Start online validation of autogenerated model; but need to make inference...

Start online validation of autogenerated model; but need to make inference model that takes binary inputs

extensions/chaeo/examples/transfer_labels_to_ilastik_object_classifier.py

@@ -141,11 +141,17 @@ def generate_ilastik_object_classifier(template_ilp, where: str, lane=0):
     return new_ilp
 
 if __name__ == '__main__':
+    root =  Path('c:/Users/rhodes/projects/proj0011-plankton-seg/')
+    template_ilp = root / 'exp0014/template_obj.ilp'
+    where_patch_stack = root / 'exp0009/output/labeled_patches-20231016-0002'
+
     new_ilp = generate_ilastik_object_classifier(
-        'c:/Users/rhodes/projects/proj0011-plankton-seg/exp0014/template_obj.ilp',
-        'c:/Users/rhodes/projects/proj0011-plankton-seg/exp0009/output/labeled_patches-20231016-0002'
+        template_ilp,
+        where_patch_stack,
     )
 
+    train_zstack = generate_file_accessor(where_patch_stack / 'zstack_train_raw.tif')
     mod = IlastikObjectClassifierModel({'project_file': new_ilp})
 
+
     print(mod.project_file_abspath)
\ No newline at end of file

extensions/ilastik/models.py

@@ -14,7 +14,10 @@ class IlastikImageToImageModel(ImageToImageModel):
     def __init__(self, params, autoload=True):
         self.project_file = Path(params['project_file'])
         params['project_file'] = self.project_file.__str__()
-        pap = extensions.ilastik.conf.paths['project_files'] / self.project_file
+        if self.project_file.is_absolute():
+            pap = self.project_file
+        else:
+            pap = extensions.ilastik.conf.paths['project_files'] / self.project_file
         self.project_file_abspath = pap
         if not pap.exists():
             raise FileNotFoundError(f'Project file does not exist: {pap}')