Merge branch 'master' into dev

Author: constantinpape

RELEASE_OVERVIEW.md

@@ -1,5 +1,10 @@
 # Release Overview
 
+**New in version 1.5.0**
+- Preliminary version of object classification tool.
+- Enabling support for napari v6, zarr v3 and numpy v2.
+- Add support for training models for automatic instance segmentation-only.
+
 **New in version 1.4.0**
 
 This release includes three main changes:

micro_sam/instance_segmentation.py

@@ -805,6 +805,7 @@ def get_unetr(
         use_skip_connection=False,
         resize_input=True,
         use_conv_transpose=use_conv_transpose,
+
     )
 
     if decoder_state is not None:

micro_sam/training/training.py

@@ -664,8 +664,9 @@ def default_sam_dataset(
     if raw_transform is None:
         raw_transform = require_8bit
 
+    # Prepare the label transform.
     if with_segmentation_decoder:
-        label_transform = torch_em.transform.label.PerObjectDistanceTransform(
+        default_label_transform = torch_em.transform.label.PerObjectDistanceTransform(
             distances=True,
             boundary_distances=True,
             directed_distances=False,
@@ -674,7 +675,14 @@ def default_sam_dataset(
             min_size=min_size,
         )
     else:
-        label_transform = torch_em.transform.label.MinSizeLabelTransform(min_size=min_size)
+        default_label_transform = torch_em.transform.label.MinSizeLabelTransform(min_size=min_size)
+
+    # Allow combining label transforms.
+    custom_label_transform = kwargs.pop("label_transform", None)
+    if custom_label_transform is None:
+        label_transform = default_label_transform
+    else:
+        label_transform = torch_em.transform.generic.Compose(custom_label_transform, default_label_transform)
 
     # Check the patch shape to add a singleton if required.
     patch_shape = _update_patch_shape(