SpatialPadd(KEYS, spatial_size=[111, 113], method="end"),
SpatialPadd(KEYS, spatial_size=[118, 117]),
))
TESTS.append((
"SpatialPadd 3d",
"3D",
0,
SpatialPadd(KEYS, spatial_size=[112, 113, 116]),
))
TESTS.append((
"SpatialCropd 2d",
"2D",
0,
SpatialCropd(KEYS, [49, 51], [90, 89]),
))
TESTS.append((
"SpatialCropd 3d",
"3D",
0,
SpatialCropd(KEYS,
roi_slices=[
slice(s, e)
for s, e in zip([None, None, -99], [None, -2, None])
]),
))
TESTS.append((
"SpatialCropd 2d",
t(KEYS))) # type: ignore
TESTS.append((
"SpatialPadd (x2) 2d",
"2D",
0,
True,
SpatialPadd(KEYS, spatial_size=[111, 113], method="end"),
SpatialPadd(KEYS, spatial_size=[118, 117]),
))
TESTS.append(("SpatialPadd 3d", "3D", 0, True,
SpatialPadd(KEYS, spatial_size=[112, 113, 116])))
TESTS.append(
("SpatialCropd 2d", "2D", 0, True, SpatialCropd(KEYS, [49, 51], [90, 89])))
TESTS.append((
"SpatialCropd 3d",
"3D",
0,
True,
SpatialCropd(KEYS,
roi_slices=[
slice(s, e)
for s, e in zip([None, None, -99], [None, -2, None])
]),
))
TESTS.append(
("SpatialCropd 2d", "2D", 0, True, SpatialCropd(KEYS, [49, 51],
for i in range(n_comp + 1):
if i == 0:
continue # skipping background
b_label = labels == i
bb = BoundingRect()(b_label[None])
area = (bb[0, 1] - bb[0, 0]) * (bb[0, 3] - bb[0, 2]) * (bb[0, 5] -
bb[0, 4])
if area <= 500:
continue
print(bb, area)
s = [bb[0, 0] - 16, bb[0, 2] - 16, bb[0, 4] - 16]
e = [bb[0, 1] + 16, bb[0, 3] + 16, bb[0, 5] + 16]
# generate lesion patches based on the bounding boxes
data_out = AddChanneld(keys)(data)
data_out = SpatialCropd(keys, roi_start=s, roi_end=e)(data_out)
resize = Resized(keys, patch_size, mode=("trilinear", "nearest"))
data_out = resize(data_out)
patch_out = (
f"{folder}/patch/lesion_{s[0]}_{s[1]}_{s[2]}_{e[0]}_{e[1]}_{e[2]}_{name_id}"
)
label_out = (
f"{folder}/patch/labels_{s[0]}_{s[1]}_{s[2]}_{e[0]}_{e[1]}_{e[2]}_{name_id}"
)
write_nifti(data_out["image"][0], file_name=patch_out)
write_nifti(data_out["label"][0], file_name=label_out)
# generate random negative samples
rand_data_out = AddChanneld(keys)(data)
rand_data_out["inv_label"] = (rand_data_out["label"] == 0
def test_shape(self, input_param, input_data, expected_shape):
result = SpatialCropd(**input_param)(input_data)
self.assertTupleEqual(result['img'].shape, expected_shape)
SpatialPadd(KEYS, spatial_size=[111, 113], method="end"),
SpatialPadd(KEYS, spatial_size=[118, 117]),
))
TESTS.append((
"SpatialPadd 3d",
"3D",
0,
SpatialPadd(KEYS, spatial_size=[112, 113, 116]),
))
TESTS.append((
"SpatialCropd 2d",
"2D",
0,
SpatialCropd(KEYS, [49, 51], [90, 89]),
))
TESTS.append((
"SpatialCropd 2d",
"2D",
0,
SpatialCropd(KEYS, [49, 51], [390, 89]),
))
TESTS.append((
"SpatialCropd 3d",
"3D",
0,
SpatialCropd(KEYS, [49, 51, 44], [90, 89, 93]),
))
):
TESTS.append((t.func.__name__ + "bad 1D even", "1D even", 0, t(KEYS))) # type: ignore
TESTS.append(
(
"SpatialPadd (x2) 2d",
"2D",
0,
SpatialPadd(KEYS, spatial_size=[111, 113], method="end"),
SpatialPadd(KEYS, spatial_size=[118, 117]),
)
)
TESTS.append(("SpatialPadd 3d", "3D", 0, SpatialPadd(KEYS, spatial_size=[112, 113, 116])))
TESTS.append(("SpatialCropd 2d", "2D", 0, SpatialCropd(KEYS, [49, 51], [90, 89])))
TESTS.append(
(
"SpatialCropd 3d",
"3D",
0,
SpatialCropd(KEYS, roi_slices=[slice(s, e) for s, e in zip([None, None, -99], [None, -2, None])]),
)
)
TESTS.append(("SpatialCropd 2d", "2D", 0, SpatialCropd(KEYS, [49, 51], [390, 89])))
TESTS.append(("SpatialCropd 3d", "3D", 0, SpatialCropd(KEYS, [49, 51, 44], [90, 89, 93])))
TESTS.append(("RandSpatialCropd 2d", "2D", 0, RandSpatialCropd(KEYS, [96, 93], None, True, False)))
