Piv
78d5aace15
Remove Experimental model
...
It didn't perform any better than the regular model
Removing batch normalisation significantly harmed training performance
2021-03-25 21:28:07 +10:30
Piv
ab7da5acd4
Add documentation and README, use Upsampling2D rather than image Resizing layer
2021-03-24 21:35:25 +10:30
Piv
ac3ab27ddd
Add model with no batch normalisation, use actual mobilnet model rather than extracting layers
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Found from DenseDepth, each layer can be set to trainable in the encoder, then the outputs of the
model and the required layers for skip connections can be used directly. Ends up being much cleaner
2021-03-24 20:00:26 +10:30
Piv
39074f22a7
Add working train and eval functions for nyu_v2
2021-03-21 09:51:45 +10:30
Piv
fea08521bb
Add metrics, prepare for training
2021-03-17 21:15:06 +10:30
Piv
00762f3e86
Build Functional Model, remove subclassed model
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Functional models are way easier to work with,
and I don't need any advanced features that would
require model subclassing
2021-03-17 18:24:46 +10:30
Piv
b25b9be4eb
Initial Commit
2021-03-16 21:06:27 +10:30
