Fine-tune a Cellpose model on user-corrected masks — sg_train

Trains (fine-tunes) a Cellpose segmentation model using corrected image-mask pairs provided by the user. Requires a working Python environment with Cellpose installed (see sg_setup_python()).

Usage

sg_train_cellpose(
  training_data,
  base_model = "cyto3",
  n_epochs = 100L,
  learning_rate = 0.1,
  save_path = NULL,
  verbose = TRUE
)

Arguments

training_data: A list of training pairs. Each element must be a list with $image (sg_image) and $mask (sg_mask).
base_model: Character. Cellpose base model to fine-tune. Default "cyto3".
n_epochs: Integer. Number of training epochs. Default 100L.
learning_rate: Numeric. Learning rate. Default 0.1.
save_path: Character or NULL. Directory to save the trained model. When NULL, a temporary directory is used.
verbose: Logical. Print training progress? Default TRUE.

Value

An sg_trained_model object.

Examples

# \donttest{
# Requires Python + Cellpose:
# trained <- sg_train_cellpose(training_data, base_model = "cyto3")
# }