import cv2 
import numpy as np 
from matplotlib import pyplot as plt 
from PIL import Image
 
img=cv2.imread('0002.jpg') #读取图片，装换为可运算的数组
GrayImage=cv2.cvtColor(img,cv2.COLOR_BGR2GRAY)  #将BGR图转为灰度图
ret,thresh1=cv2.threshold(GrayImage,130,255,cv2.THRESH_BINARY) #将图片进行二值化（130,255）之间的点均变为255（背景）
# print(thresh1[0,0])#250 输出[0,0]这个点的像素值 				#返回值ret为阈值
# print(ret)#130
(h,w)=thresh1.shape #返回高和宽
# print(h,w)#s输出高和宽
a = [0 for z in range(0, w)] 
print(a) #a = [0,0,0,0,0,0,0,0,0,0,...,0,0]初始化一个长度为w的数组，用于记录每一列的黑点个数 
 
#记录每一列的波峰
for j in range(0,w): #遍历一列 
  for i in range(0,h): #遍历一行
    if thresh1[i,j]==0: #如果改点为黑点
      a[j]+=1 		#该列的计数器加一计数
      thresh1[i,j]=255 #记录完后将其变为白色 
  # print (j)      
 
#      
for j in range(0,w): #遍历每一列
  for i in range((h-a[j]),h): #从该列应该变黑的最顶部的点开始向最底部涂黑
    thresh1[i,j]=0  #涂黑
 
#此时的thresh1便是一张图像向垂直方向上投影的直方图
#如果要分割字符的话，其实并不需要把这张图给画出来，只需要的到a=[]即可得到想要的信息
 
 
# img2 =Image.open('0002.jpg')
# img2.convert('L')
# img_1 = np.array(img2)
plt.imshow(thresh1,cmap=plt.gray())
plt.show()
cv2.imshow('img',thresh1) 
cv2.waitKey(0) 
cv2.destroyAllWindows() 

import cv2 
import numpy as np 
from matplotlib import pyplot as plt 
from PIL import Image
 
img=cv2.imread('C:/Users/Jet Zhang/Desktop/50/50/cut.png') 
GrayImage=cv2.cvtColor(img,cv2.COLOR_BGR2GRAY) 
ret,thresh1=cv2.threshold(GrayImage,130,255,cv2.THRESH_BINARY)
 
(h,w)=thresh1.shape #返回高和宽
 
a = [0 for z in range(0, h)] 
print(a) 
 
for j in range(0,h): 
  for i in range(0,w): 
    if thresh1[j,i]==0: 
      a[j]+=1 
      thresh1[j,i]=255
     
for j in range(0,h): 
  for i in range(0,a[j]):  
    thresh1[j,i]=0  
 
plt.imshow(thresh1,cmap=plt.gray())
plt.show()