def load_mask(self, data: DataSetBase, image):
points, _, _, segmentations, _ = self._load_all_data_unmasked(
data, image)
if data.config[
"features_bake_segmentation"] and segmentations is not None:
ignore_values = set(data.segmentation_ignore_values(image))
return [
False if segmentations[i] in ignore_values else True
for i in range(len(segmentations))
]
else:
if points is None:
return None
return data.load_features_mask(image, points[:, :2])
def load_mask(self, data: DataSetBase, image: str) -> Optional[np.ndarray]:
all_features_data = self._load_all_data_unmasked(data, image)
if not all_features_data:
return None
if (data.config["features_bake_segmentation"]
and all_features_data.semantic is not None):
# pyre-fixme [16]: `Optional` has no attribute `segmentation`
segmentations = all_features_data.semantic.segmentation
ignore_values = set(data.segmentation_ignore_values(image))
return np.array([
False if segmentations[i] in ignore_values else True
for i in range(len(segmentations))
])
else:
return data.load_features_mask(image,
all_features_data.points[:, :2])
