Pass notebook filename and not path to load an ilastik model; assumes project...

Pass notebook filename and not path to load an ilastik model; assumes project files are in conf.server.paths['ilastik']

conf/server.py

@@ -9,8 +9,8 @@ paths = {
         'inbound': root / 'images' / 'inbound',
         'outbound': root / 'images' / 'outbound',
     },
-    'ilastik' : {
-        'projects' : root / 'ilastik'
+    'ilastik': {
+        'projects': root / 'ilastik'
     }
 }
 

conf/testing.py

@@ -11,9 +11,14 @@ czifile = {
     'z': 1,
 }
 
+# ilastik = {
+#     'pixel_classifier': root / 'testdata' / 'ilastik' / 'demo_px.ilp',
+#     'object_classifier': root / 'testdata' / 'ilastik' / 'demo_obj.ilp',
+# }
+
 ilastik = {
-    'pixel_classifier': root / 'testdata' / 'ilastik' / 'demo_px.ilp',
-    'object_classifier': root / 'testdata' / 'ilastik' / 'demo_obj.ilp',
+    'pixel_classifier': 'demo_px.ilp',
+    'object_classifier': 'demo_obj.ilp',
 }
 
 output_path = root / 'testing_output'

model_server/ilastik.py

 import os
+import pathlib
 
 import numpy as np
 import vigra
 
+import conf.server
 from model_server.image import GenericImageDataAccessor, InMemoryDataAccessor
 from model_server.model import ImageToImageModel, ParameterExpectedError
 
@@ -10,9 +12,13 @@ from model_server.model import ImageToImageModel, ParameterExpectedError
 class IlastikImageToImageModel(ImageToImageModel):
 
     def __init__(self, params, autoload=True):
-        if 'project_file' not in params or not os.path.exists(params['project_file']):
-            raise ParameterExpectedError('Ilastik model expects a project (*.ilp) file')
         self.project_file = str(params['project_file'])
+        self.project_file_abspath = pathlib.Path(
+            conf.server.paths['ilastik']['projects'] / self.project_file,
+        )
+        if 'project_file' not in params or not self.project_file_abspath.exists():
+            raise ParameterExpectedError('Ilastik model expects a project (*.ilp) file')
+
         self.shell = None
         super().__init__(autoload, params)
 
@@ -28,7 +34,7 @@ class IlastikImageToImageModel(ImageToImageModel):
 
         args = app.parse_args([])
         args.headless = True
-        args.project = self.project_file
+        args.project = self.project_file_abspath.__str__()
         shell = app.main(args)
 
         if not isinstance(shell.workflow, self.get_workflow()):

tests/test_ilastik.py

@@ -3,7 +3,7 @@ import unittest
 
 import numpy as np
 
-from conf.testing import czifile, ilastik, output_path
+import conf.testing
 from model_server.image import CziImageFileAccessor, InMemoryDataAccessor, write_accessor_data_to_file
 from model_server.ilastik import IlastikObjectClassifierModel, IlastikPixelClassifierModel
 from model_server.model import Model
@@ -12,7 +12,7 @@ from tests.test_api import TestServerBaseClass
 
 class TestIlastikPixelClassification(unittest.TestCase):
     def setUp(self) -> None:
-        self.cf = CziImageFileAccessor(czifile['path'])
+        self.cf = CziImageFileAccessor(conf.testing.czifile['path'])
 
 
     def test_faulthandler(self): # recreate error that is messing up ilastik
@@ -25,18 +25,23 @@ class TestIlastikPixelClassification(unittest.TestCase):
 
 
     def test_raise_error_if_autoload_disabled(self):
-        model = IlastikPixelClassifierModel({'project_file': ilastik['pixel_classifier']}, autoload=False)
+        model = IlastikPixelClassifierModel(
+            {'project_file': conf.testing.ilastik['pixel_classifier']},
+            autoload=False
+        )
         w = 512
         h = 256
 
         input_img = InMemoryDataAccessor(data=np.random.rand(w, h, 1, 1))
 
         with self.assertRaises(AttributeError):
-            pxmap , _= model.infer(input_img)
+            pxmap, _ = model.infer(input_img)
 
 
     def test_run_pixel_classifier_on_random_data(self):
-        model = IlastikPixelClassifierModel({'project_file': ilastik['pixel_classifier']})
+        model = IlastikPixelClassifierModel(
+            {'project_file': conf.testing.ilastik['pixel_classifier']},
+        )
         w = 512
         h = 256
 
@@ -48,12 +53,16 @@ class TestIlastikPixelClassification(unittest.TestCase):
 
     def test_run_pixel_classifier(self):
         channel = 0
-        model = IlastikPixelClassifierModel({'project_file': ilastik['pixel_classifier']})
-        cf = CziImageFileAccessor(czifile['path'])
+        model = IlastikPixelClassifierModel(
+            {'project_file': conf.testing.ilastik['pixel_classifier']}
+        )
+        cf = CziImageFileAccessor(
+            conf.testing.czifile['path']
+        )
         mono_image = cf.get_one_channel_data(channel)
 
-        self.assertEqual(mono_image.shape_dict['X'], czifile['w'])
-        self.assertEqual(mono_image.shape_dict['Y'], czifile['h'])
+        self.assertEqual(mono_image.shape_dict['X'], conf.testing.czifile['w'])
+        self.assertEqual(mono_image.shape_dict['Y'], conf.testing.czifile['h'])
         self.assertEqual(mono_image.shape_dict['C'], 1)
         self.assertEqual(mono_image.shape_dict['Z'], 1)
 
@@ -64,7 +73,7 @@ class TestIlastikPixelClassification(unittest.TestCase):
         self.assertEqual(pxmap.shape_dict['Z'], 1)
         self.assertTrue(
             write_accessor_data_to_file(
-                output_path / f'pxmap_{cf.fpath.stem}_ch{channel}.tif',
+                conf.testing.output_path / f'pxmap_{cf.fpath.stem}_ch{channel}.tif',
                 pxmap
             )
         )
@@ -74,13 +83,15 @@ class TestIlastikPixelClassification(unittest.TestCase):
 
     def test_run_object_classifier(self):
         self.test_run_pixel_classifier()
-        fp = czifile['path']
-        model = IlastikObjectClassifierModel({'project_file': ilastik['object_classifier']})
+        fp = conf.testing.czifile['path']
+        model = IlastikObjectClassifierModel(
+            {'project_file': conf.testing.ilastik['object_classifier']}
+        )
         objmap, _ = model.infer(self.mono_image, self.pxmap)
 
         self.assertTrue(
             write_accessor_data_to_file(
-                output_path / f'obmap_{fp.stem}.tif',
+                conf.testing.output_path / f'obmap_{fp.stem}.tif',
                 objmap,
             )
         )
@@ -88,9 +99,11 @@ class TestIlastikPixelClassification(unittest.TestCase):
 
     def test_ilastik_pixel_classification_as_workflow(self):
         result = infer_image_to_image(
-            czifile['path'],
-            IlastikPixelClassifierModel({'project_file': ilastik['pixel_classifier']}),
-            output_path,
+            conf.testing.czifile['path'],
+            IlastikPixelClassifierModel(
+                {'project_file': conf.testing.ilastik['pixel_classifier']}
+            ),
+            conf.testing.output_path,
             channel=0,
         )
         self.assertTrue(result.success)
@@ -100,7 +113,7 @@ class TestIlastikOverApi(TestServerBaseClass):
     def test_load_ilastik_pixel_model(self):
         resp_load = requests.put(
             self.uri + 'models/ilastik/pixel_classification/load/',
-            params={'project_file': str(ilastik['pixel_classifier'])},
+            params={'project_file': str(conf.testing.ilastik['pixel_classifier'])},
         )
         model_id = resp_load.json()['model_id']
 
@@ -116,7 +129,7 @@ class TestIlastikOverApi(TestServerBaseClass):
     def test_load_ilastik_object_model(self):
         resp_load = requests.put(
             self.uri + 'models/ilastik/object_classification/load/',
-            params={'project_file': str(ilastik['object_classifier'])},
+            params={'project_file': str(conf.testing.ilastik['object_classifier'])},
         )
         model_id = resp_load.json()['model_id']
 
@@ -134,8 +147,8 @@ class TestIlastikOverApi(TestServerBaseClass):
             self.uri + f'infer/from_image_file',
             params={
                 'model_id': model_id,
-                'input_filename': czifile['filename'],
-                'channel': 2,
+                'input_filename': conf.testing.czifile['filename'],
+                'channel': 0,
             },
         )
         self.assertEqual(resp_infer.status_code, 200, resp_infer.content.decode())