Fix Swin for latest MONAI (#113)

* Fix napari-hub shield in README

* Update News and Citation with eLife data

* Update README.md

* Update README.md

* Update model_SwinUNetR.py

Remove deprecated img_size argument for latest MONAI

* Revert "Update model_SwinUNetR.py"

This reverts commit 504ee6d.

* Test with new env and latest MONAI

* Add monai optional reader for tiff to dependencies

* Prospective test fixes

* Update test_and_deploy.yml

* Update model_SwinUNetR.py

* Update test_and_deploy.yml

* Move tifffile deps to MONAI install only

* Fix Swin args + try to get tifffile installed in CI

* update pyclesperanto dependency (#117)

* Update README.md (#114)

Fix napari-hub shield in README

Update News and Citation with eLife data

Update README.md

* remove prototype

---------

Co-authored-by: Cyril Achard <94955160+C-Achard@users.noreply.github.com>

* Fix Swin feature size

---------

Co-authored-by: Stephane Rigaud <Stephane.rigaud@pasteur.fr>

Author: C-Achard

.github/workflows/test_and_deploy.yml

@@ -51,6 +51,8 @@ jobs:
         run: |
           python -m pip install --upgrade pip
           python -m pip install setuptools tox tox-gh-actions
+          python -m pip install tifffile
+          python -m pip install monai[nibabel,einops,tifffile]
 #         pip install git+https://github.com/lucasb-eyer/pydensecrf.git@master#egg=pydensecrf
 
 # this runs the platform-specific tests declared in tox.ini

conda/napari_CellSeg3D_ARM64.yml

@@ -18,7 +18,7 @@ dependencies:
         - monai[nibabel, einops]>=0.9.0
         - tqdm
         - scikit-image
-        - pyclesperanto-prototype
+        - pyclesperanto
         - tqdm
         - matplotlib
         - napari_cellseg3d

docs/welcome.rst

@@ -168,7 +168,7 @@ This plugin additionally uses the following libraries and software:
 .. _PyTorch: https://pytorch.org/
 .. _MONAI project: https://monai.io/
 .. _on their website: https://docs.monai.io/en/stable/networks.html#nets
-.. _pyclEsperanto: https://github.com/clEsperanto/pyclesperanto_prototype
+.. _pyclEsperanto: https://github.com/clEsperanto/pyclesperanto
 .. _WNet: https://arxiv.org/abs/1711.08506
 
 .. rubric:: References

napari_cellseg3d/code_models/instance_segmentation.py

@@ -6,7 +6,7 @@
 from typing import List
 
 import numpy as np
-import pyclesperanto_prototype as cle
+import pyclesperanto as cle
 from qtpy.QtWidgets import QWidget
 from skimage.measure import label, regionprops
 from skimage.morphology import remove_small_objects
@@ -287,7 +287,7 @@ def voronoi_otsu(
     BASED ON CODE FROM : napari_pyclesperanto_assistant by Robert Haase
     https://github.com/clEsperanto/napari_pyclesperanto_assistant
     Original code at :
-    https://github.com/clEsperanto/pyclesperanto_prototype/blob/master/pyclesperanto_prototype/_tier9/_voronoi_otsu_labeling.py.
+    https://github.com/clEsperanto/pyclesperanto/blob/d1990e28b1da44a7921890b7bd809d522d3198b8/pyclesperanto/_tier7.py#L409-L448.
 
     Args:
         volume (np.ndarray): volume to segment

napari_cellseg3d/code_models/models/model_SwinUNetR.py

@@ -1,5 +1,7 @@
 """SwinUNetR wrapper for napari_cellseg3d."""
 
+import inspect
+
 from monai.networks.nets import SwinUNETR
 
 from napari_cellseg3d.utils import LOGGER
@@ -30,30 +32,30 @@ def __init__(
         use_checkpoint (bool): whether to use checkpointing during training.
         **kwargs: additional arguments to SwinUNETR.
         """
+        parent_init = super().__init__
+        sig = inspect.signature(parent_init)
+        init_kwargs = dict(
+            in_channels=in_channels,
+            out_channels=out_channels,
+            use_checkpoint=use_checkpoint,
+            feature_size=48,
+            drop_rate=0.5,
+            attn_drop_rate=0.5,
+            use_v2=True,
+            **kwargs,
+        )
+        if "img_size" in sig.parameters:
+            # since MONAI API changes depending on py3.8 or py3.9
+            init_kwargs["img_size"] = input_img_size
+        if "dropout_prob" in kwargs:
+            init_kwargs["drop_rate"] = kwargs["dropout_prob"]
+            init_kwargs.pop("dropout_prob")
         try:
-            super().__init__(
-                input_img_size,
-                in_channels=in_channels,
-                out_channels=out_channels,
-                feature_size=48,
-                use_checkpoint=use_checkpoint,
-                drop_rate=0.5,
-                attn_drop_rate=0.5,
-                use_v2=True,
-                **kwargs,
-            )
+            parent_init(**init_kwargs)
         except TypeError as e:
             logger.warning(f"Caught TypeError: {e}")
-            super().__init__(
-                input_img_size,
-                in_channels=1,
-                out_channels=1,
-                feature_size=48,
-                use_checkpoint=use_checkpoint,
-                drop_rate=0.5,
-                attn_drop_rate=0.5,
-                use_v2=True,
-            )
+            init_kwargs["in_channels"] = 1
+            parent_init(**init_kwargs)
 
     # def forward(self, x_in):
     #     y = super().forward(x_in)

napari_cellseg3d/dev_scripts/sliding_window_voronoi.py

@@ -1,6 +1,6 @@
 """Test script for sliding window Voronoi-Otsu segmentation.""."""
 import numpy as np
-import pyclesperanto_prototype as cle
+import pyclesperanto as cle
 from tqdm import tqdm