Create a new sg_trained_model object

Constructor for the sg_trained_model S3 class, representing a trained segmentation model with associated metadata.

Usage

new_sg_trained_model(
  model_path,
  backend = c("cellpose", "stardist"),
  base_model,
  training_metrics,
  model_card = list()
)

Arguments

model_path

Character. Path to the trained model weights.

backend

Character. Segmentation backend: "cellpose" or "stardist".

base_model

Character. Name of the base model that was fine-tuned.

training_metrics

Named list of training metrics (e.g., loss curve, number of epochs).

model_card

Named list of model card metadata (description, author, intended use, etc.).

Value

An object of class sg_trained_model.

Examples

mdl <- new_sg_trained_model(
  model_path = tempdir(),
  backend = "cellpose",
  base_model = "cyto3",
  training_metrics = list(n_epochs = 100L, final_loss = 0.05)
)
print(mdl)
#> <sg_trained_model>
#> Backend: cellpose
#> Base model: cyto3
#> Model path: /tmp/RtmpNfLzCr
#> Epochs: 100
#> Final loss: 0.05
#> Created: 2026-08-22 13:08:28