import numpy as np 
import cv2 

def get_vvList(list_data):
    #取出list中像素存在的區(qū)間
    vv_list=list()
    v_list=list()
    for index,i in enumerate(list_data):
        if i>0:
            v_list.append(index)
        else:
            if v_list:
                vv_list.append(v_list)
                #list的clear與[]有區(qū)別
                v_list=[]
    return vv_list

if __name__=='__main__':
    img_bgr=cv2.imread('./testImg/2.png',1)
    if not img_bgr is None:
        img=img_bgr.copy()
        img_gray=cv2.cvtColor(img,cv2.COLOR_BGR2GRAY)
        #二值化
        t,binary=cv2.threshold(img_gray,0,255,cv2.THRESH_OTSU+cv2.THRESH_BINARY)
        '''
        垂直投影為從上往下投射，統(tǒng)計(jì)每一列的黑色像素總數(shù)
        '''
        rows,cols=binary.shape
        ver_list=[0]*cols
        for j in range(cols):
            for i in range(rows):
                if binary.item(i,j)==0:
                    ver_list[j]=ver_list[j]+1
        '''
        對(duì)ver_list中的元素進(jìn)行篩選，可以去除一些噪點(diǎn)
        '''
        ver_arr=np.array(ver_list)
        ver_arr[np.where(ver_arr<1)]=0
        ver_list=ver_arr.tolist()

        #繪制垂直投影
        img_white=np.ones(shape=(rows,cols),dtype=np.uint8)*255
        for j in range(cols):
            pt1=(j,rows-1)
            pt2=(j,rows-1-ver_list[j])
            cv2.line(img_white,pt1,pt2,(0,),1)
        cv2.imshow('垂直投影',img_white)
        cv2.waitKey(0)

        #切割單一字符
        vv_list=get_vvList(ver_list)
        for i in vv_list:
            img_ver=img_bgr[:,i[0]:i[-1]]
            cv2.imshow('單一字符',img_ver)
            cv2.waitKey(0)