From 691a9fcef635303fecbfebfbb16824460ff95294 Mon Sep 17 00:00:00 2001
From: Christopher Rhodes <christopher.rhodes@embl.de>
Date: Thu, 28 Mar 2024 18:50:25 +0100
Subject: [PATCH] Passes, long warnings that convex hull calcs don't work
---
model_server/base/roiset.py | 14 ++++++++------
1 file changed, 8 insertions(+), 6 deletions(-)
diff --git a/model_server/base/roiset.py b/model_server/base/roiset.py
index 4607b72b..503c5b66 100644
--- a/model_server/base/roiset.py
+++ b/model_server/base/roiset.py
@@ -154,18 +154,17 @@ class RoiSet(object):
return self._df.itertuples(name='Roi')
@staticmethod
- def make_df(acc_raw, acc_obj_ids, expand_box_by, deproject=True) -> pd.DataFrame:
+ def make_df(acc_raw, acc_obj_ids, expand_box_by) -> 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
+ # :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
- if deproject:
- assert acc_obj_ids.nz == 1, 'Can only deproject a 2D object identity map'
+ if acc_obj_ids.nz == 1: # deproject objects' z-coordinates from argmax of raw image
argmax = acc_raw.data.argmax(axis=3, keepdims=True)[:, :, 0, 0].astype('uint16')
df = (
pd.DataFrame(
@@ -180,7 +179,7 @@ class RoiSet(object):
)
)
df['zi'] = df['intensity_mean'].round().astype('int')
- else:
+ else: # objects' z-coordinates come from arg of max count in object identities map
df = (
pd.DataFrame(
regionprops_table(
@@ -192,7 +191,10 @@ class RoiSet(object):
columns={'bbox-0': 'y0', 'bbox-1': 'x0', 'bbox-2': 'y1', 'bbox-3': 'x1', }
)
)
- df['zi'] = ... # from somewhere in obmap floor of avg z for each label...
+ def _get_zi_from_obj_map_counts(la):
+ return (acc_obj_ids.data == la).sum(axis=(0, 1, 2)).argmax()
+
+ df['zi'] = df['label'].apply(_get_zi_from_obj_map_counts)
# compute expanded bounding boxes
--
GitLab