diff --git a/model_server/base/pipelines/roiset_obmap.py b/model_server/base/pipelines/roiset_obmap.py
index 383136755d886be4e2ff31e3f48aff96a65fc763..2b533f44be3c16104e23e6fa3c0658fae01426ec 100644
--- a/model_server/base/pipelines/roiset_obmap.py
+++ b/model_server/base/pipelines/roiset_obmap.py
@@ -1,19 +1,17 @@
from typing import Dict, Union
from fastapi import APIRouter
-import pandas as pd
-from pydantic import Field
+from pydantic import BaseModel, Field
+from ..accessors import GenericImageDataAccessor
+from ..pipelines.segment_zproj import segment_zproj_pipeline
+from ..pipelines.shared import call_pipeline
+from ..roiset import get_label_ids, RoiSet, RoiSetMetaParams, RoiSetExportParams
+from ..session import session
-from model_server.base.accessors import GenericImageDataAccessor, PatchStack
-from model_server.base.pipelines.params import PipelineParams, PipelineRecord
-from model_server.base.pipelines.segment import segment_pipeline
-from model_server.base.pipelines.util import call_pipeline
-from model_server.base.roiset import get_label_ids, RoiSet, RoiSetMetaParams, RoiSetExportParams
-from model_server.base.session import session
-from model_server.base.util import PipelineTrace
+from ..pipelines.shared import PipelineTrace, PipelineParams, PipelineRecord
-from model_server.base.models import Model, InstanceSegmentationModel, SemanticSegmentationModel
+from ..models import Model, InstanceSegmentationModel
router = APIRouter(
prefix='/pipelines',
@@ -21,6 +19,16 @@ router = APIRouter(
)
class RoiSetObjectMapParams(PipelineParams):
+ class _SegmentationParams(BaseModel):
+ channel: int = Field(
+ None,
+ description='Channel of input image to use for solving segmentation; use all channels if empty'
+ )
+ zi: Union[int, None] = Field(
+ None,
+ description='z coordinate to use on input image when solving segmentation; apply MIP if empty',
+ )
+
accessor_id: str = Field(
description='ID(s) of previously loaded accessor(s) to use as pipeline input'
)
@@ -35,15 +43,12 @@ class RoiSetObjectMapParams(PipelineParams):
None,
description='Pixel classifier used to derive channel(s) as additional inputs to object classification'
)
- segmentation_channel: int = Field(
- description='Channel of input image to use for solving segmentation'
- )
patches_channel: int = Field(
description='Channel of input image used in patches sent to object classifier'
)
- zmask_zindex: Union[int, None] = Field(
- None,
- description='z coordinate to use on input image when solving segmentation; apply MIP if empty',
+ segmentation: _SegmentationParams = Field(
+ _SegmentationParams(),
+ description='Parameters used to solve segmentation'
)
roi_params: RoiSetMetaParams = RoiSetMetaParams(**{
'mask_type': 'boxes',
@@ -105,22 +110,17 @@ def roiset_object_map_pipeline(
models: Dict[str, Model],
**k
) -> (PipelineTrace, RoiSet):
- if not isinstance(models['pixel_classifier_segmentation_model'], SemanticSegmentationModel):
- raise IncompatibleModelsError('Expecting a pixel classification model')
-
d = PipelineTrace(accessors['accessor'])
- zmi = k['zmask_zindex']
- sch = k['segmentation_channel']
- if isinstance(zmi, int):
- assert 0 < zmi < d.last.nz
- d['mip'] = d.last.get_mono(channel=sch).get_zi(zmi)
- else:
- d['mip'] = d.last.get_mono(channel=sch).apply(lambda x: x.max(axis=-1, keepdims=True))
+ d['mask'] = segment_zproj_pipeline(
+ accessors,
+ {'model': models['pixel_classifier_segmentation_model']},
+ **k['segmentation'],
+ ).last
- d['mip_mask'] = models['pixel_classifier_segmentation_model'].label_pixel_class(d.last)
- d['segmentation'] = get_label_ids(d.last)
- rois = RoiSet.from_object_ids(d['input'], d['segmentation'], RoiSetMetaParams(**k['roi_params']))
+ # d['mask'] = models['pixel_classifier_segmentation_model'].label_pixel_class(d.last)
+ d['labeled'] = get_label_ids(d.last)
+ rois = RoiSet.from_object_ids(d['input'], d['labeled'], RoiSetMetaParams(**k['roi_params']))
# optionally run an object classifier if specified
if obmod := models.get('object_classifier_model'):
@@ -134,9 +134,3 @@ def roiset_object_map_pipeline(
d[obmod_name] = rois.get_object_class_map(obmod_name)
return d, rois
-
-class Error(Exception):
- pass
-
-class IncompatibleModelsError(Error):
- pass
\ No newline at end of file
diff --git a/tests/test_ilastik/test_roiset_workflow.py b/tests/test_ilastik/test_roiset_workflow.py
index bfe51ed0dd166eac173ffbb2319e07604b87c7f2..31b0c0d6e4a3b590c23f629120c0b981020e478b 100644
--- a/tests/test_ilastik/test_roiset_workflow.py
+++ b/tests/test_ilastik/test_roiset_workflow.py
@@ -65,7 +65,7 @@ class BaseTestRoiSetMonoProducts(object):
return {
'mask_type': 'boxes',
'filters': {
- 'area': {'min': 1e3, 'max': 1e8}
+ 'area': {'min': 1e0, 'max': 1e8}
},
'expand_box_by': [128, 2]
}
@@ -97,7 +97,9 @@ class TestRoiSetWorkflow(BaseTestRoiSetMonoProducts, unittest.TestCase):
'accessor_id': 'acc_id',
'pixel_classifier_segmentation_model_id': 'px_id',
'object_classifier_model_id': 'ob_id',
- 'segmentation_channel': test_params['segmentation_channel'],
+ 'segmentation': {
+ 'channel': test_params['segmentation_channel'],
+ },
'patches_channel': test_params['patches_channel'],
'roi_params': self._get_roi_params(),
'export_params': self._get_export_params(),
@@ -108,13 +110,16 @@ class TestRoiSetWorkflow(BaseTestRoiSetMonoProducts, unittest.TestCase):
params = RoiSetObjectMapParams(
**self._pipeline_params(),
)
- trace, _ = roiset_object_map_pipeline(
+ trace, rois = roiset_object_map_pipeline(
{'accessor': acc_in},
{f'{k}_model': v['model'] for k, v in self._get_models().items()},
**params.dict()
)
+ trace.write_interm(Path(output_path) / 'trace', 'roiset_worfklow_trace', skip_first=False, skip_last=False)
self.assertTrue('ob_id' in trace.keys())
+ self.assertEqual(len(trace['labeled']._unique()[0]), 14)
+ self.assertEqual(rois.count, 13)
self.assertEqual(len(trace['ob_id']._unique()[0]), 2)