Dataset Viewer
The dataset viewer is not available for this split.
Cannot load the dataset split (in streaming mode) to extract the first rows.
Error code: StreamingRowsError
Exception: CastError
Message: Couldn't cast
schema_version: int64
dataset: string
release_version: string
generator_commit: string
splits: struct<train: struct<images: int64, resolutions: list<item: struct<width: int64, height: int64, coun (... 221 chars omitted)
child 0, train: struct<images: int64, resolutions: list<item: struct<width: int64, height: int64, count: int64>>>
child 0, images: int64
child 1, resolutions: list<item: struct<width: int64, height: int64, count: int64>>
child 0, item: struct<width: int64, height: int64, count: int64>
child 0, width: int64
child 1, height: int64
child 2, count: int64
child 1, val: struct<images: int64, resolutions: list<item: struct<width: int64, height: int64, count: int64>>>
child 0, images: int64
child 1, resolutions: list<item: struct<width: int64, height: int64, count: int64>>
child 0, item: struct<width: int64, height: int64, count: int64>
child 0, width: int64
child 1, height: int64
child 2, count: int64
child 2, test: struct<images: int64, resolutions: list<item: struct<width: int64, height: int64, count: int64>>>
child 0, images: int64
child 1, resolutions: list<item: struct<width: int64, height: int64, count: int64>>
child 0, item: struct<width: int64, height: int64, count: int64>
child 0, width: int64
child 1, height: int64
child 2, count: int64
masks: struct<count: int64, resolutions: list<item: struct<width: int64, height: int64, count: int64>>>
child 0, count: int64
child 1, resolutions: list<item: struct<width: int64, height: int64, count: int64>>
child 0, item: struct<width: int64, height: int64, count: int64>
child 0, width: int64
child 1, height: int64
child 2, count: int64
totals: struct<environment_maps: int64, training: int64, validation: int64, test: int64, completion_masks: i (... 5 chars omitted)
child 0, environment_maps: int64
child 1, training: int64
child 2, validation: int64
child 3, test: int64
child 4, completion_masks: int64
file_count: int64
files: list<item: struct<path: string, size_bytes: int64, sha256: string>>
child 0, item: struct<path: string, size_bytes: int64, sha256: string>
child 0, path: string
child 1, size_bytes: int64
child 2, sha256: string
total_bytes: int64
to
{'schema_version': Value('int64'), 'dataset': Value('string'), 'release_version': Value('string'), 'generator_commit': Value('string'), 'file_count': Value('int64'), 'total_bytes': Value('int64'), 'files': List({'path': Value('string'), 'size_bytes': Value('int64'), 'sha256': Value('string')})}
because column names don't match
Traceback: Traceback (most recent call last):
File "/src/services/worker/src/worker/utils.py", line 149, 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 129, 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 489, 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 2818, in __iter__
for key, example in ex_iterable:
^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2355, in __iter__
for key, pa_table in self._iter_arrow():
~~~~~~~~~~~~~~~~^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2380, in _iter_arrow
for key, pa_table in self.ex_iterable._iter_arrow():
~~~~~~~~~~~~~~~~~~~~~~~~~~~~^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 536, in _iter_arrow
for key, pa_table in iterator:
^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 419, in _iter_arrow
for key, pa_table in self.generate_tables_fn(**gen_kwags):
~~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/json/json.py", line 343, in _generate_tables
self._cast_table(pa_table, json_field_paths=json_field_paths),
~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/json/json.py", line 132, in _cast_table
pa_table = table_cast(pa_table, self.info.features.arrow_schema)
File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2369, in table_cast
return cast_table_to_schema(table, schema)
File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2297, in cast_table_to_schema
raise CastError(
...<3 lines>...
)
datasets.table.CastError: Couldn't cast
schema_version: int64
dataset: string
release_version: string
generator_commit: string
splits: struct<train: struct<images: int64, resolutions: list<item: struct<width: int64, height: int64, coun (... 221 chars omitted)
child 0, train: struct<images: int64, resolutions: list<item: struct<width: int64, height: int64, count: int64>>>
child 0, images: int64
child 1, resolutions: list<item: struct<width: int64, height: int64, count: int64>>
child 0, item: struct<width: int64, height: int64, count: int64>
child 0, width: int64
child 1, height: int64
child 2, count: int64
child 1, val: struct<images: int64, resolutions: list<item: struct<width: int64, height: int64, count: int64>>>
child 0, images: int64
child 1, resolutions: list<item: struct<width: int64, height: int64, count: int64>>
child 0, item: struct<width: int64, height: int64, count: int64>
child 0, width: int64
child 1, height: int64
child 2, count: int64
child 2, test: struct<images: int64, resolutions: list<item: struct<width: int64, height: int64, count: int64>>>
child 0, images: int64
child 1, resolutions: list<item: struct<width: int64, height: int64, count: int64>>
child 0, item: struct<width: int64, height: int64, count: int64>
child 0, width: int64
child 1, height: int64
child 2, count: int64
masks: struct<count: int64, resolutions: list<item: struct<width: int64, height: int64, count: int64>>>
child 0, count: int64
child 1, resolutions: list<item: struct<width: int64, height: int64, count: int64>>
child 0, item: struct<width: int64, height: int64, count: int64>
child 0, width: int64
child 1, height: int64
child 2, count: int64
totals: struct<environment_maps: int64, training: int64, validation: int64, test: int64, completion_masks: i (... 5 chars omitted)
child 0, environment_maps: int64
child 1, training: int64
child 2, validation: int64
child 3, test: int64
child 4, completion_masks: int64
file_count: int64
files: list<item: struct<path: string, size_bytes: int64, sha256: string>>
child 0, item: struct<path: string, size_bytes: int64, sha256: string>
child 0, path: string
child 1, size_bytes: int64
child 2, sha256: string
total_bytes: int64
to
{'schema_version': Value('int64'), 'dataset': Value('string'), 'release_version': Value('string'), 'generator_commit': Value('string'), 'file_count': Value('int64'), 'total_bytes': Value('int64'), 'files': List({'path': Value('string'), 'size_bytes': Value('int64'), 'sha256': Value('string')})}
because column names don't matchNeed help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.
RENI HDR
RENI HDR is a curated dataset of outdoor, natural high-dynamic-range illumination environments used to train and evaluate RENI and RENI++. Each image is a full equirectangular environment map in linear RGB radiance.
| Property | Value |
|---|---|
| Environment maps | 1,704 |
| Training | 1,673 |
| Validation | 10 |
| Test | 21 |
| Fixed completion masks | 5 |
| Licence | CC0 1.0 |
| Release | 1.0 |
| Release date | 2026-07-30 |
| Release builder | 2159106d50f2ef38090c762e079840c0bb74fc6e |
The source panoramas were obtained under CC0 and manually curated. Images containing personally identifiable information, offensive content, or predominantly unnatural light sources were removed.
Contents
The archive extracts to the directory expected by ns_reni:
RENI_HDR/
train/ # 1,673 EXRs at 128 x 64
val/ # 10 high-resolution EXRs at 1024 x 512
test/ # 21 held-out EXRs at 128 x 64
masks/ # five fixed 512 x 256 completion masks
The test images are held out from decoder training and are used by fitting only their latent codes. The validation maps retain their high-resolution versions for qualitative evaluation; the loader resamples them when a fixed query resolution is requested.
This release deliberately excludes the working directory's later pseudo-sun labels, Blender files, object meshes, inverse-rendering renders and unrelated image assets. Those are not part of the curated illumination corpus.
Download
Download and verify the tagged release:
hf download jadgardner/reni-hdr \
--repo-type dataset \
--revision v1.0 \
--local-dir reni-hdr
(cd reni-hdr && sha256sum -c SHA256SUMS)
tar --zstd -xf reni-hdr/archives/reni-hdr.tar.zst -C /path/to/data
The result is /path/to/data/RENI_HDR, which can be passed directly to
RENI++:
ns-train reni --data /path/to/data/RENI_HDR
The archive can also be downloaded without the Hugging Face CLI:
curl -L \
"https://huggingface.co/datasets/jadgardner/reni-hdr/resolve/v1.0/archives/reni-hdr.tar.zst?download=true" \
-o reni-hdr.tar.zst
CONTENTS.json records the release-relative path, size and SHA256 of all
1,709 extracted files. DATASET_STATS.json records the validated split
counts and resolutions. MANIFEST.json and SHA256SUMS cover the
downloadable release files.
Provenance
The environments were curated from the CC0 sources listed in SOURCES.md.
The collected files were sequentially renamed during the original curation,
so a per-image source-name mapping is not available. This limitation is
recorded explicitly rather than inferring provenance after the fact.
Licence
The dataset is released under the
CC0 1.0 Universal Public Domain Dedication.
See LICENSE.md.
Citation
Please cite the RENI and RENI++ publications:
@inproceedings{gardner2022reni,
title = {Rotation-Equivariant Conditional Spherical Neural Fields for
Learning a Natural Illumination Prior},
author = {Gardner, James A. D. and Egger, Bernhard and
Smith, William A. P.},
booktitle = {Advances in Neural Information Processing Systems},
volume = {35},
pages = {26309--26323},
year = {2022}
}
@article{gardner2026renipp,
title = {{RENI++}: A Rotation-Equivariant, Scale-Invariant, Natural
Illumination Prior},
author = {Gardner, James A. D. and Egger, Bernhard and
Smith, William A. P.},
journal = {IEEE Transactions on Pattern Analysis and Machine Intelligence},
year = {2026},
doi = {10.1109/TPAMI.2026.3691593}
}
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