From 009e4b309d610ec521d84b7acbe12e3c80c0c54d Mon Sep 17 00:00:00 2001
From: Christopher Rhodes <christopher.rhodes@embl.de>
Date: Wed, 27 Nov 2024 20:47:02 +0100
Subject: [PATCH] All pre-existing tests pass
---
model_server/base/roiset.py | 51 ++++++++++++++++---------------------
tests/base/test_roiset.py | 2 ++
2 files changed, 24 insertions(+), 29 deletions(-)
diff --git a/model_server/base/roiset.py b/model_server/base/roiset.py
index dbe24304..ba35a9a9 100644
--- a/model_server/base/roiset.py
+++ b/model_server/base/roiset.py
@@ -234,6 +234,10 @@ def filter_df_overlap_seg(df1: pd.DataFrame, df2: pd.DataFrame = None) -> pd.Dat
return dfbb
+def is_df_3d(df: pd.DataFrame) -> bool:
+ return 'z0' in df.columns and 'zi' in df.columns
+
+
def make_df_from_object_ids(
acc_raw,
acc_obj_ids,
@@ -290,17 +294,15 @@ def make_df_from_object_ids(
elif acc_obj_ids.nz == 1 and acc_raw.nz == 1: # purely 2d, no z information in dataframe
df = pd.DataFrame(regionprops_table(
- acc_obj_ids.data_yxz,
+ acc_obj_ids.data_yx,
properties=('label', 'area', 'bbox')
)).rename(columns={
'bbox-0': 'y0', 'bbox-1': 'x0', 'bbox-2': 'y1', 'bbox-3': 'x1'
})
- # df['zi'] = 0
-
def _make_binary_mask(r):
acc = InMemoryDataAccessor(acc_obj_ids.data == r.label)
- return acc.get_mono(0).crop_hw((r.y0, r.x0, (r.y1 - r.y0), (r.x1 - r.x0))).data_yx
+ cropped = acc.get_mono(0).crop_hw((r.y0, r.x0, (r.y1 - r.y0), (r.x1 - r.x0))).data_yx
return cropped
else: # purely 3d: objects' median z-coordinates come from arg of max count in object identities map
@@ -318,24 +320,11 @@ def make_df_from_object_ids(
def _make_binary_mask(r):
acc = InMemoryDataAccessor(acc_obj_ids.data == r.label)
-
- # TODO: optional r.z0:z1 + 1 for case of 3d objects
cropped = acc.get_mono(0).crop_hwd((r.y0, r.x0, r.z0, (r.y1 - r.y0), (r.x1 - r.x0), (r.z1 - r.z0))).data_yxz
- # TODO: 3d crop method on accessor
return cropped
df = df_insert_slices(df, acc_raw.shape_dict, expand_box_by)
-
df_fil = filter_df(df, filters)
-
- # def _make_binary_mask(r):
- # acc = InMemoryDataAccessor(acc_obj_ids.data == r.label)
- #
- # # TODO: optional r.z0:z1 + 1 for case of 3d objects
- # # cropped = acc.get_mono(0, mip=True).crop_hw((r.y0, r.x0, (r.y1 - r.y0), (r.x1 - r.x0))).data_yx
- # cropped = acc.get_mono(0).crop_hw((r.y0, r.x0, (r.y1 - r.y0), (r.x1 - r.x0))).data_yxz[r.z0: r.z1]
- # return cropped
-
df_fil['binary_mask'] = df_fil.apply(
_make_binary_mask,
axis=1,
@@ -360,16 +349,15 @@ def df_insert_slices(df: pd.DataFrame, sd: dict, expand_box_by) -> pd.DataFrame:
df['ebb_x0'] = (df.x0 - ebxy).apply(lambda x: max(x, 0))
df['ebb_x1'] = (df.x1 + ebxy).apply(lambda x: min(x, w))
- # handle based on third dimension
- if 'z0' in df.columns and 'z1' in df.columns:
+ # handle based on whether bounding box coordinates are 2d or 3d
+ if is_df_3d(df):
df['ebb_z0'] = (df.z0 - ebz).apply(lambda x: max(x, 0))
df['ebb_z1'] = (df.z1 + ebz).apply(lambda x: max(x, nz))
- elif 'zi' in df.columns:
+ else:
+ if 'zi' not in df.columns:
+ df['zi'] = 0
df['ebb_z0'] = (df.zi - ebz).apply(lambda x: max(x, 0))
df['ebb_z1'] = (df.zi + ebz).apply(lambda x: min(x, nz))
- else:
- df['ebb_z0'] = df.zi
- df['ebb_z1'] = df.zi
df['ebb_h'] = df['ebb_y1'] - df['ebb_y0']
df['ebb_w'] = df['ebb_x1'] - df['ebb_x0']
@@ -423,7 +411,7 @@ def make_object_ids_from_df(df: pd.DataFrame, sd: dict) -> InMemoryDataAccessor:
if 'binary_mask' not in df.columns:
raise MissingSegmentationError('RoiSet dataframe does not contain segmentation')
- if 'z0' in df.columns and 'zi' in df.columns: # use 3d coordinates
+ if is_df_3d(df): # use 3d coordinates
def _label_obj(r):
sl = np.s_[r.y0:r.y1, r.x0:r.x1, :, r.z0:r.z1]
mask = np.expand_dims(r.binary_mask, 2)
@@ -837,6 +825,7 @@ class RoiSet(object):
return patches_df
def get_patch_masks(self, pad_to: int = None, expanded: bool = False) -> pd.DataFrame:
+ is_3d = is_df_3d(self._df)
def _make_patch_mask(roi):
if expanded:
patch = np.zeros((roi.ebb_h, roi.ebb_w, 1, 1), dtype='uint8')
@@ -845,7 +834,10 @@ class RoiSet(object):
patch = (roi.binary_mask * 255).astype('uint8')
if pad_to:
patch = pad(patch, pad_to)
- return np.expand_dims(patch, (2, 3))
+ if is_3d:
+ return np.expand_dims(patch, 3)
+ else:
+ return np.expand_dims(patch, (2, 3))
dfe = self._df.copy()
dfe['patch_mask'] = dfe.apply(_make_patch_mask, axis=1)
@@ -1203,9 +1195,10 @@ class RoiSet(object):
fname = f'{prefix}-la{r.label:04d}-zi{r.zi:04d}.{ext}'
try:
ma_acc = generate_file_accessor(pa_masks / fname)
- # TODO: check this on re-serialized test data
- # assert ma_acc.chroma == 1 and ma_acc.nz == 1
- mask_data = ma_acc.data_yxz / ma_acc.dtype_max
+ if is_df_3d(df):
+ mask_data = ma_acc.data_yxz / ma_acc.dtype_max
+ else:
+ mask_data = ma_acc.data_yx / ma_acc.dtype_max
return mask_data
except Exception as e:
raise DeserializeRoiSetError(e)
@@ -1214,7 +1207,7 @@ class RoiSet(object):
id_mask = make_object_ids_from_df(df, acc_raw.shape_dict)
return cls.from_object_ids(acc_raw, id_mask)
- else: # assume bounding boxes only
+ else: # assume bounding boxes, exclusively 2d objects
df['y'] = df['y0']
df['x'] = df['x0']
df['h'] = df['y1'] - df['y0']
diff --git a/tests/base/test_roiset.py b/tests/base/test_roiset.py
index dd792e7c..46896538 100644
--- a/tests/base/test_roiset.py
+++ b/tests/base/test_roiset.py
@@ -252,6 +252,8 @@ class TestRoiSet3dProducts(unittest.TestCase):
where = output_path / 'run_exports_mono_3d'
+ # TODO: test serialization/deserialization of 3d patches
+
def setUp(self) -> None:
# set up test raw data and segmentation from file
self.stack = generate_file_accessor(data['multichannel_zstack_raw']['path'])
--
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