geodl 0.3.0
- Support for three model architectures: UNet, UNet with MobileNetv2
encoder, and UNet3+
- UNet with MobileNetv2 encoder is no longer limited to three input
predictor variables
- Assessment and prediction functions now expect a nn_module object as
opposed to a luz fitted object
- Dynamically generate chips during training process as opposed to
saving them to disk beforehand (still experimental)
- Ignore outer rows and columns of cells when calculating loss or
assessment metrics if desired
- Use R torch to calculate several different land surface parameters
(LSPs) from a digital terrain model: slope, hillshade, aspect,
northwardness, eastwardness, transformed solar radiation aspect index
(TRASP), site exposure index (SEI), topographic position index (TPI),
and surface curvatures (mean, profile, and planform)
- Calculate three-band terrain visualization raster grid from a DTM
using torch or terra
- New specialized model for extracting geomorphic features from
digital terrain models (DTMs)
- New function to count the number of trainable parameters in a
model
- Fixed issue with chip generation pipeline that caused some chips
with NA cells to be written
- Updated atrous spatial pyramid pooling (ASPP) module to align with
the version used within DeepLabv3+
geodl 0.2.0