Improved Utilities (#44)

* Utils improvements

- Set new results path now remains across utils
- Utils generate one layer and update it on subsequent runs
- Layer choice tries to be conserved across utils

* Cleanup + CRF fixes

* Fragmenting utility

* Temp fix for CRF (#46)

* Update plugin_convert.py

* Update test_and_deploy.yml

* Update test_inference.py

* Fix tests + new weights

* Update test_models.py

* Fix dir for saving in tests

* Docstring update

* CRF and utils colormap adjustment

* Update plugin_crf.py

* Fix typo in crf.py

Co-authored-by: Jessy Lauer <[email protected]>

* Fix Pathlib typo in plugin_convert.py

Co-authored-by: Jessy Lauer <[email protected]>

* Fixed filepaths + comments cleanup

* Fixed merge comment deletion

---------

Co-authored-by: Jessy Lauer <[email protected]>

Author: C-Achard

.github/workflows/test_and_deploy.yml

@@ -7,6 +7,7 @@ on:
   push:
     branches:
       - main
+      - cy/utils
     tags:
       - "v*" # Push events to matching v*, i.e. v1.0, v20.15.10
   pull_request:

napari_cellseg3d/code_models/crf.py

@@ -7,8 +7,9 @@
 Philipp Krähenbühl and Vladlen Koltun
 NIPS 2011
 
-Implemented using the pydense libary available at https://github.com/kodalli/pydensecrf.
+Implemented using the pydense library available at https://github.com/kodalli/pydensecrf.
 """
+
 from warnings import warn
 
 try:

napari_cellseg3d/code_models/workers_utils.py

@@ -151,7 +151,7 @@ def __init__(self, file_location):
         except ImportError as e:
             logger.error("ONNX is not installed but ONNX model was loaded")
             logger.error(e)
-            msg = "PLEASE INSTALL ONNX CPU OR GPU USING pip install napari-cellseg3d[onnx-cpu] OR napari-cellseg3d[onnx-gpu]"
+            msg = "PLEASE INSTALL ONNX CPU OR GPU USING: pip install napari-cellseg3d[onnx-cpu] OR pip install napari-cellseg3d[onnx-gpu]"
             logger.error(msg)
             raise ImportError(msg) from e
 
@@ -177,6 +177,8 @@ def to(self, device):
 
 
 class QuantileNormalizationd(MapTransform):
+    """MONAI-style dict transform to normalize each image in a batch individually by quantile normalization."""
+
     def __init__(self, keys, allow_missing_keys: bool = False):
         super().__init__(keys, allow_missing_keys)
 
@@ -199,6 +201,8 @@ def normalizer(self, image: torch.Tensor):
 
 
 class QuantileNormalization(Transform):
+    """MONAI-style transform to normalize each image in a batch individually by quantile normalization."""
+
     def __call__(self, img):
         return utils.quantile_normalization(img)
 

napari_cellseg3d/code_plugins/plugin_base.py

@@ -446,9 +446,10 @@ def _update_default_paths(self, path=None):
                 self.extract_dataset_paths(self.labels_filepaths),
                 self.results_path,
             ]
-            return
+            return utils.parse_default_path(self._default_path)
         if Path(path).is_dir():
             self._default_path.append(path)
+        return utils.parse_default_path(self._default_path)
 
     @staticmethod
     def extract_dataset_paths(paths):
@@ -458,3 +459,37 @@ def extract_dataset_paths(paths):
         if paths[0] is None:
             return None
         return str(Path(paths[0]).parent)
+
+
+class BasePluginUtils(BasePluginFolder):
+    """Small subclass used to have centralized widgets layer and result path selection in utilities"""
+
+    save_path = None
+    utils_default_paths = [Path.home() / "cellseg3d"]
+
+    def __init__(
+        self,
+        viewer: napari.viewer.Viewer,
+        parent=None,
+        loads_images=True,
+        loads_labels=True,
+    ):
+        super().__init__(
+            viewer=viewer,
+            loads_images=loads_images,
+            loads_labels=loads_labels,
+            parent=parent,
+        )
+        if parent is not None:
+            self.setParent(parent)
+        self.parent = parent
+
+        self.layer = None
+        """Should contain the layer associated with the results of the utility widget"""
+
+    def _update_default_paths(self, path=None):
+        """Override to also update utilities' pool of default paths"""
+        default_path = super()._update_default_paths(path)
+        logger.debug(f"Trying to update default with {default_path}")
+        if default_path is not None:
+            self.utils_default_paths.append(default_path)