Dataset Preview
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The dataset generation failed
Error code: DatasetGenerationError
Exception: ArrowNotImplementedError
Message: Cannot write struct type 'driver_parameters' with no child field to Parquet. Consider adding a dummy child field.
Traceback: Traceback (most recent call last):
File "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 1821, in _prepare_split_single
num_examples, num_bytes = writer.finalize()
^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/arrow_writer.py", line 781, in finalize
self.write_rows_on_file()
File "/usr/local/lib/python3.12/site-packages/datasets/arrow_writer.py", line 663, in write_rows_on_file
self._write_table(table)
File "/usr/local/lib/python3.12/site-packages/datasets/arrow_writer.py", line 771, in _write_table
self._build_writer(inferred_schema=pa_table.schema)
File "/usr/local/lib/python3.12/site-packages/datasets/arrow_writer.py", line 812, in _build_writer
self.pa_writer = pq.ParquetWriter(
^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/pyarrow/parquet/core.py", line 1070, in __init__
self.writer = _parquet.ParquetWriter(
^^^^^^^^^^^^^^^^^^^^^^^
File "pyarrow/_parquet.pyx", line 2363, in pyarrow._parquet.ParquetWriter.__cinit__
File "pyarrow/error.pxi", line 155, in pyarrow.lib.pyarrow_internal_check_status
File "pyarrow/error.pxi", line 92, in pyarrow.lib.check_status
pyarrow.lib.ArrowNotImplementedError: Cannot write struct type 'driver_parameters' with no child field to Parquet. Consider adding a dummy child field.
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 1348, in compute_config_parquet_and_info_response
parquet_operations = convert_to_parquet(builder)
^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 980, in convert_to_parquet
builder.download_and_prepare(
File "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 882, in download_and_prepare
self._download_and_prepare(
File "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 943, in _download_and_prepare
self._prepare_split(split_generator, **prepare_split_kwargs)
File "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 1646, in _prepare_split
for job_id, done, content in self._prepare_split_single(
^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 1832, in _prepare_split_single
raise DatasetGenerationError("An error occurred while generating the dataset") from e
datasets.exceptions.DatasetGenerationError: An error occurred while generating the datasetNeed help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.
camera_angle_x float64 | frames list |
|---|---|
0.691111 | [
{
"file_path": "./rgb/cam_00.png",
"heat_img_path": "./linear/cam_00.exr",
"transform_matrix": [
[
-0.09085416048765182,
-0.02132938988506794,
0.9956357479095459,
4.978178977966309
],
[
0.99586421251297,
-0.0019458252936601639,
0.... |
0.691111 | [
{
"file_path": "./rgb/cam_00.png",
"heat_img_path": "./linear/cam_00.exr",
"transform_matrix": [
[
0.04710321128368378,
0.007042908109724522,
0.9988651871681213,
4.994326114654541
],
[
0.9988900423049927,
-0.00033218867611140013,
... |
0.691111 | [
{
"file_path": "./rgb/cam_00.png",
"heat_img_path": "./linear/cam_00.exr",
"transform_matrix": [
[
0.004808125086128712,
-0.017197711393237114,
0.9998405575752258,
4.999202728271484
],
[
0.9999884366989136,
0.00008267878729384392,
... |
0.691111 | [
{
"file_path": "./rgb/cam_00.png",
"heat_img_path": "./linear/cam_00.exr",
"transform_matrix": [
[
-0.13065798580646515,
-0.013294464908540249,
0.9913383722305298,
4.956691741943359
],
[
0.991427481174469,
-0.0017519736429676414,
... |
0.691111 | [
{
"file_path": "./rgb/cam_00.png",
"heat_img_path": "./linear/cam_00.exr",
"transform_matrix": [
[
-0.09085416048765182,
-0.02132938988506794,
0.9956357479095459,
4.978178977966309
],
[
0.99586421251297,
-0.0019458252936601639,
0.... |
0.691111 | [{"file_path":"./rgb/cam_00.png","heat_img_path":"./linear/cam_00.exr","transform_matrix":[[0.047103(...TRUNCATED) |
0.691111 | [{"file_path":"./rgb/cam_00.png","heat_img_path":"./linear/cam_00.exr","transform_matrix":[[0.004808(...TRUNCATED) |
0.691111 | [{"file_path":"./rgb/cam_00.png","heat_img_path":"./linear/cam_00.exr","transform_matrix":[[7.549790(...TRUNCATED) |
0.691111 | [{"file_path":"./rgb/cam_00.png","heat_img_path":"./linear/cam_00.exr","transform_matrix":[[7.549790(...TRUNCATED) |
0.691111 | [{"file_path":"./rgb/cam_00.png","heat_img_path":"./linear/cam_00.exr","transform_matrix":[[7.549790(...TRUNCATED) |
End of preview.
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Check out the documentation for more information.
HiGS Dataset
The dataset accompanying the paper "HiGS: Inverse Radiative Transport for Infrared Scenes with Gaussian Primitives".
The repo contains 4 synthetic RGB-thermal scenes, each has 4 distinct heating conditions: bunny, human, radiator, and torus.
There is also a real capture dataset included: teapot.
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