from numpy import * import operator from os import listdir #从列方向扩展 #tile(a,(size,1)) def knn(k,testdata,traindata,labels):     traindatasize=traindata.shape[0]     dif=tile(testdata,(traindatasize,1))-traindata     sqdif=dif**2     sumsqdif=sqdif.sum(axis=1)     distance=sumsqdif**0.5     sortdistance=distance.argsort()     count={}     for i in range(0,k):         vote=labels[sortdistance[i]]         count[vote]=count.get(vote,0)+1     sortcount=sorted(count.items(),key=operator.itemgetter(1),reverse=True)     return sortcount[0][0] #图片处理 #先将所有图片转为固定宽高，比如32*32，然后再转为文本 #pillow from PIL import Image im=Image.open("C:/Users/Administrator/Desktop/33.png") fh=open("C:/Users/Administrator/Desktop/33.txt","a") #im.save("C:/Users/me/Pictures/weixin.bmp") width=im.size[0] height=im.size[1] #k=im.getpixel((1,9)) #print(k) for i in range(0,width):     for j in range(0,height):         cl=im.getpixel((i,j))         clall=cl[0]+cl[1]+cl[2]         if(clall==0):             #黑色             fh.write("1")         else:             fh.write("0")     fh.write("\n") fh.close() #加载数据 def datatoarray(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]))     return arr arr1=datatoarray("E:/m/others/traindata/0_4.txt") #建立一个函数取文件名前缀 def seplabel(fname):     filestr=fname.split(".")[0]     label=int(filestr.split("_")[0])     return label #建立训练数据 def traindata():     labels=[]     trainfile=listdir("E:/m/others/traindata")     num=len(trainfile)     #长度1024（列），每一行存储一个文件     #用一个数组存储所有训练数据，行：文件总数，列：1024     trainarr=zeros((num,1024))     for i in range(0,num):         thisfname=trainfile[i]         thislabel=seplabel(thisfname)         labels.append(thislabel)         trainarr[i,:]=datatoarray("traindata/"+thisfname)     return trainarr,labels #用测试数据调用KNN算法去测试，看是否能够准确识别 def datatest():     trainarr,labels=traindata()     testlist=listdir("testdata")     tnum=len(testlist)     for i in range(0,tnum):         thistestfile=testlist[i]         testarr=datatoarray("testdata/"+thistestfile)         rknn=knn(3,testarr,trainarr,labels)         print(rknn) #datatest() #抽某一个测试文件出来进行试验 trainarr,labels=traindata() thistestfile="33.txt" testarr=datatoarray("C:/Users/Administrator/Desktop/"+thistestfile) rknn=knn(3,testarr,trainarr,labels) print(rknn) ******************************************************************************************

from PIL import Image im=Image.open("C:/Users/Administrator/Desktop/33.png") #im.save("C:/Users/Administrator/Desktop/33.bmp") fh=open("C:/Users/Administrator/Desktop/33.txt","a") pic_size=im.size width=im.size[0] height=im.size[1] print(pic_size) print("  width:"+str(width)) print ("  height:"+str(height)) px_color=im.getpixel((0,9)) print(px_color) from os import listdir listdir_name=listdir("E:/m/others/traindata")#得到文件夹下的所有文件名 print(listdir_name) from numpy import * zero=zeros((2,5)) print (zero)