I used this command:

 tesseract five_filter_5.jpg ocr.txt --oem 1 --psm 6 -l eng

I used "eng.traineddata" from tessdata_best repo.

It gave "5" in ocr.txt.




On Sat, Oct 27, 2018 at 12:22 PM <[email protected]> wrote:

> 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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