refactor: Refactored detection post-processing

[fg-mindee]

This PR introduces the following modifications:

• speeds up and clean the binarization of the probability map and the opening transform
• makes it flexible enough to handle multi-channel outputs
• reflects changes in DB & LinkNet to stick with single-channel output

After comparing latency with the option of switching to PyTorch & TF implementations of the opening transform, I reverted back the changes for one reason: on CPU & GPU, it was all faster except for TensorFlow on CPU that takes ~4-6 times longer to compute the opening transform (max_pool2d seems to be really slow on TF for CPU 🤷‍♂️ )

Any feedback is welcome!

[charlesmindee]

Thanks!

[codecov]

Codecov Report

Merging #724 (4357783) into main (6a591b0) will decrease coverage by 0.00%.
The diff coverage is 100.00%.

@@            Coverage Diff             @@
##             main     #724      +/-   ##
==========================================
- Coverage   96.03%   96.03%   -0.01%     
==========================================
  Files         125      125              
  Lines        4717     4713       -4     
==========================================
- Hits         4530     4526       -4     
  Misses        187      187              

Flag	Coverage Δ
unittests	96.03% <100.00%> (-0.01%)	⬇️

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Impacted Files	Coverage Δ
doctr/models/detection/core.py	96.96% <100.00%> (-0.33%)	⬇️
...s/detection/differentiable_binarization/pytorch.py	98.37% <100.00%> (ø)
...etection/differentiable_binarization/tensorflow.py	97.36% <100.00%> (ø)
doctr/models/detection/linknet/pytorch.py	98.07% <100.00%> (ø)
doctr/models/detection/linknet/tensorflow.py	100.00% <100.00%> (ø)

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