Hello, I am using Tesseract to extract some data from screenshots. I've noticed that sometimes there are mistakes in interpreting characters like '0' and 'O', 'P' and 'R' or '-' and '—' or the other way around. This happen with the same font. And it happens sometimes even with some preprocessing, like binarization. Is there a comprehensive map of all characters that are usually mistakenly recognised that are very similar? I need that map in order to calculate effective string distance with Levenshtein and adjust the cost for characters that are very similar. Thanks.
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