def test_crop_covered_segments(self):
source_dataset = Dataset.from_iterable([
DatasetItem(
id=1,
image=np.zeros((5, 5, 3)),
annotations=[
# The mask is partially covered by the polygon
Mask(np.array(
[[0, 0, 1, 1, 1], [0, 0, 1, 1, 1], [1, 1, 1, 1, 1],
[1, 1, 1, 0, 0], [1, 1, 1, 0, 0]], ),
z_order=0),
Polygon([1, 1, 4, 1, 4, 4, 1, 4], z_order=1),
]),
])
target_dataset = Dataset.from_iterable([
DatasetItem(id=1,
image=np.zeros((5, 5, 3)),
annotations=[
Mask(np.array([[0, 0, 1, 1, 1], [0, 0, 0, 0, 1],
[1, 0, 0, 0, 1], [1, 0, 0, 0, 0],
[1, 1, 1, 0, 0]], ),
z_order=0),
Polygon([1, 1, 4, 1, 4, 4, 1, 4], z_order=1),
]),
])
actual = transforms.CropCoveredSegments(source_dataset)
compare_datasets(self, target_dataset, actual)
def test_crop_covered_segments(self):
class SrcExtractor(Extractor):
def __iter__(self):
return iter([
DatasetItem(
id=1,
image=np.zeros((5, 5, 3)),
annotations=[
# The mask is partially covered by the polygon
Mask(np.array([[0, 0, 1, 1, 1], [0, 0, 1, 1, 1],
[1, 1, 1, 1, 1], [1, 1, 1, 0, 0],
[1, 1, 1, 0, 0]], ),
z_order=0),
Polygon([1, 1, 4, 1, 4, 4, 1, 4], z_order=1),
]),
])
class DstExtractor(Extractor):
def __iter__(self):
return iter([
DatasetItem(id=1,
image=np.zeros((5, 5, 3)),
annotations=[
Mask(np.array(
[[0, 0, 1, 1, 1], [0, 0, 0, 0, 1],
[1, 0, 0, 0, 1], [1, 0, 0, 0, 0],
[1, 1, 1, 0, 0]], ),
z_order=0),
Polygon([1, 1, 4, 1, 4, 4, 1, 4],
z_order=1),
]),
])
actual = transforms.CropCoveredSegments(SrcExtractor())
compare_datasets(self, DstExtractor(), actual)