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Crash/BSOD on Windows 11 when using Hebrew #39
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I believe Tesseract itself doesn't care how an image was captured. Could you please provide more context (e.g., an example image or a link to the ticket on the Tesseract bug tracker)? Or maybe you mean that dpScreenOCR has issues capturing images on machines with Intel UHD 600?
Googling for "Tesseract-OCR-DNN" gives no results. BTW, Tesseract already uses deep learning (LSTM). |
My problem is that every time I use this software, the computer shuts down or i get BSOD system crash, this is the instructions to build from source:
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So you are using Windows? Could you please tell your Windows and dpScreenOCR versions, and provide the steps to reproduce the crash/shutdown?
That's unlikely: Tesseract doesn't use GPU acceleration.
The Tesseract library used by dpScreenOCR on Windows is already built from the official source code from https://github.com/tesseract-ocr/tesseract. |
my Windows version: Windows 11 |
What languages do you use for OCR? Were they installed from the language manager or elsewhere? |
Language: hebrew |
Does using only English also cause a crash? |
I didn't try the English language, |
I don't currently have access to Windows 11, but I was unable to reproduce the issue with Windows 7 and 10. I have tried both the official Hebrew data and the files from https://gitlab.com/pninim.org/tessdata_heb_rashi/-/tree/main/tesseract_4.1.1. It would help me if you could:
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Apparently version 1.1.0 does not cause any problem, but no I don't know for sure yet, |
Problem:
dpscreenocr uses Tesseract to recognize text on the screen. However, Tesseract has known issues with recognizing text from images captured by Intel UHD 600 graphics cards (like BSOD).
Solution:
Add support for Tesseract-OCR-DNN to dpscreenocr. Tesseract-OCR-DNN is a deep learning-based OCR engine that is not affected by the same issues as Tesseract.
Benefits:
Improved accuracy for recognizing text from images captured by Intel UHD600 graphics cards.
Increased flexibility for users to choose the best OCR engine for their needs.
Implementation:
Add a new configuration option to dpscreenocr that allows users to choose between using Tesseract or Tesseract-OCR-DNN.
Update the code to use Tesseract-OCR-DNN when the new configuration option is set to "Tesseract-OCR-DNN".
Conclusion:
Adding support for Tesseract-OCR-DNN to dpscreenocr would be a valuable addition to the program. It would provide users with improved accuracy and flexibility, making it a more powerful tool for recognizing text on the screen.
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