diff --git a/model_server/base/accessors.py b/model_server/base/accessors.py
index e4c4a16444ccafcb63172a90cd1bce3169607f8b..3bebea375a4b94a0e91dd2143e872c64d9d92ca6 100644
--- a/model_server/base/accessors.py
+++ b/model_server/base/accessors.py
@@ -77,14 +77,14 @@ class GenericImageDataAccessor(ABC):
return self.data.sum(axis=(0, 1, 2))
@property
- def data_xy(self) -> np.ndarray:
+ def data_yx(self) -> np.ndarray:
if not self.chroma == 1 and self.nz == 1:
raise InvalidDataShape('Can only return XY array from accessors with a single channel and single z-level')
else:
return self.data[:, :, 0, 0]
@property
- def data_xyz(self) -> np.ndarray:
+ def data_yxz(self) -> np.ndarray:
if not self.chroma == 1:
raise InvalidDataShape('Can only return XYZ array from accessors with a single channel')
else:
@@ -428,6 +428,20 @@ class PatchStack(InMemoryDataAccessor):
def count(self):
return self.shape_dict['P']
+ @property
+ def data_yx(self) -> np.ndarray:
+ if not self.chroma == 1 and self.nz == 1:
+ raise InvalidDataShape('Can only return XY array from accessors with a single channel and single z-level')
+ else:
+ return self.data[:, :, :, 0, 0]
+
+ @property
+ def data_yxz(self) -> np.ndarray:
+ if not self.chroma == 1:
+ raise InvalidDataShape('Can only return XYZ array from accessors with a single channel')
+ else:
+ return self.data[:, :, :, 0, :]
+
def export_pyxcz(self, fpath: Path):
tzcyx = np.moveaxis(
self.pyxcz, # yxcz
diff --git a/model_server/base/roiset.py b/model_server/base/roiset.py
index 186ebb28026f0bc844a563b1727ae1602641fbf7..235327076ca18ed9dcc863374aa835141d3d1e0b 100644
--- a/model_server/base/roiset.py
+++ b/model_server/base/roiset.py
@@ -75,7 +75,7 @@ def get_label_ids(acc_seg_mask: GenericImageDataAccessor, allow_3d=False, connec
"""
if allow_3d and connect_3d:
nda_la = label(
- acc_seg_mask.data_xyz,
+ acc_seg_mask.data_yxz,
connectivity=3,
).astype('uint16')
return InMemoryDataAccessor(np.expand_dims(nda_la, 2))
@@ -84,7 +84,7 @@ def get_label_ids(acc_seg_mask: GenericImageDataAccessor, allow_3d=False, connec
la_3d = np.zeros((*acc_seg_mask.hw, 1, acc_seg_mask.nz), dtype='uint16')
for zi in range(0, acc_seg_mask.nz):
la_2d = label(
- acc_seg_mask.data_xyz[:, :, zi],
+ acc_seg_mask.data_yxz[:, :, zi],
connectivity=2,
).astype('uint16')
la_2d[la_2d > 0] = la_2d[la_2d > 0] + nla
@@ -94,7 +94,7 @@ def get_label_ids(acc_seg_mask: GenericImageDataAccessor, allow_3d=False, connec
else:
return InMemoryDataAccessor(
label(
- acc_seg_mask.get_mip().data_xy,
+ acc_seg_mask.get_mip().data_yx,
connectivity=1,
).astype('uint16')
)
@@ -234,10 +234,10 @@ def make_df_from_object_ids(acc_raw, acc_obj_ids, expand_box_by, deproject_chann
)
acc_raw.get_mono(deproject_channel)
- zi_map = acc_raw.get_mono(deproject_channel).get_z_argmax().data_xy.astype('uint16')
+ zi_map = acc_raw.get_mono(deproject_channel).get_z_argmax().data_yx.astype('uint16')
assert len(zi_map.shape) == 2
df = pd.DataFrame(regionprops_table(
- acc_obj_ids.data_xy,
+ acc_obj_ids.data_yx,
intensity_image=zi_map,
properties=('label', 'area', 'intensity_mean', 'bbox')
)).rename(columns={'bbox-0': 'y0', 'bbox-1': 'x0', 'bbox-2': 'y1', 'bbox-3': 'x1'})
@@ -245,7 +245,7 @@ def make_df_from_object_ids(acc_raw, acc_obj_ids, expand_box_by, deproject_chann
else: # objects' z-coordinates come from arg of max count in object identities map
df = pd.DataFrame(regionprops_table(
- acc_obj_ids.data_xyz,
+ acc_obj_ids.data_yxz,
properties=('label', 'area', 'bbox')
)).rename(columns={
'bbox-0': 'y0', 'bbox-1': 'x0', 'bbox-2': 'z0', 'bbox-3': 'y1', 'bbox-4': 'x1', 'bbox-5': 'z1'
@@ -260,7 +260,7 @@ def make_df_from_object_ids(acc_raw, acc_obj_ids, expand_box_by, deproject_chann
def _make_binary_mask(r):
acc = InMemoryDataAccessor(acc_obj_ids.data == r.label)
- cropped = acc.get_mono(0, mip=True).crop_hw((r.y0, r.x0, (r.y1 - r.y0), (r.x1 - r.x0))).data_xy
+ cropped = acc.get_mono(0, mip=True).crop_hw((r.y0, r.x0, (r.y1 - r.y0), (r.x1 - r.x0))).data_yx
return cropped
df['binary_mask'] = df.apply(
@@ -743,7 +743,7 @@ class RoiSet(object):
if white_channel:
assert white_channel < raw.chroma
- mono = raw.get_mono(white_channel).data_xyz
+ mono = raw.get_mono(white_channel).data_yxz
stack = np.stack([mono, mono, mono], axis=2)
else:
stack = np.zeros([*raw.shape[0:2], 3, raw.shape[3]], dtype=raw.dtype)
@@ -756,7 +756,7 @@ class RoiSet(object):
stack[:, :, ii, :] = safe_add(
stack[:, :, ii, :], # either black or grayscale channel
rgb_overlay_weights[ii],
- raw.get_mono(ci).data_xyz
+ raw.get_mono(ci).data_yxz
)
else:
if white_channel is not None: # interpret as just a single channel
@@ -771,7 +771,7 @@ class RoiSet(object):
annotate_rgb = True
break
if annotate_rgb: # make RGB patches anyway to include annotation color
- mono = raw.get_mono(white_channel).data_xyz
+ mono = raw.get_mono(white_channel).data_yxz
stack = np.stack([mono, mono, mono], axis=2)
else: # make monochrome patches
stack = raw.get_mono(white_channel).data
@@ -1057,7 +1057,7 @@ class RoiSet(object):
try:
ma_acc = generate_file_accessor(pa_masks / fname)
assert ma_acc.chroma == 1 and ma_acc.nz == 1
- mask_data = ma_acc.data_xy / ma_acc.dtype_max
+ mask_data = ma_acc.data_yx / ma_acc.dtype_max
return mask_data
except Exception as e:
raise DeserializeRoiSetError(e)
@@ -1192,8 +1192,8 @@ class IntensityThresholdInstanceMaskSegmentationModel(InstanceMaskSegmentationMo
) -> GenericImageDataAccessor:
labels = get_label_ids(mask)
df = pd.DataFrame(regionprops_table(
- labels.data_xyz,
- intensity_image=img.get_mono(self.channel).data_xyz,
+ labels.data_yxz,
+ intensity_image=img.get_mono(self.channel).data_yxz,
properties=('label', 'area', 'intensity_mean', 'bbox')
))
df['intensity_mean'] > self.tr
diff --git a/tests/base/test_accessors.py b/tests/base/test_accessors.py
index 1df5863c71f1d157d612e74ba83a822632d9f221..cfa929e33b04c59e89f578b5f72b9a6ac9f95a97 100644
--- a/tests/base/test_accessors.py
+++ b/tests/base/test_accessors.py
@@ -233,7 +233,6 @@ class TestPatchStackAccessor(unittest.TestCase):
self.assertEqual(acc.pyxcz.shape, (n, h, w, 1, 1))
return acc
-
def test_make_patch_stack_from_file(self):
h = data['monozstackmask']['h']
w = data['monozstackmask']['w']
@@ -301,6 +300,8 @@ class TestPatchStackAccessor(unittest.TestCase):
self.assertEqual(acc.count, n)
self.assertEqual(acc.pczyx.shape, (n, nc, nz, h, w))
self.assertEqual(acc.hw, (h, w))
+ self.assertEqual(acc.get_mono(channel=0).data_yxz.shape, (n, h, w, nz))
+ self.assertEqual(acc.get_mono(channel=0, mip=True).data_yx.shape, (n, h, w))
return acc
def test_get_one_channel(self):
diff --git a/tests/base/test_roiset.py b/tests/base/test_roiset.py
index b8e433e827304421d26ada0b8f9c5cbe1b037c32..2152ade5f108f92bde3015355440cc019282caa0 100644
--- a/tests/base/test_roiset.py
+++ b/tests/base/test_roiset.py
@@ -643,7 +643,7 @@ class TestRoiSetObjectDetection(unittest.TestCase):
from skimage.measure import label, regionprops, regionprops_table
mask = self.seg_mask_3d
- labels = label(mask.data_xyz, connectivity=3)
+ labels = label(mask.data_yxz, connectivity=3)
table = pd.DataFrame(
regionprops_table(labels)
).rename(