I'm trying to read different cropped images from a big file and I manage to read most of them but there are some of them which return an empty string when I try to read them with tesseract.
The code is just this line:
pytesseract.image_to_string(cv2.imread("img.png"), lang="eng")
Is there anything I can try to be able to read these kind of images?
Thanks in advance
Edit:
Thresholding the image before passing it to pytesseract increases the accuracy.
import cv2
import numpy as np
# Grayscale image
img = Image.open('num.png').convert('L')
ret,img = cv2.threshold(np.array(img), 125, 255, cv2.THRESH_BINARY)
# Older versions of pytesseract need a pillow image
# Convert back if needed
img = Image.fromarray(img.astype(np.uint8))
print(pytesseract.image_to_string(img))
This printed out
5.78 / C02
Edit:
Doing just thresholding on the second image returns 11.1. Another step that can help is to set the page segmentation mode to "Treat the image as a single text line." with the config --psm 7. Doing this on the second image returns 11.1 "202 ', with the quotation marks coming from the partial text at the top. To ignore those, you can also set what characters to search for with a whitelist by the config -c tessedit_char_whitelist=0123456789.%. Everything together:
pytesseract.image_to_string(img, config='--psm 7 -c tessedit_char_whitelist=0123456789.%')
This returns 11.1 202. Clearly pytesseract is having a hard time with that percent symbol, which I'm not sure how to improve on that with image processing or config changes.
