Waaw, good job! Could you share the source code of this ocr? If that's 
okay, I'll be really happy.

On Sunday, 13 November 2022 at 14:15:17 UTC+3 Lorenzo Blz wrote:

> Hi Chris,
> you should try to get something like this:
>
> [image: temp2b.jpg]
>
>
>
> I inverted the headers section and then did two different threshold on 
> each part. If you are not interested in the titles you can just crop them 
> out.
>
> The image is blurry, maybe it was upscaled a little? If so, try different 
> levels of upscale, probably better if full integers like 2x, 3x, etc. to 
> see if it improves. Or see if other frames from the video might be better 
> or improve the video capture (resolution, lighting, frame rate, etc.).
>
> This is what I get:
>
> Modes Dunchieachiungszet
>
> = ro
> oF wn [3
> HF omen | mm
> Gesamt 00s 0%
>
> quite unusable but at least it is starting to find something.
>
>
> I think training will help IF all your images have this kind of blurry 
> text and you use actual crops from these images for training.
>
>
> Bye
>
> Lorenzo
>
> Il giorno sab 12 nov 2022 alle ore 18:57 Chris E. <goaf...@gmail.com> ha 
> scritto:
>
>> Hi,
>>
>> I want to OCR this kind of image, which is from a video grabber, 
>> unfortunately of pretty bad quality. With the default options of tesseract, 
>> it's pretty useless.
>> Before I start digging deeper into training tesseract, I would love to 
>> hear some recommendations. Would it be possible to achieve a good result 
>> from this kind of image with proper training?
>> Any further ideas/tips would be appreciated!
>>
>> Greetings,
>> Chris
>>
>> [image: temp2.jpg]
>>
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