Pytesseract Image to String issue

The missing knowledge is page-segmentation-mode (psm). You need to use them, when you can't get the desired result.

If we look at your image, the only artifacts are the black columns. Other than that, the image looks like a binary image. Suitable for tesseract to recognize the characters and the digits.

Lets try reading the image by setting the psm to 6.

6 Assume a single uniform block of text.

print(pytesseract.image_to_string(img, config="--psm 6")

The result will be:

Total Kills: 75,230,550

Kill Details: (recorded after 2019/10/23)
993,161 331,129
1,380,450 33,265,533
5,031,168

Update

The second way to solve the problem is getting binary mask and applying OCR to the mask features.

• Binary-mask

  • 

• Features of the binary-mask

  • 

As we can see the result is slightly different from the input image. Now when we apply OCR result will be:

Total Kills: 75,230,550

Kill Details: (recorded after 2019/10/23)
993,161 331,129
1,380,450 33,265,533
5,031,168

Code:

import cv2
import numpy as np
import pytesseract

# Load the image
img = cv2.imread("LuKz3.jpg")

# Convert to hsv
hsv = cv2.cvtColor(img, cv2.COLOR_BGR2HSV)

# Get the binary mask
msk = cv2.inRange(hsv, np.array([0, 0, 0]), np.array([179, 255, 154]))

# Extract
krn = cv2.getStructuringElement(cv2.MORPH_RECT, (5, 3))
dlt = cv2.dilate(msk, krn, iterations=5)
res = 255 - cv2.bitwise_and(dlt, msk)

# OCR
txt = pytesseract.image_to_string(res, config="--psm 6")
print(txt)

# Display
cv2.imshow("res", res)
cv2.waitKey(0)