I am using Pytesseract to recognise an image for number 5 and I'm stunned
that even after applying various filters like GlaussianBlur and Threshold
and applying dilation and erosion to remove the noise it still not able to
identify the image.
I am using Eng Trained data by default. Not sure where I am going wrong. Do
I need to include any other training file here?
Filters Tried:
1: cv2.threshold(cv2.GaussianBlur(img, (9, 9), 0), 0, 255,
cv2.THRESH_BINARY + cv2.THRESH_OTSU)[1],
2: cv2.threshold(cv2.GaussianBlur(img, (7, 7), 0), 0, 255,
cv2.THRESH_BINARY + cv2.THRESH_OTSU)[1],
3: cv2.threshold(cv2.GaussianBlur(img, (5, 5), 0), 0, 255,
cv2.THRESH_BINARY + cv2.THRESH_OTSU)[1],
4: cv2.threshold(cv2.medianBlur(img, 5), 0, 255,
cv2.THRESH_BINARY + cv2.THRESH_OTSU)[1],
5: cv2.threshold(cv2.medianBlur(img, 3), 0, 255,
cv2.THRESH_BINARY + cv2.THRESH_OTSU)[1],
6: cv2.adaptiveThreshold(cv2.GaussianBlur(img, (5, 5), 0), 255,
cv2.ADAPTIVE_THRESH_GAUSSIAN_C, cv2.THRESH_BINARY, 31, 2),
7: cv2.adaptiveThreshold(cv2.medianBlur(img, 3), 255,
cv2.ADAPTIVE_THRESH_GAUSSIAN_C, cv2.THRESH_BINARY, 31, 2),
*Training Data:*
eng.traineddata
*Original Image: See Attached*
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