Fixes + reqs update

- Fixed model instantiation
- Fix window overlap argument type error
- Updated reqs.txt to have einops (MONAI optional dep.)

Author: C-Achard

napari_cellseg3d/model_workers.py

@@ -227,7 +227,7 @@ def __init__(
         self.instance_params = instance
         self.use_window = use_window
         self.window_infer_size = window_infer_size
-        self.window_overlap_percentage = (0.8,)
+        self.window_overlap_percentage = 0.8
         self.keep_on_cpu = keep_on_cpu
         self.stats_to_csv = stats_csv
         """These attributes are all arguments of :py:func:~inference, please see that for reference"""
@@ -346,7 +346,7 @@ def inference(self):
 
         dims = self.model_dict["model_input_size"]
 
-        model = self.model_dict["class"].get_net()
+
         if self.model_dict["name"] == "SegResNet":
             model = self.model_dict["class"].get_net(
                 input_image_size=[
@@ -360,6 +360,8 @@ def inference(self):
                 img_size=[dims, dims, dims],
                 use_checkpoint=False,
             )
+        else:
+            model = self.model_dict["class"].get_net()
 
         self.log_parameters()
 
@@ -445,6 +447,7 @@ def inference(self):
                 inputs = inputs.to("cpu")
                 print(inputs.shape)
 
+                # self.log("output")
                 model_output = lambda inputs: post_process_transforms(
                     self.model_dict["class"].get_output(model, inputs)
                 )
@@ -460,6 +463,8 @@ def inference(self):
                 else:
                     window_size = None
                     window_overlap = 0.25
+
+                # self.log("window")
                 outputs = sliding_window_inference(
                     inputs,
                     roi_size=window_size,

napari_cellseg3d/models/model_SwinUNetR.py

@@ -3,7 +3,7 @@
 
 
 def get_weights_file():
-    return ""
+    return "Swin64_best_metric.pth"
 
 
 def get_net(img_size, use_checkpoint=True):

requirements.txt

@@ -13,13 +13,10 @@ napari[all]>=0.4.14
 QtPy
 opencv-python>=4.5.5
 dask-image>=0.6.0
-scikit-image>=0.19.2
 matplotlib>=3.4.1
 tifffile>=2022.2.9
 imageio-ffmpeg>=0.4.5
 torch>=1.11
-monai>=0.9.0
-nibabel
+monai[nibabel,scikit-image,itk,einops]>=0.9.0
 pillow
-itk>=5.2.0
 vispy>=0.9.6