小编use*_*569的帖子

我正在尝试清理上面的图像我已经尝试了几种使用open cv的不同方法,我要么过多地侵蚀原始图像,使得部分字母丢失,如下所示:

我不确定如何摆脱最后一条对角线并修复S,到目前为止,我的代码是:

import cv2 
import matplotlib.pylab as plt
img = cv2.imread('/captcha_3blHDdS.png')

#make image gray 
gray = cv2.cvtColor(img,cv2.COLOR_BGR2GRAY)

#Blur
blur = cv2.GaussianBlur(gray,(5,5),0)
bilateral = cv2.bilateralFilter(gray,5,75,75)

#Thresholding
ret, thresh = cv2.threshold(bilateral,25,255,cv2.THRESH_BINARY_INV+cv2.THRESH_OTSU)

#Kernal
kernel = cv2.getStructuringElement(cv2.MORPH_RECT, (3, 3))

#other things
erosion = cv2.erode(thresh,kernel,iterations = 1)
closing = cv2.morphologyEx(erosion, cv2.MORPH_CLOSE, kernel, iterations = 1)

#Transform image
dist_transform = cv2.distanceTransform(closing,cv2.DIST_L2,5)
ret, sure_fg = cv2.threshold(dist_transform,0.02*dist_transform.max(),255,cv2.THRESH_BINARY)#,255,0)

#kernel_1
kernel_1 = cv2.getStructuringElement(cv2.MORPH_ELLIPSE, (1, 2))

dilation_1 = cv2.dilate(sure_fg,kernel_1,iterations = 2)
erosion_1 = cv2.erode(dilation_1,kernel_1,iterations = 3)

plt.imshow(erosion_1, 'gray')

任何帮助将不胜感激,以下是更多从验证码产生的图像类型的例子;

还包含指向包含 …

给出一个整数列表,例如:

lst = [-5, -1, -13, -11, 4, 8, 16, 32]

是否有一种Pythonic方法来检索列表中最大的负数(例如-1)和列表中最小的正数(例如4)？

嗨希望得到一些帮助,我有两列Dataframe df作为;

Source ID
1      2
2      3
1      2
1      2
1      3
3      1

我的目的是对Source进行分组,并根据分组的Source将ID单元格除以总计,并将其附加到orginial数据框,以便新列看起来像;

   Source ID  ID_new
    1      2  2/9
    2      3  3/3
    1      2  2/9
    1      2  2/9
    1      3  3/9
    3      1  3/1

我已经到了;

df.groupby('Source ID')['ID'].sum()

得到总数,ID但我不知道下一步去哪里.