More doc updates

Author: constantinpape

micro_sam/precompute_state.py

@@ -1,3 +1,6 @@
+"""Precompute image embeddings and automatic mask generator state for image data.
+"""
+
 import os
 import pickle
 
@@ -26,7 +29,7 @@ def cache_amg_state(
         predictor: The segment anything predictor.
         raw: The image data.
         image_embeddings: The image embeddings.
-        save_path: The embedding save path. The AMG state will be stored in <save_path>/amg_state.pickle.
+        save_path: The embedding save path. The AMG state will be stored in 'save_path/amg_state.pickle'.
         verbose: Whether to run the computation verbose.
         kwargs: The keyword arguments for the amg class.
 

micro_sam/training/__init__.py

@@ -1,2 +1,5 @@
+"""Functionality for training Segment Anything.
+"""
+
 from .sam_trainer import SamTrainer, SamLogger
 from .util import ConvertToSamInputs, get_trainable_sam_model

micro_sam/training/sam_trainer.py

@@ -26,7 +26,7 @@ class SamTrainer(torch_em.trainer.DefaultTrainer):
         n_objects_per_batch: If not given, we compute the loss for all objects in a sample.
             Otherwise the loss computation is limited to n_objects_per_batch, and the objects are randomly sampled.
         mse_loss: The regression loss to compare the IoU predicted by the model with the true IoU.
-        sigmoid: The actuction function for normalizing the model output.
+        sigmoid: The activation function for normalizing the model output.
         **kwargs: The keyword arguments of the DefaultTrainer super class.
     """