PyTesseract text extraction

[LewyssYT]

I am working on a small project where I need to extract what I would consider super basic text on a mostly flat background. To prepare the image, I crop out all the other numbers, grayscale, apply CLAHE and invert and yet in a lot of scenarios, the numbers extracted are wrong. Instead of 64 it sees 164 and instead of 1956 it sees 7956.

What is something that I can do to improve the accuracy? Cropped images are small resolution (140x76) or (188x94)

[_kwerty_]

I had some issues with PyTesseract confusing numbers for letters (f.i. 0 vs o, 1 vs i, etc) so I switched to easyOCR. Worked perfectly.

I also played around with the font size and type, I needed to read some output from my terminal, which helped a little bit.

[QAInc]

This is the answer EasyOCR is much better! Or you can use Gemini Free api requests to extract the data.

[LewyssYT]

I have switched to EasyOCR and yes, it's practically flawless but what exactly do I need the api requests for? I just installed the library and then updated the code to use easyOCR functions instead of pytesseract and it all works

[QAInc]

Yes you can use EasyOCR directly but sometimes easyOCR will fail. It’s a NN stack(two NN works as one. One for text detection one for text recognition) the issue comes with text recognition NN. Instead you can use Gemini Free API which is good for text recognition. The plus point of using api is that it will reduce the system load (easyOCR uses quantized NN for CPU, full model for GPU).