From 799f2ea538b390a3725ec38ca44e2a1cebac8594 Mon Sep 17 00:00:00 2001
From: Christopher Rhodes <christopher.rhodes@embl.de>
Date: Thu, 1 Aug 2024 16:46:06 +0200
Subject: [PATCH] Implemented and tested creation of RoiSet from polygon
coordinates
---
model_server/base/roiset.py | 50 ++++++++++++++++++++++++++-----------
tests/base/test_roiset.py | 22 ++++++++++------
2 files changed, 49 insertions(+), 23 deletions(-)
diff --git a/model_server/base/roiset.py b/model_server/base/roiset.py
index dcd8cfa7..bdbd2c8c 100644
--- a/model_server/base/roiset.py
+++ b/model_server/base/roiset.py
@@ -10,6 +10,7 @@ from pydantic import BaseModel
from scipy.stats import moment
from skimage.filters import sobel
+from skimage import draw
from skimage.measure import approximate_polygon, find_contours, label, points_in_poly, regionprops, regionprops_table, shannon_entropy
from skimage.morphology import binary_dilation, disk
@@ -181,10 +182,6 @@ def make_df_from_object_ids(acc_raw, acc_obj_ids, expand_box_by) -> pd.DataFrame
)
return df
-# TODO: implement
-def make_df_from_polygons(acc_raw, polygons:np.ndarray) -> pd.DataFrame:
- pass
-
def df_insert_slices(df: pd.DataFrame, sd: dict, expand_box_by) -> pd.DataFrame:
h = sd['Y']
@@ -345,20 +342,43 @@ class RoiSet(object):
Create a RoiSet from a binary segmentation mask (either 2D or 3D)
:param acc_raw: accessor to a generally a multichannel z-stack
:param acc_seg: accessor of a binary segmentation mask (mono) of either two or three dimensions
- :param allow_3d: return a 3D map if True; return a 2D map of the mask's maximum intensity project if False
+ :param allow_3d: use a 3D map if True; use a 2D map of the mask's maximum intensity project if False
:param connect_3d: objects can span multiple z-positions if True; objects are unique to a single z if False
:param params: optional arguments that influence the definition and representation of ROIs
- :return: object identities map
"""
- return RoiSet.from_object_ids(acc_raw, get_label_ids(acc_seg, allow_3d=allow_3d, connect_3d=connect_3d), params)
+ return RoiSet.from_object_ids(
+ acc_raw,
+ get_label_ids(
+ acc_seg,
+ allow_3d=allow_3d,
+ connect_3d=connect_3d
+ ),
+ params
+ )
@staticmethod
- #TODO: implement
- def from_polygons(acc_raw, polygons: np.ndarray):
- binary_poly = np.zeros(acc_raw.mono(0).shape, dtype=bool)
- for p in poly:
- pidcs = draw.polygon(p[:, 1], p[:, 0])
- binary_poly[pidcs] = True
+ def from_polygons_2d(
+ acc_raw,
+ polygons: List[np.ndarray],
+ params: RoiSetMetaParams = RoiSetMetaParams()
+ ):
+ """
+ Create a RoiSet where objects are defined from a list of polygon coordinates
+ :param acc_raw: accessor to a generally a multichannel z-stack
+ :param polygons: list of (variable x 2) np.ndarrays describing (x, y) polymer coordinates
+ :param params: optional arguments that influence the definition and representation of ROIs
+ """
+ mask = np.zeros(acc_raw.get_mono(0, mip=True).shape, dtype=bool)
+ for p in polygons:
+ sl = draw.polygon(p[:, 1], p[:, 0])
+ mask[sl] = True
+ return RoiSet.from_binary_mask(
+ acc_raw,
+ InMemoryDataAccessor(mask),
+ allow_3d=False,
+ connect_3d=False,
+ params=params,
+ )
# TODO: get overlapping segments
@@ -394,7 +414,7 @@ class RoiSet(object):
write_accessor_data_to_file(fp, annotated)
return (prefix + '.tif')
- def get_zmask(self, mask_type='boxes'):
+ def get_zmask(self, mask_type='boxes') -> np.ndarray:
"""
Return a mask of same dimensionality as raw data
@@ -780,7 +800,7 @@ class RoiSet(object):
return record
def get_polygons(self, poly_threshold=0, dilation_radius=1) -> pd.DataFrame:
- """
+ self.coordinates_ = """
Fit polygons to all object boundaries in the RoiSet
:param poly_threshold: threshold distance for polygon fit; a smaller number follows sharp features more closely
:param dilation_radius: radius of binary dilation to apply before fitting polygon
diff --git a/tests/base/test_roiset.py b/tests/base/test_roiset.py
index 1626aca0..3f31948d 100644
--- a/tests/base/test_roiset.py
+++ b/tests/base/test_roiset.py
@@ -659,7 +659,7 @@ class TestRoiSetSerialization(unittest.TestCase):
class TestRoiSetPolygons(BaseTestRoiSetMonoProducts, unittest.TestCase):
def test_compute_polygons(self):
- roiset = RoiSet.from_binary_mask(
+ roiset_ref = RoiSet.from_binary_mask(
self.stack_ch_pa,
self.seg_mask,
params=RoiSetMetaParams(
@@ -668,19 +668,25 @@ class TestRoiSetPolygons(BaseTestRoiSetMonoProducts, unittest.TestCase):
)
)
- poly = roiset.get_polygons()
- binary_poly = np.zeros(self.seg_mask.hw, dtype=bool)
- for p in poly:
- pidcs = draw.polygon(p[:, 1], p[:, 0])
- binary_poly[pidcs] = True
+ poly = roiset_ref.get_polygons()
+ roiset_test = RoiSet.from_polygons_2d(self.stack_ch_pa, poly)
+ binary_poly = (roiset_test.acc_obj_ids.get_mono(0, mip=True).data > 0)
+ self.assertEqual(self.seg_mask.shape, binary_poly.shape)
+
+ # most mask pixels are within in fitted polygon
test_mask = np.logical_and(
np.logical_not(binary_poly),
- (self.seg_mask.data[:, :, 0, 0] == 255)
+ (self.seg_mask.data == 255)
)
- # most mask pixels are within in fitted polygon
self.assertLess(test_mask.sum() / test_mask.size, 0.001)
+ # output results
+ od = output_path / 'polygons'
+ write_accessor_data_to_file(od / 'from_polygons.tif', InMemoryDataAccessor(binary_poly))
+ write_accessor_data_to_file(od / 'ref_mask.tif', self.seg_mask)
+ write_accessor_data_to_file(od / 'diff.tif', InMemoryDataAccessor(test_mask))
+
def test_serialize_coco(self):
roiset = RoiSet.from_binary_mask(
self.stack_ch_pa,
--
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