diff --git a/model_server/extensions/chaeo/roiset.py b/model_server/base/roiset.py
similarity index 94%
rename from model_server/extensions/chaeo/roiset.py
rename to model_server/base/roiset.py
index c478ff2598527216e85857b9f448eeea73372ae7..bf40227a0629c2d3747e1faf20360565fa664a63 100644
--- a/model_server/extensions/chaeo/roiset.py
+++ b/model_server/base/roiset.py
@@ -1,9 +1,11 @@
from math import sqrt, floor
from pathlib import Path
+from typing import List, Union
from uuid import uuid4
import numpy as np
import pandas as pd
+from pydantic import BaseModel
from scipy.stats import moment
from skimage.filters import sobel
@@ -15,10 +17,51 @@ from model_server.base.accessors import GenericImageDataAccessor, InMemoryDataAc
from model_server.base.models import InstanceSegmentationModel
from model_server.base.process import pad, rescale, resample_to_8bit, make_rgb
from model_server.extensions.chaeo.annotators import draw_box_on_patch, draw_contours_on_patch, draw_boxes_on_3d_image
-from model_server.extensions.chaeo.params import RoiFilter, RoiSetMetaParams, RoiSetExportParams
from model_server.extensions.chaeo.accessors import write_patch_to_file, MonoPatchStack, Multichannel3dPatchStack
from model_server.extensions.chaeo.process import mask_largest_object
+class PatchParams(BaseModel):
+ draw_bounding_box: bool = False
+ draw_contour: bool = False
+ draw_mask: bool = False
+ rescale_clip: float = 0.001
+ focus_metric: str = 'max_sobel'
+ rgb_overlay_channels: List[Union[int, None]] = [None, None, None]
+ rgb_overlay_weights: List[float] = [1.0, 1.0, 1.0]
+ pad_to: int = 256
+
+
+class AnnotatedZStackParams(BaseModel):
+ draw_label: bool = False
+
+
+class RoiFilterRange(BaseModel):
+ min: float
+ max: float
+
+
+class RoiFilter(BaseModel):
+ area: Union[RoiFilterRange, None] = None
+ solidity: Union[RoiFilterRange, None] = None
+
+
+class RoiSetMetaParams(BaseModel):
+ filters: Union[RoiFilter, None] = None
+ expand_box_by: List[int] = [128, 0]
+
+
+class RoiSetExportParams(BaseModel):
+ pixel_probabilities: bool = False
+ patches_3d: Union[PatchParams, None] = None
+ annotated_patches_2d: Union[PatchParams, None] = None
+ patches_2d: Union[PatchParams, None] = None
+ patch_masks: Union[PatchParams, None] = None
+ annotated_zstacks: Union[AnnotatedZStackParams, None] = None
+ object_classes: bool = False
+ dataframe: bool = False
+
+
+
def _get_label_ids(acc_seg_mask: GenericImageDataAccessor) -> InMemoryDataAccessor:
return InMemoryDataAccessor(label(acc_seg_mask.data[:, :, 0, 0]).astype('uint16'))
@@ -516,5 +559,3 @@ def project_stack_from_focal_points(
)
-
-
diff --git a/model_server/extensions/chaeo/params.py b/model_server/extensions/chaeo/params.py
deleted file mode 100644
index 9e06b286498a21bf1115b15f26f99b10547d9808..0000000000000000000000000000000000000000
--- a/model_server/extensions/chaeo/params.py
+++ /dev/null
@@ -1,44 +0,0 @@
-from typing import List, Union
-
-from pydantic import BaseModel
-
-
-class PatchParams(BaseModel):
- draw_bounding_box: bool = False
- draw_contour: bool = False
- draw_mask: bool = False
- rescale_clip: float = 0.001
- focus_metric: str = 'max_sobel'
- rgb_overlay_channels: List[Union[int, None]] = [None, None, None]
- rgb_overlay_weights: List[float] = [1.0, 1.0, 1.0]
- pad_to: int = 256
-
-
-class AnnotatedZStackParams(BaseModel):
- draw_label: bool = False
-
-class RoiFilterRange(BaseModel):
- min: float
- max: float
-
-class RoiFilter(BaseModel):
- area: Union[RoiFilterRange, None] = None
- solidity: Union[RoiFilterRange, None] = None
-
-
-class RoiSetMetaParams(BaseModel):
- filters: Union[RoiFilter, None] = None
- expand_box_by: List[int] = [128, 0]
-
-
-class RoiSetExportParams(BaseModel):
- pixel_probabilities: bool = False
- patches_3d: Union[PatchParams, None] = None
- annotated_patches_2d: Union[PatchParams, None] = None
- patches_2d: Union[PatchParams, None] = None
- patch_masks: Union[PatchParams, None] = None
- annotated_zstacks: Union[AnnotatedZStackParams, None] = None
- object_classes: bool = False
- dataframe: bool = False
-
-
diff --git a/model_server/extensions/chaeo/products.py b/model_server/extensions/chaeo/products.py
deleted file mode 100644
index b28b04f643122b019e912540f228c8ed20be9eeb..0000000000000000000000000000000000000000
--- a/model_server/extensions/chaeo/products.py
+++ /dev/null
@@ -1,3 +0,0 @@
-
-
-
diff --git a/model_server/extensions/chaeo/tests/test_roiset_workflow.py b/model_server/extensions/chaeo/tests/test_roiset_workflow.py
new file mode 100644
index 0000000000000000000000000000000000000000..369701def197a92e470e456142bcfade57ef2c9b
--- /dev/null
+++ b/model_server/extensions/chaeo/tests/test_roiset_workflow.py
@@ -0,0 +1,71 @@
+import unittest
+
+from model_server.base.models import DummyInstanceSegmentationModel
+from model_server.base.roiset import RoiSetMetaParams, RoiSetExportParams
+from model_server.conf.testing import output_path
+from model_server.extensions.chaeo.conf.testing import multichannel_zstack, pipeline_params
+from model_server.extensions.chaeo.workflows import infer_object_map_from_zstack
+
+from tests.test_roiset import BaseTestRoiSetMonoProducts
+
+class TestRoiSetWorkflow(BaseTestRoiSetMonoProducts, unittest.TestCase):
+
+ def test_object_map_workflow(self):
+ pp = pipeline_params
+ models = [
+ self.pxmodel,
+ DummyInstanceSegmentationModel(),
+ ]
+
+ models = {
+ 'pixel_classifier': {
+ 'model': self.pxmodel,
+ 'params': {
+ 'px_class': 0,
+ 'px_prob_threshold': 0.6,
+ }
+ },
+ 'object_classifier': {
+ 'name': 'dummy',
+ 'model': DummyInstanceSegmentationModel(),
+ }
+ }
+
+ roi_params = RoiSetMetaParams(**{
+ 'mask_type': 'boxes',
+ 'filters': {
+ 'area': {'min': 1e3, 'max': 1e8}
+ },
+ 'expand_box_by': [128, 2]
+ })
+
+ export_params = RoiSetExportParams(**{
+ 'pixel_probabilities': True,
+ 'patches_3d': {},
+ 'annotated_patches_2d': {
+ 'draw_bounding_box': True,
+ 'rgb_overlay_channels': [3, None, None],
+ 'rgb_overlay_weights': [0.2, 1.0, 1.0],
+ 'pad_to': 512,
+ },
+ 'patches_2d': {
+ 'draw_bounding_box': False,
+ 'draw_mask': False,
+ },
+ 'patch_masks': {
+ 'pad_to': 256,
+ },
+ 'annotated_zstacks': {},
+ 'object_classes': True,
+ 'dataframe': True,
+ })
+
+ infer_object_map_from_zstack(
+ multichannel_zstack['path'],
+ output_path / 'roiset' / 'workflow',
+ models,
+ segmentation_channel=pp['segmentation_channel'],
+ patches_channel=pp['patches_channel'],
+ export_params=export_params,
+ roi_params=roi_params,
+ )
\ No newline at end of file
diff --git a/model_server/extensions/chaeo/workflows.py b/model_server/extensions/chaeo/workflows.py
index 08d06adf07dbba82c84286a32d7154d1c1070ea1..b837877979017384effdb840c1f171d7e6d1d808 100644
--- a/model_server/extensions/chaeo/workflows.py
+++ b/model_server/extensions/chaeo/workflows.py
@@ -8,9 +8,9 @@ from skimage.measure import label
from skimage.morphology import dilation
from sklearn.model_selection import train_test_split
-from extensions.chaeo.params import RoiSetExportParams, RoiSetMetaParams
+from base.roiset import RoiSetMetaParams, RoiSetExportParams
from model_server.extensions.chaeo.process import mask_largest_object
-from model_server.extensions.chaeo.roiset import _get_label_ids, RoiSet
+from base.roiset import _get_label_ids, RoiSet
from model_server.base.accessors import generate_file_accessor, InMemoryDataAccessor, write_accessor_data_to_file
from model_server.base.models import Model, InstanceSegmentationModel, SemanticSegmentationModel
@@ -68,7 +68,8 @@ def infer_object_map_from_zstack(
'output_path': output_folder_path,
}
-# TODO: to app-specific ecotaxa module
+
+
def transfer_ecotaxa_labels_to_patch_stacks(
where_masks: str,
where_patches: str,
@@ -172,6 +173,4 @@ def transfer_ecotaxa_labels_to_patch_stacks(
for k in zstacks.keys():
write_accessor_data_to_file(Path(where_output) / f'zstack_{k}.tif', InMemoryDataAccessor(zstacks[k]))
- pd.DataFrame(stack_meta).to_csv(Path(where_output) / f'{dfk}_stack.csv', index=False)
-
-
+ pd.DataFrame(stack_meta).to_csv(Path(where_output) / f'{dfk}_stack.csv', index=False)
\ No newline at end of file
diff --git a/model_server/extensions/chaeo/tests/test_zstack.py b/tests/test_roiset.py
similarity index 81%
rename from model_server/extensions/chaeo/tests/test_zstack.py
rename to tests/test_roiset.py
index f3b82997482884e70e12bd341dbc732c5aa745dc..df77c111ec69b372d6778465cc119d385aae3316 100644
--- a/model_server/extensions/chaeo/tests/test_zstack.py
+++ b/tests/test_roiset.py
@@ -6,9 +6,8 @@ from pathlib import Path
from model_server.conf.testing import output_path
from model_server.extensions.chaeo.conf.testing import multichannel_zstack, pixel_classifier, pipeline_params
-from extensions.chaeo.params import RoiSetExportParams, RoiSetMetaParams
-from model_server.extensions.chaeo.workflows import infer_object_map_from_zstack
-from model_server.extensions.chaeo.roiset import _get_label_ids, RoiSet
+from model_server.base.roiset import RoiSetMetaParams
+from model_server.base.roiset import _get_label_ids, RoiSet
from model_server.base.accessors import generate_file_accessor, InMemoryDataAccessor, write_accessor_data_to_file
from model_server.extensions.ilastik.models import IlastikPixelClassifierModel
from model_server.base.models import DummyInstanceSegmentationModel
@@ -131,7 +130,7 @@ class TestRoiSetMonoProducts(BaseTestRoiSetMonoProducts, unittest.TestCase):
roiset = RoiSet(self.stack_ch_pa, id_map, params=RoiSetMetaParams(mask_type='boxes'))
df = roiset.get_df()
- from model_server.extensions.chaeo.roiset import project_stack_from_focal_points
+ from base.roiset import project_stack_from_focal_points
img = project_stack_from_focal_points(
df['centroid-0'].to_numpy(),
@@ -159,66 +158,6 @@ class TestRoiSetMonoProducts(BaseTestRoiSetMonoProducts, unittest.TestCase):
self.assertTrue(all(roiset.get_df()['classify_by_dummy_class'].unique() == [1]))
self.assertTrue(all(np.unique(roiset.object_class_maps['dummy_class'].data) == [0, 1]))
- def test_object_map_workflow(self):
- pp = pipeline_params
- models = [
- self.pxmodel,
- DummyInstanceSegmentationModel(),
- ]
-
- models = {
- 'pixel_classifier': {
- 'model': self.pxmodel,
- 'params': {
- 'px_class': 0,
- 'px_prob_threshold': 0.6,
- }
- },
- 'object_classifier': {
- 'name': 'dummy',
- 'model': DummyInstanceSegmentationModel(),
- }
- }
-
- roi_params = RoiSetMetaParams(**{
- 'mask_type': 'boxes',
- 'filters': {
- 'area': {'min': 1e3, 'max': 1e8}
- },
- 'expand_box_by': [128, 2]
- })
-
- export_params = RoiSetExportParams(**{
- 'pixel_probabilities': True,
- 'patches_3d': {},
- 'annotated_patches_2d': {
- 'draw_bounding_box': True,
- 'rgb_overlay_channels': [3, None, None],
- 'rgb_overlay_weights': [0.2, 1.0, 1.0],
- 'pad_to': 512,
- },
- 'patches_2d': {
- 'draw_bounding_box': False,
- 'draw_mask': False,
- },
- 'patch_masks': {
- 'pad_to': 256,
- },
- 'annotated_zstacks': {},
- 'object_classes': True,
- 'dataframe': True,
- })
-
- infer_object_map_from_zstack(
- multichannel_zstack['path'],
- output_path / 'roiset' / 'workflow',
- models,
- segmentation_channel=pp['segmentation_channel'],
- patches_channel=pp['patches_channel'],
- export_params=export_params,
- roi_params=roi_params,
- )
-
class TestRoiSetMultichannelProducts(BaseTestRoiSetMonoProducts, unittest.TestCase):