def _get_feature_label_keys():
"""Extracts and returns the dataset feature and label keys."""
feature_spec = (scannet_specs.scene_feature_spec(
with_annotations=True).get_serialized_info())
feature_dict = tfds.core.utils.flatten_nest_dict(feature_spec)
feature_keys = []
label_keys = []
for key in sorted(feature_dict):
if 'labels' in key:
label_keys.append(key)
else:
feature_keys.append(key)
return feature_keys, label_keys
def decode_fn(value):
tensors = example_parser.decode_serialized_example(
serialized_example=value,
features=scannet_specs.scene_feature_spec(with_annotations=True))
tensor_dict = tfds.core.utils.flatten_nest_dict(tensors)
return tensor_dict