The dataset viewer is not available for this split.
Error code: StreamingRowsError
Exception: CastError
Message: Couldn't cast
scene: string
ref_shutter: double
ref_shutter_fraction: string
hdr_method: string
photos: list<item: struct<time: string, type: string, shooting_time: string, iso: int64, shutter_speed: stri (... 114 chars omitted)
child 0, item: struct<time: string, type: string, shooting_time: string, iso: int64, shutter_speed: string, num_ima (... 102 chars omitted)
child 0, time: string
child 1, type: string
child 2, shooting_time: string
child 3, iso: int64
child 4, shutter_speed: string
child 5, num_images: int64
child 6, source_files: list<item: string>
child 0, item: string
child 7, exposure_times: list<item: double>
child 0, item: double
child 8, ref_shutter: double
envmaps: list<item: struct<time: string, shooting_time: string, iso: int64, shutter_speed: string, num_exposu (... 69 chars omitted)
child 0, item: struct<time: string, shooting_time: string, iso: int64, shutter_speed: string, num_exposures: int64, (... 57 chars omitted)
child 0, time: string
child 1, shooting_time: string
child 2, iso: int64
child 3, shutter_speed: string
child 4, num_exposures: int64
child 5, exposure_times: list<item: double>
child 0, item: double
child 6, ref_shutter: double
alignment_method: string
gps: struct<latitude: double, longitude: double, altitude_m: double>
child 0, latitude: double
child 1, longitude: double
child 2, altitude_m: double
to
{'scene': Value('string'), 'ref_shutter': Value('float64'), 'ref_shutter_fraction': Value('string'), 'hdr_method': Value('string'), 'photos': List({'time': Value('string'), 'type': Value('string'), 'shooting_time': Value('string'), 'iso': Value('int64'), 'shutter_speed': Value('string'), 'num_images': Value('int64'), 'source_files': List(Value('string')), 'exposure_times': List(Value('float64')), 'ref_shutter': Value('float64')}), 'envmaps': List({'time': Value('string'), 'shooting_time': Value('string'), 'iso': Value('int64'), 'shutter_speed': Value('string'), 'num_exposures': Value('int64'), 'exposure_times': List(Value('float64')), 'ref_shutter': Value('float64')}), 'alignment_method': Value('string')}
because column names don't match
Traceback: Traceback (most recent call last):
File "/src/services/worker/src/worker/utils.py", line 99, in get_rows_or_raise
return get_rows(
^^^^^^^^^
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 77, in get_rows
rows_plus_one = list(itertools.islice(ds, rows_max_number + 1))
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 2690, in __iter__
for key, example in ex_iterable:
^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 2227, in __iter__
for key, pa_table in self._iter_arrow():
^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 2251, in _iter_arrow
for key, pa_table in self.ex_iterable._iter_arrow():
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 494, in _iter_arrow
for key, pa_table in iterator:
^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 384, in _iter_arrow
for key, pa_table in self.generate_tables_fn(**gen_kwags):
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/packaged_modules/json/json.py", line 299, in _generate_tables
self._cast_table(pa_table, json_field_paths=json_field_paths),
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/packaged_modules/json/json.py", line 128, in _cast_table
pa_table = table_cast(pa_table, self.info.features.arrow_schema)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/table.py", line 2321, in table_cast
return cast_table_to_schema(table, schema)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/table.py", line 2249, in cast_table_to_schema
raise CastError(
datasets.table.CastError: Couldn't cast
scene: string
ref_shutter: double
ref_shutter_fraction: string
hdr_method: string
photos: list<item: struct<time: string, type: string, shooting_time: string, iso: int64, shutter_speed: stri (... 114 chars omitted)
child 0, item: struct<time: string, type: string, shooting_time: string, iso: int64, shutter_speed: string, num_ima (... 102 chars omitted)
child 0, time: string
child 1, type: string
child 2, shooting_time: string
child 3, iso: int64
child 4, shutter_speed: string
child 5, num_images: int64
child 6, source_files: list<item: string>
child 0, item: string
child 7, exposure_times: list<item: double>
child 0, item: double
child 8, ref_shutter: double
envmaps: list<item: struct<time: string, shooting_time: string, iso: int64, shutter_speed: string, num_exposu (... 69 chars omitted)
child 0, item: struct<time: string, shooting_time: string, iso: int64, shutter_speed: string, num_exposures: int64, (... 57 chars omitted)
child 0, time: string
child 1, shooting_time: string
child 2, iso: int64
child 3, shutter_speed: string
child 4, num_exposures: int64
child 5, exposure_times: list<item: double>
child 0, item: double
child 6, ref_shutter: double
alignment_method: string
gps: struct<latitude: double, longitude: double, altitude_m: double>
child 0, latitude: double
child 1, longitude: double
child 2, altitude_m: double
to
{'scene': Value('string'), 'ref_shutter': Value('float64'), 'ref_shutter_fraction': Value('string'), 'hdr_method': Value('string'), 'photos': List({'time': Value('string'), 'type': Value('string'), 'shooting_time': Value('string'), 'iso': Value('int64'), 'shutter_speed': Value('string'), 'num_images': Value('int64'), 'source_files': List(Value('string')), 'exposure_times': List(Value('float64')), 'ref_shutter': Value('float64')}), 'envmaps': List({'time': Value('string'), 'shooting_time': Value('string'), 'iso': Value('int64'), 'shutter_speed': Value('string'), 'num_exposures': Value('int64'), 'exposure_times': List(Value('float64')), 'ref_shutter': Value('float64')}), 'alignment_method': 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.
WildRelight Dataset
A real-world relighting dataset of 30 outdoor/semi-indoor scenes captured across multiple time steps throughout the day. Each scene provides paired HDR photographs and HDR environment maps, enabling evaluation of outdoor relighting tasks.
Download Command
Download small resolution for quick verification.
hf download lez/wildrelight --repo-type dataset --include "small-aligned/**" --local-dir ./wildrelight/small-aligned
Download full resolution dataset.
hf download lez/wildrelight --repo-type dataset --include "ori-aligned/**" --local-dir ./wildrelight/ori-aligned
Key Statistics
| Property | Value |
|---|---|
| Scenes | 30 |
| Time steps per scene | 6β8 (spaced ~1 hour apart) |
| Total HDR photo/envmap pairs | 196 |
| Photo resolution (full) | 6048 Γ 4024 px |
| Envmap resolution (full) | 7680 Γ 3840 px (equirectangular) |
| Photo resolution (small) | 1200 Γ ~798 px |
| Envmap resolution (small) | 1200 Γ 600 px |
| File format | OpenEXR |
| HDR normalization | Radiance at reference shutter speed (1/500 β 1/10 s, per scene) |
Equipment
- Main camera: Sony Ξ±7 series β RAW
- 360Β° camera: Insta360 Pro2 β 6-lens equidistant fisheye, stitched to equirectangular
Dataset Variants
Two resolution variants are provided under ori/ and small/. Within each variant, every scene contains four folders:
{variant}/{scene}/
βββ photo/ # HDR photograph (unaligned)
βββ photo_aligned/ # HDR photograph (temporally aligned, recommended)
βββ envmap/ # HDR environment map (unaligned)
βββ envmap_aligned/ # HDR environment map (temporally aligned, recommended)
Both photo_aligned/ and envmap_aligned/ are temporally aligned to the first time step β each image is warped so that the static background is registered across time. Use these for relighting experiments.
File Naming
photo/ time{N}_hdr.exr (N = 0, 1, 2, β¦)
envmap/ time{N}_envmap.exr
Metadata
Each scene contains a meta.json with:
| Field | Description |
|---|---|
scene |
Scene name |
ref_shutter |
Reference shutter speed (seconds) used for HDR normalization |
ref_shutter_fraction |
Human-readable, e.g. "1/500" |
hdr_method |
HDR merge algorithm (triangular_weight_debevec1997) |
alignment_method |
life_optical_flow or cv2_sift_homography |
gps |
{latitude, longitude, altitude_m} β available for 10 scenes |
photos[].shooting_time |
Capture timestamp from EXIF |
photos[].iso |
ISO speed |
photos[].shutter_speed |
Representative shutter speed (human-readable) |
envmaps[].shooting_time |
Capture timestamp |
envmaps[].shutter_speed |
Envmap shutter speed |
Scene List
GPS coordinates are provided as additional information. Since collecting GPS coordinates was not part of the original plan, only 10 scenes contain GPS coordinates.
| Scene | Time steps | Alignment | GPS |
|---|---|---|---|
| bench2 | 6 | LIFE flow | β |
| bench3 | 6 | LIFE flow | β |
| bike | 6 | LIFE flow | yes |
| bikes2 | 6 | LIFE flow | β |
| bridge | 6 | LIFE flow | β |
| building304 | 6 | LIFE flow | β |
| building324 | 7 | LIFE flow | β |
| byway | 6 | LIFE flow | yes |
| cabin | 6 | CV2/SIFT | β |
| corridor | 6 | LIFE flow | yes |
| foodtruck | 6 | LIFE flow | yes |
| garden | 6 | LIFE flow | β |
| grassland | 7 | LIFE flow | yes |
| grassland2 | 6 | LIFE flow | yes |
| indoor | 6 | CV2/SIFT | β |
| lake | 6 | LIFE flow | β |
| meadow | 6 | LIFE flow | β |
| parking | 7 | LIFE flow | β |
| pillar | 6 | LIFE flow | β |
| playground | 7 | LIFE flow | β |
| rail | 7 | LIFE flow | β |
| road | 7 | LIFE flow | β |
| sand | 6 | CV2/SIFT | β |
| seaside | 8 | CV2/SIFT | β |
| stairs | 6 | LIFE flow | yes |
| statue | 6 | LIFE flow | yes |
| statue2 | 6 | LIFE flow | yes |
| table_tennis | 6 | LIFE flow | yes |
| wall | 6 | LIFE flow | β |
| yatai | 7 | LIFE flow | β |
Temporal Alignment
Photos are aligned to time0 of each scene. Two methods are used depending on scene content:
- LIFE optical flow (26 scenes): dense flow-based warping, handles gradual lighting changes and small camera motion
- CV2/SIFT homography (4 scenes:
cabin,indoor,sand,seaside): feature-based homography, used when flow alignment fails due to detailed textures.
Alignment is computed independently for ori and small resolutions. Environment maps are aligned using phase-correlation-based rotation estimation.
License
This dataset is released under the Creative Commons Attribution 4.0 International (CC BY 4.0) license.
Citation
If you use this dataset, please cite:
@misc{wang2026wildrelight,
title={WildRelight: A Real-World Benchmark and Physics-Guided Adaptation for Single-Image Relighting},
author={Lezhong Wang and Mehmet Onurcan Kaya and Siavash Bigdeli and Jeppe Revall Frisvad},
year={2026},
eprint={2605.11696},
archivePrefix={arXiv},
primaryClass={cs.CV},
url={https://arxiv.org/abs/2605.11696},
}
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