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Author	SHA1	Message	Date
Piv	ac3ab27ddd	Add model with no batch normalisation, use actual mobilnet model rather than extracting layers ... 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 ... 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