From 8254cad584be34f1aa48158e5aa2529388e8a95a Mon Sep 17 00:00:00 2001
From: Christopher Rhodes <christopher.rhodes@embl.de>
Date: Thu, 28 Mar 2024 18:37:26 +0100
Subject: [PATCH] Implementing alternative dataframe generation where
z-positions are in object map, i.e. do not need to be de-projected from raw
---
model_server/base/roiset.py | 41 ++++++++++++++++++++++++-----------
tests/test_roiset.py | 43 +++++++++++++++++++++++++------------
2 files changed, 58 insertions(+), 26 deletions(-)
diff --git a/model_server/base/roiset.py b/model_server/base/roiset.py
index 236d742a..4607b72b 100644
--- a/model_server/base/roiset.py
+++ b/model_server/base/roiset.py
@@ -154,29 +154,46 @@ class RoiSet(object):
return self._df.itertuples(name='Roi')
@staticmethod
- def make_df(acc_raw, acc_obj_ids, expand_box_by) -> pd.DataFrame:
+ def make_df(acc_raw, acc_obj_ids, expand_box_by, deproject=True) -> pd.DataFrame:
"""
Build dataframe associate object IDs with summary stats
:param acc_raw: accessor to raw image data
:param acc_obj_ids: accessor to map of object IDs
:param expand_box_by: number of pixels to expand bounding box in all directions (without exceeding image boundary)
+ :param deproject: assign object's z-position based on argmax of raw data if True
:return: pd.DataFrame
"""
# build dataframe of objects, assign z index to each object
- argmax = acc_raw.data.argmax(axis=3, keepdims=True)[:, :, 0, 0].astype('uint16')
- df = (
- pd.DataFrame(
- regionprops_table(
- acc_obj_ids.data[:, :, 0, 0],
- intensity_image=argmax,
- properties=('label', 'area', 'intensity_mean', 'solidity', 'bbox', 'centroid')
+ if deproject:
+ assert acc_obj_ids.nz == 1, 'Can only deproject a 2D object identity map'
+ argmax = acc_raw.data.argmax(axis=3, keepdims=True)[:, :, 0, 0].astype('uint16')
+ df = (
+ pd.DataFrame(
+ regionprops_table(
+ acc_obj_ids.data[:, :, 0, 0],
+ intensity_image=argmax,
+ properties=('label', 'area', 'intensity_mean', 'solidity', 'bbox', 'centroid')
+ )
+ )
+ .rename(
+ columns={'bbox-0': 'y0', 'bbox-1': 'x0', 'bbox-2': 'y1', 'bbox-3': 'x1', }
)
)
- .rename(
- columns={'bbox-0': 'y0', 'bbox-1': 'x0', 'bbox-2': 'y1', 'bbox-3': 'x1', }
+ df['zi'] = df['intensity_mean'].round().astype('int')
+ else:
+ df = (
+ pd.DataFrame(
+ regionprops_table(
+ acc_obj_ids.data[:, :, 0, :],
+ properties=('label', 'area', 'solidity', 'bbox', 'centroid')
+ )
+ )
+ .rename(
+ columns={'bbox-0': 'y0', 'bbox-1': 'x0', 'bbox-2': 'y1', 'bbox-3': 'x1', }
+ )
)
- )
- df['zi'] = df['intensity_mean'].round().astype('int')
+ df['zi'] = ... # from somewhere in obmap floor of avg z for each label...
+
# compute expanded bounding boxes
h, w, c, nz = acc_raw.shape
diff --git a/tests/test_roiset.py b/tests/test_roiset.py
index 532218b9..f8e2eb6c 100644
--- a/tests/test_roiset.py
+++ b/tests/test_roiset.py
@@ -261,20 +261,6 @@ class TestRoiSetFromZmask(unittest.TestCase):
self.stack_ch_pa = self.stack.get_one_channel_data(roiset_test_data['pipeline_params']['segmentation_channel'])
self.seg_mask_3d = generate_file_accessor(roiset_test_data['multichannel_zstack']['mask_path_3d'])
- id_map = _get_label_ids(self.seg_mask_3d, allow_3d=True)
- self.assertGreater(id_map.nz, 1)
-
- roiset = RoiSet.from_3d_obj_ids(
- self.stack_ch_pa,
- id_map,
- params=RoiSetMetaParams(
- mask_type='contours',
- filters={'area': {'min': 1e3, 'max': 1e4}},
- )
- )
- self.roiset = roiset
- self.zmask = InMemoryDataAccessor(roiset.get_zmask())
-
@staticmethod
def _label_is_2d(id_map, la): # single label's zmask has same counts as its MIP
mask_3d = (id_map == la)
@@ -293,3 +279,32 @@ class TestRoiSetFromZmask(unittest.TestCase):
is_2d = all([self._label_is_2d(id_map.data, la) for la in labels])
self.assertTrue(is_2d)
+ def test_3d_zmask(self):
+ write_accessor_data_to_file(output_path / 'roiset_from_3d' / 'raw.tif', self.roiset.acc_raw)
+ # write_accessor_data_to_file(output_path / 'roiset_from_3d' / 'ob_ids.tif', self.roiset.acc_obj_ids)
+ write_accessor_data_to_file(output_path / 'roiset_from_3d' / 'zmask.tif', self.zmask)
+
+ def test_create_roiset_from_3d_obj_ids(self):
+ id_map = _get_label_ids(self.seg_mask_3d, allow_3d=True, connect_3d=False)
+ self.assertEqual(self.stack_ch_pa.shape, id_map.shape)
+
+ roiset = RoiSet.from_3d_obj_ids(
+ self.stack_ch_pa,
+ id_map,
+ params=RoiSetMetaParams(mask_type='contours')
+ )
+ self.assertEqual(roiset.count, id_map.data.max())
+ self.assertGreater(len(roiset.get_df()['zi'].unique()), 1)
+
+ def test_create_roiset_from_2d_obj_ids(self):
+ id_map = _get_label_ids(self.seg_mask_3d, allow_3d=False)
+ self.assertEqual(self.stack_ch_pa.shape[0:3], id_map.shape[0:3])
+ self.assertEqual(id_map.nz, 1)
+
+ roiset = RoiSet.from_2d_obj_ids(
+ self.stack_ch_pa,
+ id_map,
+ params=RoiSetMetaParams(mask_type='contours')
+ )
+ self.assertEqual(roiset.count, id_map.data.max())
+ self.assertGreater(len(roiset.get_df()['zi'].unique()), 1)
--
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