desmondlzy/bigs
Updated
Dataset Preview
The full dataset viewer is not available (click to read why). Only showing a preview of the rows.
The dataset generation failed because of a cast error
Error code: DatasetGenerationCastError
Exception: DatasetGenerationCastError
Message: An error occurred while generating the dataset
All the data files must have the same columns, but at some point there are 2 new columns ({'light_power', 'light_type'})
This happened while the json dataset builder was generating data using
hf://datasets/desmondlzy/bigs-data/dragon/olat_1/transforms_train.json (at revision 5b82f88ef44341ccb12cac2e4675c8367174de69)
Please either edit the data files to have matching columns, or separate them into different configurations (see docs at https://hf.co/docs/hub/datasets-manual-configuration#multiple-configurations)
Traceback: Traceback (most recent call last):
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 1870, in _prepare_split_single
writer.write_table(table)
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/arrow_writer.py", line 622, in write_table
pa_table = table_cast(pa_table, self._schema)
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/table.py", line 2292, in table_cast
return cast_table_to_schema(table, schema)
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/table.py", line 2240, in cast_table_to_schema
raise CastError(
datasets.table.CastError: Couldn't cast
fl_x: double
fl_y: double
cx: double
cy: double
w: int64
h: int64
light_type: string
light: list<item: double>
child 0, item: double
light_power: int64
frames: list<item: struct<file_path: string, transform_matrix: list<item: list<item: double>>, obj_mask_path: string, com_mask_path: string, light: struct<type: string, position: list<item: double>, intensity: int64>>>
child 0, item: struct<file_path: string, transform_matrix: list<item: list<item: double>>, obj_mask_path: string, com_mask_path: string, light: struct<type: string, position: list<item: double>, intensity: int64>>
child 0, file_path: string
child 1, transform_matrix: list<item: list<item: double>>
child 0, item: list<item: double>
child 0, item: double
child 2, obj_mask_path: string
child 3, com_mask_path: string
child 4, light: struct<type: string, position: list<item: double>, intensity: int64>
child 0, type: string
child 1, position: list<item: double>
child 0, item: double
child 2, intensity: int64
to
{'fl_x': Value(dtype='float64', id=None), 'fl_y': Value(dtype='float64', id=None), 'cx': Value(dtype='float64', id=None), 'cy': Value(dtype='float64', id=None), 'w': Value(dtype='int64', id=None), 'h': Value(dtype='int64', id=None), 'light': Sequence(feature=Value(dtype='float64', id=None), length=-1, id=None), 'frames': [{'file_path': Value(dtype='string', id=None), 'transform_matrix': Sequence(feature=Sequence(feature=Value(dtype='float64', id=None), length=-1, id=None), length=-1, id=None), 'obj_mask_path': Value(dtype='string', id=None), 'com_mask_path': Value(dtype='string', id=None), 'light': {'type': Value(dtype='string', id=None), 'position': Sequence(feature=Value(dtype='float64', id=None), length=-1, id=None), 'intensity': Value(dtype='float64', id=None)}}]}
because column names don't match
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 1433, in compute_config_parquet_and_info_response
parquet_operations, partial, estimated_dataset_info = stream_convert_to_parquet(
File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 989, in stream_convert_to_parquet
builder._prepare_split(
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 1741, in _prepare_split
for job_id, done, content in self._prepare_split_single(
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 1872, in _prepare_split_single
raise DatasetGenerationCastError.from_cast_error(
datasets.exceptions.DatasetGenerationCastError: An error occurred while generating the dataset
All the data files must have the same columns, but at some point there are 2 new columns ({'light_power', 'light_type'})
This happened while the json dataset builder was generating data using
hf://datasets/desmondlzy/bigs-data/dragon/olat_1/transforms_train.json (at revision 5b82f88ef44341ccb12cac2e4675c8367174de69)
Please either edit the data files to have matching columns, or separate them into different configurations (see docs at https://hf.co/docs/hub/datasets-manual-configuration#multiple-configurations)Need help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.
fl_x float64 | fl_y float64 | cx float64 | cy float64 | w int64 | h int64 | light sequence | frames list |
|---|---|---|---|---|---|---|---|
787.886986 | 787.886986 | 256 | 256 | 512 | 512 | [
-3.6180000000000003,
2.2359999999999998,
2.6285
] | [
{
"file_path": "./img/1_0.exr",
"transform_matrix": [
[
0,
-4.371139183945161e-8,
-1,
-5
],
[
1,
0,
0,
0
],
[
0,
-1,
4.371139183945161e-8,
2.18556948539117e-7
],
[
... |
787.886986 | 787.886986 | 256 | 256 | 512 | 512 | [
-2.1645,
2.584,
3.693
] | [
{
"file_path": "./img/10_0.exr",
"transform_matrix": [
[
0,
-4.371139183945161e-8,
-1,
-5
],
[
1,
0,
0,
0
],
[
0,
-1,
4.371139183945161e-8,
2.18556948539117e-7
],
[
... |
787.886986 | 787.886986 | 256 | 256 | 512 | 512 | [
-0.4195,
2.584,
4.26
] | [
{
"file_path": "./img/11_0.exr",
"transform_matrix": [
[
0,
-4.371139183945161e-8,
-1,
-5
],
[
1,
0,
0,
0
],
[
0,
-1,
4.371139183945161e-8,
2.18556948539117e-7
],
[
... |
787.886986 | 787.886986 | 256 | 256 | 512 | 512 | [
2.8434999999999997,
2.584,
3.1995
] | [
{
"file_path": "./img/12_0.exr",
"transform_matrix": [
[
0,
-4.371139183945161e-8,
-1,
-5
],
[
1,
0,
0,
0
],
[
0,
-1,
4.371139183945161e-8,
2.18556948539117e-7
],
[
... |
787.886986 | 787.886986 | 256 | 256 | 512 | 512 | [
3.9219999999999997,
2.584,
1.7155
] | [
{
"file_path": "./img/13_0.exr",
"transform_matrix": [
[
0,
-4.371139183945161e-8,
-1,
-5
],
[
1,
0,
0,
0
],
[
0,
-1,
4.371139183945161e-8,
2.18556948539117e-7
],
[
... |
787.886986 | 787.886986 | 256 | 256 | 512 | 512 | [
-3.2790000000000004,
0.7805,
3.693
] | [
{
"file_path": "./img/14_0.exr",
"transform_matrix": [
[
0,
-4.371139183945161e-8,
-1,
-5
],
[
1,
0,
0,
0
],
[
0,
-1,
4.371139183945161e-8,
2.18556948539117e-7
],
[
... |
787.886986 | 787.886986 | 256 | 256 | 512 | 512 | [
-2.499,
-0.7805,
4.26
] | [
{
"file_path": "./img/15_0.exr",
"transform_matrix": [
[
0,
-4.371139183945161e-8,
-1,
-5
],
[
1,
0,
0,
0
],
[
0,
-1,
4.371139183945161e-8,
2.18556948539117e-7
],
[
... |
787.886986 | 787.886986 | 256 | 256 | 512 | 512 | [
2.499,
0.7805,
4.26
] | [
{
"file_path": "./img/16_0.exr",
"transform_matrix": [
[
0,
-4.371139183945161e-8,
-1,
-5
],
[
1,
0,
0,
0
],
[
0,
-1,
4.371139183945161e-8,
2.18556948539117e-7
],
[
... |
787.886986 | 787.886986 | 256 | 256 | 512 | 512 | [
3.2790000000000004,
-0.7805,
3.693
] | [
{
"file_path": "./img/17_0.exr",
"transform_matrix": [
[
0,
-4.371139183945161e-8,
-1,
-5
],
[
1,
0,
0,
0
],
[
0,
-1,
4.371139183945161e-8,
2.18556948539117e-7
],
[
... |
787.886986 | 787.886986 | 256 | 256 | 512 | 512 | [
4.8235,
0.7805,
1.06
] | [{"file_path":"./img/18_0.exr","transform_matrix":[[0.0,-4.371139183945161e-8,-1.0,-5.0],[1.0,0.0,-0(...TRUNCATED) |
End of preview.
BiGS Dataset
The OLAT dataset used in the paper BiGS: Bidirectional Primitives for Relightable 3D Gaussian Splatting (3DV 2025). Check out our project page.
We provide 7 synthetic scenes in the dataset, featuring various complex light transport effects, such as subsurface scattering, fuzzy surfaces, and iridescent reflection.
Each scene (1.8 ~ 3.2 GB) consists of:
- 40 training OLAT conditions (
olat_1-olat_40) with 48 views per light condition; - 58 test OLAT conditions (
olat_41-olat_98) with 1 view per light condition; - 1 all-light-on conditions (
olat_all) with 48 views per light conditions.
Each light condition includes .exr images, object masks, transforms with camera poses, light positions and intensities.
Please refer to our github repo for how to use the dataset provided here to train BiGS, and our paper (arxiv) for details of BiGS.
Citation
If you use our dataset in your research, please consider citing us with the below bibtex entry:
@misc{zhenyuan2024bigs,
title={BiGS: Bidirectional Primitives for Relightable 3D Gaussian Splatting},
author={Liu Zhenyuan and Yu Guo and Xinyuan Li and Bernd Bickel and Ran Zhang},
year={2024},
eprint={2408.13370},
url={https://arxiv.org/abs/2408.13370},
}
Acknowledgments
Our synthetic data is generated using Mitsuba. We thank the 3D models' creators: Keenan Crane for Spot; Stanford Computer Graphics Laboratory for the models Dragon and Bunny; Wenzel Jakob for the model Mistuba Ball. Special thanks to Changxi Zheng for supporting the internship program at Tencent Pixel Lab.
- Downloads last month
- 1,675
Models trained or fine-tuned on desmondlzy/bigs-data