Datasets:
The dataset viewer is not available for this split.
Error code: StreamingRowsError
Exception: ValueError
Message: Invalid string class label LSAA-12K@474d548e4a82bca6c5f205a9d4d4482135269a64
Traceback: Traceback (most recent call last):
File "/src/services/worker/src/worker/utils.py", line 147, in get_rows_or_raise
return get_rows(
dataset=dataset,
...<4 lines>...
column_names=column_names,
)
File "/src/libs/libcommon/src/libcommon/utils.py", line 272, in decorator
return func(*args, **kwargs)
File "/src/services/worker/src/worker/utils.py", line 127, in get_rows
rows_plus_one = list(itertools.islice(safe_iter(ds, dataset=dataset), rows_max_number + 1))
File "/src/services/worker/src/worker/utils.py", line 483, in safe_iter
yield from ds.decode(False) if ds.features else ds
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2840, in __iter__
for key, example in ex_iterable:
^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2386, in __iter__
example = _apply_feature_types_on_example(
example, self.features, token_per_repo_id=self.token_per_repo_id
)
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2303, in _apply_feature_types_on_example
encoded_example = features.encode_example(example)
File "/usr/local/lib/python3.14/site-packages/datasets/features/features.py", line 2178, in encode_example
return encode_nested_example(self, example)
File "/usr/local/lib/python3.14/site-packages/datasets/features/features.py", line 1460, in encode_nested_example
{k: encode_nested_example(schema[k], obj.get(k), level=level + 1) for k in schema}
~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/features/features.py", line 1483, in encode_nested_example
return schema.encode_example(obj) if obj is not None else None
~~~~~~~~~~~~~~~~~~~~~^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/features/features.py", line 1158, in encode_example
example_data = self.str2int(example_data)
File "/usr/local/lib/python3.14/site-packages/datasets/features/features.py", line 1095, in str2int
output = [self._strval2int(value) for value in values]
~~~~~~~~~~~~~~~~^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/features/features.py", line 1116, in _strval2int
raise ValueError(f"Invalid string class label {value}")
ValueError: Invalid string class label LSAA-12K@474d548e4a82bca6c5f205a9d4d4482135269a64Need help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.
LSAA-12K
LSAA-12K contains 12,097 building facade samples with paired images, semantic label maps, JSON annotations, and English text prompts. It is released for the SAGE-Façade project, the implementation of SAGE-Façade: Semantic-Aligned Guidance for Exemplar-Based Façade Synthesis.
Splits
| Split | Samples | Archive |
|---|---|---|
| train | 11,795 | train.zip |
| test | 302 | test.zip |
| Total | 12,097 |
The archives preserve the original split and directory layout. No source files are modified, removed, or re-encoded. Each sample has four files with the same filename stem:
train/ test/
images/<sample_id>.jpg images/<sample_id>.jpg
labels/<sample_id>.png labels/<sample_id>.png
jsons/<sample_id>.json jsons/<sample_id>.json
prompts/<sample_id>.txt prompts/<sample_id>.txt
images: facade images in JPEG format.labels: semantic label maps in PNG format. Keep their original values/colors; do not treat them as ordinary RGB photographs or apply lossy compression.jsons: original JSON annotations. Inspected examples use LabelMe-style fields such asshapes,label,points, andshape_type.prompts: English descriptions, for exampleA building facade with 6 floors and 50 windows.
Sample IDs match across all four directories in each split. No sample ID is shared between train and test. This filename check does not establish absence of visually similar images or related building views.
Download and extract
Copy this dataset repository's ID (yisui/LSAA-12K) from the page URL,
then substitute it in the command below:
python -m pip install -U huggingface_hub
hf download yisui/LSAA-12K train.zip test.zip SHA256SUMS \
--repo-type dataset --local-dir ./LSAA-12K
cd LSAA-12K
sha256sum -c SHA256SUMS
unzip train.zip
unzip test.zip
To download only the test split, request test.zip and extract that archive.
Public, ungated datasets can be downloaded without logging in. For private
or gated access, log in with hf auth login first and obtain access as needed.
These ZIP files are an archival distribution for the project's existing file
layout. Use hf download or huggingface_hub.snapshot_download and extract
them before training; this release does not define a structured
datasets.load_dataset table or guarantee a Dataset Viewer preview.
SHA256SUMS provides checksums of both archives. dataset_stats.json records
sample counts, file counts, source sizes, archive sizes, and packaging checks.
ZIP member paths, uncompressed sizes, and CRCs were checked after packaging.
Usage and provenance
Use the train split for model development and the test split for evaluation. Refer to the project's dataset documentation for the expected layout and label conventions. This card does not infer class-index or color mappings from annotation examples.
The project README declares LSAA-12K a derivative work based on LSAA under CC BY-NC-SA 4.0. The metadata above follows that declaration. Attribute the LSAA source dataset and the SAGE-Façade/LSAA-12K creators when reusing the data, preserve relevant source notices, and follow the CC BY-NC-SA 4.0 terms. The project's code license (Apache-2.0) is separate from the dataset license.
Citation
Please cite the SAGE-Façade paper and the original LSAA dataset when using this release. An official BibTeX entry should be added when supplied by the authors; this card does not invent publication metadata.
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