diff --git a/extensions/chaeo/conf/testing.py b/extensions/chaeo/conf/testing.py
index 00389e08d8adbe01a3bd14c19f76342a9c00ccea..c151234c73607bf5f8d5660b23d1187a80f72b84 100644
--- a/extensions/chaeo/conf/testing.py
+++ b/extensions/chaeo/conf/testing.py
@@ -15,7 +15,10 @@ pixel_classifier = {
}
pipeline_params = {
- 'threshold': 0.6,
+ 'segmentation_channel': 0,
+ 'patches_channel': 4,
+ 'pxmap_channel': 0,
+ 'pxmap_threshold': 0.6,
}
output_path = root / 'testing' / 'output' / 'chaeo'
diff --git a/extensions/chaeo/tests/test_zstack.py b/extensions/chaeo/tests/test_zstack.py
index 53cdac09349611a2e801d2a7d96e5a13056da5d6..c15fdfee209fce56d09d0b49a846de2c49b8acc9 100644
--- a/extensions/chaeo/tests/test_zstack.py
+++ b/extensions/chaeo/tests/test_zstack.py
@@ -6,30 +6,41 @@ from conf.testing import output_path
from extensions.chaeo.conf.testing import multichannel_zstack, pixel_classifier, pipeline_params
from extensions.chaeo.products import export_patches_from_zstack, export_multichannel_patches_from_zstack, export_patch_masks_from_zstack
+from extensions.chaeo.workflows import infer_object_map_from_zstack
from extensions.chaeo.zmask import build_zmask_from_object_mask
from model_server.accessors import generate_file_accessor, InMemoryDataAccessor, write_accessor_data_to_file
from extensions.ilastik.models import IlastikPixelClassifierModel
+from model_server.models import DummyInstanceSegmentationModel
class TestZStackDerivedDataProducts(unittest.TestCase):
def setUp(self) -> None:
+
# need test data incl obj map
self.stack = generate_file_accessor(multichannel_zstack['path'])
+ self.stack_ch_seg = self.stack.get_one_channel_data(pipeline_params['segmentation_channel'])
+ self.stack_ch_pa = self.stack.get_one_channel_data(pipeline_params['patches_channel'])
- pxmodel = IlastikPixelClassifierModel(
+ self.pxmodel = IlastikPixelClassifierModel(
{'project_file': pixel_classifier['path']},
)
- mip = InMemoryDataAccessor(self.stack.get_one_channel_data(channel=0).data.max(axis=-1, keepdims=True))
- self.pxmap, result = pxmodel.infer(mip)
+ mip = InMemoryDataAccessor(
+ self.stack_ch_seg.data.max(axis=-1, keepdims=True)
+ )
+ pxmap, _ = self.pxmodel.infer(mip)
- # write_accessor_data_to_file(output_path / 'pxmap.tif', self.pxmap)
- self.obmap = InMemoryDataAccessor(self.pxmap.data > pipeline_params['threshold'])
- # write_accessor_data_to_file(output_path / 'obmap.tif', self.obmap)
+ write_accessor_data_to_file(output_path / 'pxmap.tif', pxmap)
+ self.seg_mask = InMemoryDataAccessor(
+ pxmap.get_one_channel_data(
+ pipeline_params['pxmap_channel']
+ ).data > pipeline_params['pxmap_threshold']
+ )
+ write_accessor_data_to_file(output_path / 'seg_mask.tif', self.seg_mask)
def test_zmask_makes_correct_boxes(self, mask_type='boxes', **kwargs):
zmask, meta, df, interm = build_zmask_from_object_mask(
- self.obmap.get_one_channel_data(0),
- self.stack.get_one_channel_data(0),
+ self.seg_mask,
+ self.stack_ch_pa,
mask_type=mask_type,
**kwargs,
)
@@ -58,10 +69,10 @@ class TestZStackDerivedDataProducts(unittest.TestCase):
return zmask, meta
def test_zmask_works_on_non_zstacks(self, **kwargs):
- acc_zstack_slice = InMemoryDataAccessor(self.stack.data[:, :, 0, 0])
+ acc_zstack_slice = InMemoryDataAccessor(self.stack_ch_pa.data[:, :, :, 0])
self.assertEqual(acc_zstack_slice.nz, 1)
zmask, meta, df, interm = build_zmask_from_object_mask(
- self.obmap.get_one_channel_data(0),
+ self.seg_mask,
acc_zstack_slice,
mask_type='boxes',
**kwargs,
@@ -85,7 +96,7 @@ class TestZStackDerivedDataProducts(unittest.TestCase):
)
files = export_patches_from_zstack(
output_path / '2d_patches',
- self.stack.get_one_channel_data(channel=1),
+ self.stack_ch_pa,
meta,
draw_bounding_box=True,
)
@@ -98,15 +109,15 @@ class TestZStackDerivedDataProducts(unittest.TestCase):
)
files = export_patches_from_zstack(
output_path / '3d_patches',
- self.stack.get_one_channel_data(4),
+ self.stack_ch_pa,
meta,
make_3d=True)
self.assertGreaterEqual(len(files), 1)
def test_flatten_image(self):
zmask, meta, df, interm = build_zmask_from_object_mask(
- self.obmap.get_one_channel_data(0),
- self.stack.get_one_channel_data(4),
+ self.seg_mask,
+ self.stack_ch_pa,
mask_type='boxes',
)
@@ -188,4 +199,20 @@ class TestZStackDerivedDataProducts(unittest.TestCase):
InMemoryDataAccessor(self.stack.data),
meta,
)
- self.assertGreaterEqual(len(files), 1)
\ No newline at end of file
+ self.assertGreaterEqual(len(files), 1)
+
+ def test_object_map_workflow(self):
+ pp = pipeline_params
+ models = [
+ self.pxmodel,
+ DummyInstanceSegmentationModel(),
+ ]
+ infer_object_map_from_zstack(
+ multichannel_zstack['path'],
+ output_path,
+ models,
+ pxmap_foreground_channel=pp['pxmap_channel'],
+ pxmap_threshold=pp['pxmap_threshold'],
+ segmentation_channel=pp['segmentation_channel'],
+ patches_channel=pp['patches_channel'],
+ )
\ No newline at end of file
diff --git a/extensions/chaeo/workflows.py b/extensions/chaeo/workflows.py
index 50428f09b0c7f9a6f51e89ef586598bc016f9284..284a773a34fdd5c986ad131358318896447e358e 100644
--- a/extensions/chaeo/workflows.py
+++ b/extensions/chaeo/workflows.py
@@ -19,7 +19,7 @@ from extensions.chaeo.zmask import project_stack_from_focal_points, RoiSet
from extensions.ilastik.models import IlastikPixelClassifierModel
from model_server.accessors import generate_file_accessor, InMemoryDataAccessor, write_accessor_data_to_file
-from model_server.models import Model
+from model_server.models import Model, InstanceSegmentationModel, SemanticSegmentationModel
from model_server.process import rescale
from model_server.workflows import Timer
@@ -240,14 +240,14 @@ def infer_object_map_from_zstack(
zmask_type: str = 'boxes',
zmask_filters: Dict = None,
# zmask_expand_box_by: int = None,
- exports: RoiSetExportParams = None,
+ exports: RoiSetExportParams = RoiSetExportParams(),
**kwargs,
) -> Dict:
assert len(models) == 2
pixel_classifier = models[0]
- assert isinstance(pixel_classifier, IlastikPixelClassifierModel)
+ assert isinstance(pixel_classifier, SemanticSegmentationModel)
object_classifier = models[1]
- assert isinstance(object_classifier, PatchStackObjectClassifier)
+ assert isinstance(object_classifier, InstanceSegmentationModel)
ti = Timer()
stack = generate_file_accessor(Path(input_file_path))
@@ -286,13 +286,10 @@ def infer_object_map_from_zstack(
stack.get_one_channel_data(segmentation_channel),
mask_type=zmask_type,
filters=zmask_filters,
- expand_box_by=kwargs['zmask_expand_box_by'],
+ expand_box_by=kwargs.get('zmask_expand_box_by', (0, 0)),
)
ti.click('generate_zmasks')
- # record pixel scale
- rois.df['pixel_scale_in_micrometers'] = float(stack.pixel_scale_in_micrometers.get('X'))
-
# ti, stack, fstem, obmask, pxmap, obj_table = get_zmask_meta(
# input_file_path,
# pixel_classifier,
@@ -341,13 +338,13 @@ def infer_object_map_from_zstack(
# output_map[labels_map == object_id] = object_class
# meta.append({'object_id': ii, 'object_class': object_id})
- object_class_map = rois.classify_by(patches_channel)
+ object_class_map = rois.classify_by(patches_channel, object_classifier)
# TODO: add ZMaskObjectTable method to export object map
output_path = Path(output_folder_path) / ('obj_classes_' + (fstem + '.tif'))
write_accessor_data_to_file(
output_path,
- InMemoryDataAccessor(object_class_map)
+ object_class_map
)
ti.click('export_object_classes')
diff --git a/extensions/chaeo/zmask.py b/extensions/chaeo/zmask.py
index 69e128ef871fcd47ed9e385a6da9e128c38f2a76..1f93151a437244f0c1f28700ddf56d82840681e4 100644
--- a/extensions/chaeo/zmask.py
+++ b/extensions/chaeo/zmask.py
@@ -152,7 +152,7 @@ class RoiSet(object):
return projected
def get_raw_patches(self, channel):
- return get_patches_from_zmask_meta(self.acc_raw(channel), self.zmask_meta)
+ return get_patches_from_zmask_meta(self.acc_raw, self.zmask_meta)
def get_patch_masks(self):
return get_patch_masks_from_zmask_meta(self.acc_raw, self.zmask_meta)
diff --git a/model_server/api.py b/model_server/api.py
index a1c785313881d594e49fa8f335f24664e4429bf2..79bd68fcc0e96af6f07bbacce5d96dd76ecab97c 100644
--- a/model_server/api.py
+++ b/model_server/api.py
@@ -1,6 +1,6 @@
from fastapi import FastAPI, HTTPException
-from model_server.models import DummySegmentationModel
+from model_server.models import DummySemanticSegmentationModel
from model_server.session import Session, InvalidPathError
from model_server.validators import validate_workflow_inputs
from model_server.workflows import classify_pixels
@@ -67,7 +67,7 @@ def list_active_models():
@app.put('/models/dummy/load/')
def load_dummy_model() -> dict:
- return {'model_id': session.load_model(DummySegmentationModel)}
+ return {'model_id': session.load_model(DummySemanticSegmentationModel)}
@app.put('/workflows/segment')
def infer_img(model_id: str, input_filename: str, channel: int = None) -> dict:
diff --git a/tests/test_api.py b/tests/test_api.py
index e846be74218912a97b346d862bdce4850c0eb733..89ab62e449c399f890cb42138252c099d91a0c95 100644
--- a/tests/test_api.py
+++ b/tests/test_api.py
@@ -4,7 +4,7 @@ import requests
import unittest
from conf.testing import czifile
-from model_server.models import DummySegmentationModel
+from model_server.models import DummySemanticSegmentationModel
class TestServerBaseClass(unittest.TestCase):
def setUp(self) -> None:
diff --git a/tests/test_workflow.py b/tests/test_workflow.py
index a88d8791eb4cba9ce6544124e51edacfa3a79c0a..7f6474c0038739358bdf704bec6a369c13266abc 100644
--- a/tests/test_workflow.py
+++ b/tests/test_workflow.py
@@ -1,13 +1,13 @@
import unittest
from conf.testing import czifile, output_path
-from model_server.models import DummySegmentationModel
+from model_server.models import DummySemanticSegmentationModel
from model_server.workflows import classify_pixels
class TestGetSessionObject(unittest.TestCase):
def setUp(self) -> None:
- self.model = DummySegmentationModel()
+ self.model = DummySemanticSegmentationModel()
def test_single_session_instance(self):
result = classify_pixels(czifile['path'], self.model, output_path, channel=2)