try:
 tesseract image - get.image
which calls GetThresholdedImage()
<https://github.com/tesseract-ocr/tesseract/blob/12c1abcb6b4ef90cfafe316a3b40753ee5e9b9ef/src/api/baseapi.cpp#L638>


Zdenko


st 30. 1. 2019 o 11:17 Lorenzo Bolzani <[email protected]> napísal(a):

>
> Zdenko, are you 100% sure that the image is binarized before being fed to
> the neural network? It looks like a big waste of information to me.
>
>
> Il giorno mer 30 gen 2019 alle ore 07:56 Zdenko Podobny <[email protected]>
> ha scritto:
>
>> That is not true: you do not need to transform image to grayscale. Any
>> image is at the end binarized (if input image is not binarized) by
>> tesseract (Otsu).
>>
>> BUT: preprocessing image (e.g. custom binarization) will help. See
>> https://github.com/tesseract-ocr/tesseract/wiki/ImproveQuality
>>
>> Zdenko
>>
>>
>> st 30. 1. 2019 o 7:36 <[email protected]> napísal(a):
>>
>>> Not a solution, but the image needs to be transformed into grayscaleetc,
>>> (using Open CV) since OCR works best with grayed images and images which
>>> have size of 300 dpi
>>>
>>> On Tuesday, June 12, 2018 at 12:44:21 PM UTC+5:30, Vidur Malhotra wrote:
>>>>
>>>> I tried running the tesseract on the attached image. But not getting
>>>> the desired output. My sample code:
>>>>
>>>>
>>>> import PIL
>>>> from PIL import Image
>>>> import pytesseract
>>>>
>>>> text = pytesseract.image_to_string(Image.open('test3.jpg'), lang='eng')
>>>> print(text)
>>>>
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