_1):
fh=open(txt_path_1,'w')
im=Image.open(img_path_1)
fh=open(txt_path_1,'a')

width=im.size[0]
height=im.size[1]

for i in range(0,width):
for j in range(0,height):
cl=im.getpixel((j,i))
clall=cl[0]+cl[1]+cl[2]
if(clall==0):#black
fh.write("1")
else:
fh.write("0")
fh.write("\n")

fh.close()

img_path="c:/Joe_Workspace/images"
txt_path="c:/Joe_Workspace/traindata"
imgs=listdir(img_path)
for img in imgs:
#print img_path+"/"+os.path.basename(img)
#print txt_path+"/"+os.path.splitext(img)[0]+".txt"
img2txt_func(img_path+"/"+os.path.basename(img),txt_path+"/"+os.path.splitext(img)[0]+".txt")

from numpy import *
import operator
from os import listdir
import os

from numpy.matlib import zeros

def pow_func_2nd_arry(dif,sqnum,arr_len):
sqarr = zeros((len(dif),arr_len))
for i in range(0,len(dif)):
arr=[]
arrlist=mat(dif[i]).tolist()
#print arrlist[0][175]
for j in range(0,arr_len):
arr.append(int(arrlist[0][j])**sqnum)
sqarr[i,:]=arr
return sqarr

def pow_func_1nd_arry(dif,sqnum,arr_len):
sqarr = zeros((1,arr_len))
arrlist=mat(dif).tolist()
#print sqarr
#print arrlist[0][0]
#print arrlist[675][0]
#print arrlist[674][0]
for i in range(0,arr_len):
sqarr[:,i]=int(arrlist[i][0])**sqnum
return sqarr

def array2list(dif,arr_len):
list1=[]
arrlist = mat(dif).tolist()
for i in range(0,arr_len):
list1.append(int(arrlist[0][i]))
#print list1
return list1

def knn(k,testdata,traindata,labels):
traindatasize=traindata.shape[0]
dif=tile(testdata,(traindatasize,1))-traindata
#print dif[0][0]
sqdif=pow_func_2nd_arry(dif,2,1024)
sumsqdif=sqdif.sum(axis=1)
distance=pow_func_1nd_arry(sumsqdif,0.5,len(labels))
sortdistance=distance.argsort()
sortdis_list=array2list(sortdistance,len(labels))
#print sortdis_list
count={}
for i in range(0,k):
vote=labels[int(sortdis_list[i])]
count[vote]=count.get(vote,0)+1
sortcount=sorted(count.items(),key=operator.itemgetter(1),reverse=True)
return sortcount[0][0]
def data2array(fname):
arr=[]
fh=open(fname)
for i in range(0,32):
thisline=fh.readline()
for j in range(0,32):
arr.append(int(thisline[j]))
#print arr
return arr
def seplabel(fname):
filestr=fname.split(".")[0]
label=int(filestr.split("_")[0])
return label
def traindata(train_data_path):
labels=[]
trainfile=listdir(train_data_path)
num=len(trainfile)
trainarr=zeros((num,1024))
for i in range(0,num):
thisname=trainfile[i]
thislabel=seplabel(thisname)
labels.append(thislabel)
trainarr[i,:]=data2array(train_data_path+thisname)
return trainarr,labels

test_data_path="c:/Joe_Workspace/testdata/"
train_data_path="c:/Joe_Workspace/traindata/"
trainarr,labels=traindata(train_data_path)
testfiles=listdir(test_data_path)
pass_count=0
for thistestfile in testfiles:
testarr=data2array(test_data_path+os.path.basename(thistestfile))
rst=knn(5,testarr,trainarr,labels)
print os.path.basename(thistestfile)+":"+str(seplabel(thistestfile))+"?="+str(rst)
if str(seplabel(thistestfile))==str(rst):
pass_count+=1
print "[Pass Rate:] %s%%" %((pass_count*100)/len(testfiles))