This article introduces the python image binarization to improve the recognition rate of code examples, the text through the sample code is very detailed, for everyone's learning or work has a certain reference learning value, you can refer to the next!
The code is as follows
import cv2from PIL import Imagefrom pytesseract import pytesseractfrom PIL import ImageEnhanceimport reimport string
def createFile(filePath,newFilePath):
img = (filePath)
# Mode L" is a gray image, each pixel of which is represented by 8 bits, 0 for black, 255 for white, and other numbers for different shades of gray.
Img = ('L')
(newFilePath)
# Custom grayscale boundaries, greater than this value is black, less than this value is white
threshold = 200
table = []
for i in range(256):
if i < threshold:
(0)
else:
(1)
# Image binarization
photo = (table, '1')
(newFilePath)
if __name__ == '__main__':
createFile(r'',r'')
Original image:
Processed Figures:
Identify the results:
This is the entire content of this article.