Moved project file into model.params; removed autogeneration of segmentation...

Moved project file into model.params; removed autogeneration of segmentation model from pixel predictions model

model_server/extensions/ilastik/models.py

@@ -22,13 +22,13 @@ class IlastikModel(Model):
         :param enforce_embedded:
             raise an error if all input data are not embedded in the project file, i.e. on the filesystem
         """
-        self.project_file = Path(params['project_file'])
+        self.params = params
+        pf = Path(params['project_file'])
         self.enforce_embedded = enforce_embedded
-        params['project_file'] = self.project_file.__str__()
-        if self.project_file.is_absolute():
-            pap = self.project_file
+        if pf.is_absolute():
+            pap = pf
         else:
-            pap = model_server.extensions.ilastik.conf.paths['project_files'] / self.project_file
+            pap = model_server.extensions.ilastik.conf.paths['project_files'] / pf
         self.project_file_abspath = pap
         if not pap.exists():
             raise FileNotFoundError(f'Project file does not exist: {pap}')
@@ -62,7 +62,7 @@ class IlastikModel(Model):
             assert True
         if not isinstance(shell.workflow, self.get_workflow()):
             raise ParameterExpectedError(
-                f'Ilastik project file {self.project_file} does not describe an instance of {self.__class__}'
+                f'Ilastik project file {self.project_file_abspath} does not describe an instance of {self.__class__}'
             )
         self.shell = shell
 
@@ -300,27 +300,6 @@ class IlastikObjectClassifierFromPixelPredictionsModel(IlastikModel, ImageToImag
         obmap, _ = self.infer(img, mask)
         return obmap
 
-    def make_instance_segmentation_model(self, px_ch: int):
-        """
-        Generate an instance segmentation model, i.e. one that takes binary masks instead of pixel probabilities as a
-        second input.
-        :param px_ch: channel of pixel probability map to use
-        :return:
-            InstanceSegmentationModel object
-        """
-        class _Mod(self.__class__, InstanceSegmentationModel):
-            def label_instance_class(
-                    self, img: GenericImageDataAccessor, mask: GenericImageDataAccessor, **kwargs
-            ) -> GenericImageDataAccessor:
-                if mask.dtype == 'bool':
-                    norm_mask = 1.0 * mask.data
-                else:
-                    norm_mask = mask.data / np.iinfo(mask.dtype).max
-                norm_mask_acc = mask._derived_accessor(norm_mask.astype('float32'))
-                return super().label_instance_class(img, norm_mask_acc, pixel_classification_channel=px_ch)
-        return _Mod(params={'project_file': self.project_file})
-
-
 
 class Error(Exception):
     pass