Supporting information for "imageseg: an R package for deep learning-based image segmentation" (2022)
Niedballa, J., Axtner, J., Döbert, T.F., Tilker, A., Nguyen, A., Wong, S.T., Fiderer, C., Heurich, M., Wilting, A.
Methods in Ecology and Evolution. MEE-22-05-446


imageseg_canopy_model.zip
	Model file (.hdf5) and "examples" folder for canopy density image segmentation model. In the examples, left column is model input, central column is raw model output, right column is binarized output.

imageseg_canopy_training_data.zip 
	Training data used for canopy density model (images and masks, 256x256 pixels), split into three folders. See the info.txt file for details.

imageseg_canopy_training_run.R 
	R script used for canopy model training.

imageseg_understory_model.zip
	Model file (.hdf5) and "examples" folder for understory vegetation density image segmentation model. In the examples, left column is model input, central column is raw model output, right column is binarized output.

imageseg_understory_training_data.zip 
	Training data used for understory vegetation density model (images and masks, 160x256 pixels).

imageseg_understory_training_run.R
	R script used for understory vegetation model training.
