geodl 0.3.3
- Updated torch-dependent examples so they are skipped when the torch runtime dependencies, including Lantern, are unavailable.
- Fixed example typo in
defineUnifiedFocalLoss()wherepred2was used twice.
geodl 0.3.0
CRAN release: 2025-11-12
- 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+