From b4693d6938e10f6db06133edbac44f4361b18b69 Mon Sep 17 00:00:00 2001
From: Christopher Rhodes <christopher.rhodes@embl.de>
Date: Tue, 16 Jul 2024 14:54:58 +0200
Subject: [PATCH] Renamed dataframe maker and moved derivative dataframe
columns into separate method
---
model_server/base/roiset.py | 92 +++++++++++++++++++------------------
tests/base/test_roiset.py | 1 -
2 files changed, 48 insertions(+), 45 deletions(-)
diff --git a/model_server/base/roiset.py b/model_server/base/roiset.py
index 23748e60..36f9e066 100644
--- a/model_server/base/roiset.py
+++ b/model_server/base/roiset.py
@@ -129,6 +129,51 @@ def _filter_overlap_bbox(df: pd.DataFrame) -> pd.DataFrame:
return sdf
+def _df_insert_slices(df: pd.DataFrame, shape: tuple, expand_box_by) -> pd.DataFrame:
+ h, w, c, nz = shape
+ df['h'] = df['y1'] - df['y0']
+ df['w'] = df['x1'] - df['x0']
+ ebxy, ebz = expand_box_by
+ df['ebb_y0'] = (df.y0 - ebxy).apply(lambda x: max(x, 0))
+ df['ebb_y1'] = (df.y1 + ebxy).apply(lambda x: min(x, h))
+ df['ebb_x0'] = (df.x0 - ebxy).apply(lambda x: max(x, 0))
+ df['ebb_x1'] = (df.x1 + ebxy).apply(lambda x: min(x, w))
+ df['ebb_z0'] = (df.zi - ebz).apply(lambda x: max(x, 0))
+ df['ebb_z1'] = (df.zi + ebz).apply(lambda x: min(x, nz))
+ df['ebb_h'] = df['ebb_y1'] - df['ebb_y0']
+ df['ebb_w'] = df['ebb_x1'] - df['ebb_x0']
+ df['ebb_nz'] = df['ebb_z1'] - df['ebb_z0'] + 1
+
+ # compute relative bounding boxes
+ df['rel_y0'] = df.y0 - df.ebb_y0
+ df['rel_y1'] = df.y1 - df.ebb_y0
+ df['rel_x0'] = df.x0 - df.ebb_x0
+ df['rel_x1'] = df.x1 - df.ebb_x0
+
+ assert np.all(df['rel_x1'] <= (df['ebb_x1'] - df['ebb_x0']))
+ assert np.all(df['rel_y1'] <= (df['ebb_y1'] - df['ebb_y0']))
+
+ df['slice'] = df.apply(
+ lambda r:
+ np.s_[int(r.y0): int(r.y1), int(r.x0): int(r.x1), :, int(r.zi): int(r.zi + 1)],
+ axis=1,
+ result_type='reduce',
+ )
+ df['expanded_slice'] = df.apply(
+ lambda r:
+ np.s_[int(r.ebb_y0): int(r.ebb_y1), int(r.ebb_x0): int(r.ebb_x1), :, int(r.ebb_z0): int(r.ebb_z1) + 1],
+ axis=1,
+ result_type='reduce',
+ )
+ df['relative_slice'] = df.apply(
+ lambda r:
+ np.s_[int(r.rel_y0): int(r.rel_y1), int(r.rel_x0): int(r.rel_x1), :, :],
+ axis=1,
+ result_type='reduce',
+ )
+ return df
+
+
def _safe_add(a, g, b):
assert a.dtype == b.dtype
assert a.shape == b.shape
@@ -165,7 +210,7 @@ class RoiSet(object):
self.params = params
self._df = self.filter_df(
- self.make_df(
+ self.make_df_from_object_ids(
self.acc_raw, self.acc_obj_ids, expand_box_by=params.expand_box_by
),
params.filters,
@@ -203,7 +248,7 @@ class RoiSet(object):
# call e.g. static adder
@staticmethod
- def make_df(acc_raw, acc_obj_ids, expand_box_by) -> pd.DataFrame:
+ def make_df_from_object_ids(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
@@ -231,48 +276,7 @@ class RoiSet(object):
})
df['zi'] = df['label'].apply(lambda x: (acc_obj_ids.data == x).sum(axis=(0, 1, 2)).argmax())
- # compute expanded bounding boxes
- h, w, c, nz = acc_raw.shape
- df['h'] = df['y1'] - df['y0']
- df['w'] = df['x1'] - df['x0']
- ebxy, ebz = expand_box_by
- df['ebb_y0'] = (df.y0 - ebxy).apply(lambda x: max(x, 0))
- df['ebb_y1'] = (df.y1 + ebxy).apply(lambda x: min(x, h))
- df['ebb_x0'] = (df.x0 - ebxy).apply(lambda x: max(x, 0))
- df['ebb_x1'] = (df.x1 + ebxy).apply(lambda x: min(x, w))
- df['ebb_z0'] = (df.zi - ebz).apply(lambda x: max(x, 0))
- df['ebb_z1'] = (df.zi + ebz).apply(lambda x: min(x, nz))
- df['ebb_h'] = df['ebb_y1'] - df['ebb_y0']
- df['ebb_w'] = df['ebb_x1'] - df['ebb_x0']
- df['ebb_nz'] = df['ebb_z1'] - df['ebb_z0'] + 1
-
- # compute relative bounding boxes
- df['rel_y0'] = df.y0 - df.ebb_y0
- df['rel_y1'] = df.y1 - df.ebb_y0
- df['rel_x0'] = df.x0 - df.ebb_x0
- df['rel_x1'] = df.x1 - df.ebb_x0
-
- assert np.all(df['rel_x1'] <= (df['ebb_x1'] - df['ebb_x0']))
- assert np.all(df['rel_y1'] <= (df['ebb_y1'] - df['ebb_y0']))
-
- df['slice'] = df.apply(
- lambda r:
- np.s_[int(r.y0): int(r.y1), int(r.x0): int(r.x1), :, int(r.zi): int(r.zi + 1)],
- axis=1,
- result_type='reduce',
- )
- df['expanded_slice'] = df.apply(
- lambda r:
- np.s_[int(r.ebb_y0): int(r.ebb_y1), int(r.ebb_x0): int(r.ebb_x1), :, int(r.ebb_z0): int(r.ebb_z1) + 1],
- axis=1,
- result_type='reduce',
- )
- df['relative_slice'] = df.apply(
- lambda r:
- np.s_[int(r.rel_y0): int(r.rel_y1), int(r.rel_x0): int(r.rel_x1), :, :],
- axis=1,
- result_type='reduce',
- )
+ df = _df_insert_slices(df, acc_raw.shape, expand_box_by)
# TODO: make this contingent on whether seg is included
df['binary_mask'] = df.apply(
diff --git a/tests/base/test_roiset.py b/tests/base/test_roiset.py
index b06499c9..dcf849bd 100644
--- a/tests/base/test_roiset.py
+++ b/tests/base/test_roiset.py
@@ -71,7 +71,6 @@ class TestOverlapLogic(unittest.TestCase):
def test_overlap_bbox(self):
res = _filter_overlap_bbox(self.df)
- print(res)
self.assertEqual(len(res), 2)
self.assertTrue((res.loc[0, 'overlaps_with'] == 1).all())
self.assertTrue((res.loc[1, 'overlaps_with'] == 2).all())
--
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