feat: Added recognition postprocessor with CTC decoder

[charlesmindee]

Implements CTC decoder with keras backend to decode raw output of CRNN model.
postprocessor input: raw tensor (CRNN output), output: list of words (strings), size = batch_size

[codecov]

Codecov Report

Merging #37 (591c114) into main (05d6f4f) will decrease coverage by 0.29%.
The diff coverage is 94.59%.

@@            Coverage Diff             @@
##             main      #37      +/-   ##
==========================================
- Coverage   97.84%   97.54%   -0.30%     
==========================================
  Files          17       18       +1     
  Lines         371      408      +37     
==========================================
+ Hits          363      398      +35     
- Misses          8       10       +2     

Impacted Files	Coverage Δ
doctr/models/recognition/postprocessor.py	94.44% <94.44%> (ø)
doctr/models/recognition/__init__.py	100.00% <100.00%> (ø)

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[fg-mindee]

Thanks for the PR! I left a few comments, but I'm wondering here: if this is specific to CRNN, then we should put specific parts into the crnn.py file. And I feel like your postprocessing function, could be a class (at init, we can already set num_classes, label_to_dict, ignore_case, ignore_accents, so that the call method only takes logits as inputs)

[fg-mindee]

Thanks for the edits! LGTM