[FIXED] Pytesseract gets inaccurate in reading chess notations

Issue

I've been experimenting with pytesseract and I have searched some improvements for accuracy but it didn't work for me. So here's my img:

This is the output:

Code:

img = cv2.imread("temp.png")
gry = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
thr = cv2.adaptiveThreshold(gry, 255, cv2.ADAPTIVE_THRESH_MEAN_C, cv2.THRESH_BINARY, 11, 4)
txt = pytesseract.image_to_string(thr, config='--psm 13')
print(txt) # "@)"

I don't know everything since I just started, can someone give me tips how can this be done?

Edit: Ahx solved my question but there's something buggy in the code. It's reading 6 as é. For example d6, it will read it as dé. I added some thresholds and blurs because I think it will improve it but it didn't. Here's my updated code:

img = cv2.imread('temp.png')
hsv = cv2.cvtColor(img, cv2.COLOR_BGR2HSV)
lwr = np.array([0, 0, 0])
upr = np.array([179, 255, 180])
msk = cv2.inRange(hsv, lwr, upr)
msk = cv2.resize(msk, (0, 0), fx=3, fy=3, interpolation=cv2.INTER_CUBIC)
msk = cv2.adaptiveThreshold(cv2.bilateralFilter(msk, 9, 75, 75), 255, cv2.ADAPTIVE_THRESH_GAUSSIAN_C, cv2.THRESH_BINARY, 31, 2)
msk = cv2.adaptiveThreshold(cv2.medianBlur(msk, 3), 255, cv2.ADAPTIVE_THRESH_GAUSSIAN_C, cv2.THRESH_BINARY, 31, 2)
txt = pytesseract.image_to_string(msk, lang='eng', config=r'--psm 6 --oem 3')

The e6 actually worked but 6 in others like d6, Nf6 is always é.

Here's an example if ever you wanna try it out:

Output:

result: Nf6é

Solution

You can easily get the result by performing color-segmentation. First, you need to load the image, convert it to the HSV format. Next, define the upper and lower boundaries to get the binary-mask. The binary mask will contain the required features for recognizing the characters. Then we will upsample the binary-mask and give input to the tesseract.

• Upsampled Binary-mask

  • 

• OCR Result: e6

---

Code:

import cv2
import numpy as np
import pytesseract

# Load the image
img = cv2.imread("iTO9h.png")

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

# Get binary-mask
lwr = np.array([0, 0, 0])
upr = np.array([179, 255, 180])
msk = cv2.inRange(hsv, lwr, upr)

# Up-sample
msk = cv2.resize(msk, (0, 0), fx=2, fy=2)

# OCR
txt = pytesseract.image_to_string(msk)
print(txt)

Answered By - Ahx