More model checkpoints

TensorFlow Model Checkpoints for models trained on DHS data.

Model Category	Naming Scheme
out-of-country (OOC)	DHS_OOC_{fold}_{bands}_{init}_b{batch}_fc{reg}_conv{reg}_lr{lr}
in-country	DHS_Incountry_{fold}_{bands}_{init}_b{batch}_fc{reg}_conv{reg}_lr{lr}
transfer learning	transfer_nlcenter_{bands}_b{batch}_fc{reg}_conv{reg}_lr{lr}

• {fold}: the fold that the model was tested on
• {bands}: one of MS, NL, or RGB
• {init}: the weights initialization strategy used
• {batch}: batch size
• {reg}: the L2 regularization coefficient is 0.{reg} if {reg} does not include a period ., or {reg} otherwise
• {lr}: the initial learning rate is 0.{lr} if {lr} does not include a period ., or {lr} otherwise

Changes from v1.0 to v1.0.1:

• Model checkpoint zip files no longer have nested folders.
• Each zip file now includes a params.json file which includes the parameters used to train the model.
• Added checkpoints for DHS OOC NL and RGB models. Note: the model weights for the DHS OOC MS models are unchanged.
• Added checkpoints for DHS Incountry MS and NL models.
• Added checkpoints for transfer learning models.
• Added ImageNet pretrained weights (imagenet_resnet18_tensorpack.npz)