Python+OpenCV program for batch clipping of images

In the process of learning online online courses recently, I used mobile phones to intercept a lot of pictures in order to facilitate the review after class. But the interception of the picture files occupied a lot of memory, and there were black and black information areas. Want to print out these pictures as courseware to save, but the black area around will not only consume a lot of printing ink, but also print out beautiful. I look for programs on the Internet to solve my problems, and the code I get can't achieve the goal of simplicity and efficiency.

So I wrote a Python program myself, using the simple function of OpenCV library, to take batch screenshots of a large number of pictures, intercept the required parts and save them:

A large number of pictures to be processed:

I chose one of the pictures as a demonstration:

Prior to program tailoring:

For the above image, we need to remove the black areas on both sides and cut out the useful areas.

Procedure 1:

import cv2
import os 

"""Save the file name to test.txt，Read the file name by line and operate on it."""
f = open("test.txt",'w')
for root,dirs,files in os.walk("kaochong", True):      # Traverse to retrieve roots, directories, files
	for file in files:                                 # File traversal
		f.writelines("kaochong\\" + file)              # Write file names by line
		f.write('\n')                                  # Give me a
f = open("test.txt",'r')
for i in range(1,107):                                 # 106 documents
     line = f.readline()                               # Read a row
     line = line.strip('\n')                           # Remove \n
     #print(line)
     image = cv2.imread(line)                          # Read the image corresponding to the file name
     # cropImg = image[0:1080:2, 240:1680:2]           # First y range, then x range, and the third step of each is the sampling step.
     cropImg = image[0:1080, 240:1680]                 # Tailoring
     cv2.imwrite("kaochong1\\" + line[20:39] + ".png", cropImg)       # Preservation
f.close()

# print(image.shape)
# cv2.imshow("image", image)
# print(cropImg.shape)
# cv2.imshow("cropImg", cropImg)
# cv2.waitKey(0)

Procedure 2:

import cv2
import os 

"""Simplified version, read the file name, do not save, immediately operate"""
for root,dirs,files in os.walk("kaochong", True):           # Traverse to retrieve roots, directories, files
	for file in files:                                      # File traversal
          line = "kaochong\\" + file
          #print(line)
          image = cv2.imread(line)                          # Read the image corresponding to the file name
          # cropImg = image[0:1080:2, 240:1680:2]           # First y range, then x range, and the third step of each is the sampling step.
          cropImg = image[0:1080, 240:1680]                 # Tailoring
          cv2.imwrite("kaochong1\\" + line[20:39] + ".png", cropImg)       # Preservation

After batch processing, the black area was removed and some images were clipped.

Cut-out demonstration pictures: