Comments (4)
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Thanks very much.
from crnn.tf2.
Sorry, but can you point me to where exactly I can make this change? If I'm understanding correctly, it's in metrics.py specifically lines 27 and 28 which are:
y_true = sparse2dense(y_true, [batch_size, max_width])
y_pred = sparse2dense(decoded[0], [batch_size, max_width])
but these are tensors that are converted from sparse to dense. For me, the 'space' character is the 2nd label in the table of characters. Does that mean I have to tell it to ignore differences in the 2nd characters somehow?
Or is there a way to access the predicted values without tensors (but I think that would make it slower?)
from crnn.tf2.
Sorry, I didn't notice the email. In the function, the conversion to densor tensor is only because the compared api does not support sparse tensor. You can think about how to count whether it matches or not. The simplest, circular comparison, ignoring spaces is a crude implementation.
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