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Hi, I'd like to know what is the recommended/optimal data preparation for training (and recognition, if different).
For example:
is it better to use a grayscale image or a binary one?
is it better to leave some white margins (left/right, top/bottom) or trim tight to the text(*)? In the first case, the "target_height" should include the margin or not?
does it perform some kind or text straightening/dewarping or should I do it?
any other things to consider?
Thanks.
(*) I'm asking this because when I started to using it, it was common for the very first letter to be discarded and adding some white margin seemed to fix it. But I was using very little data and maybe it was just a coincidence. The uw3 samples also have a small border.
The text was updated successfully, but these errors were encountered:
Hi, I'd like to know what is the recommended/optimal data preparation for training (and recognition, if different).
For example:
Thanks.
(*) I'm asking this because when I started to using it, it was common for the very first letter to be discarded and adding some white margin seemed to fix it. But I was using very little data and maybe it was just a coincidence. The uw3 samples also have a small border.
The text was updated successfully, but these errors were encountered: