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jhu-ccvl
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syscon3d

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train
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
dataset_root: string
full_mixture_distinct_scene: list<item: struct<image_rel_paths: list<item: string>, sample_id: string, subset_size: int64>>
  child 0, item: struct<image_rel_paths: list<item: string>, sample_id: string, subset_size: int64>
      child 0, image_rel_paths: list<item: string>
          child 0, item: string
      child 1, sample_id: string
      child 2, subset_size: int64
identical_images: list<item: struct<image_rel_paths: list<item: string>, sample_id: string, subset_size: int64>>
  child 0, item: struct<image_rel_paths: list<item: string>, sample_id: string, subset_size: int64>
      child 0, image_rel_paths: list<item: string>
          child 0, item: string
      child 1, sample_id: string
      child 2, subset_size: int64
mixed: list<item: struct<image_rel_paths: list<item: string>, sample_id: string, subset_size: int64>>
  child 0, item: struct<image_rel_paths: list<item: string>, sample_id: string, subset_size: int64>
      child 0, image_rel_paths: list<item: string>
          child 0, item: string
      child 1, sample_id: string
      child 2, subset_size: int64
mixed_controlled: list<item: struct<image_rel_paths: list<item: string>, sample_id: string, subset_size: int64>>
  child 0, item: struct<image_rel_paths: list<item: string>, sample_id: string, subset_size: int64>
      child 0, image_rel_paths: list<item: string>
          child 0, item: string
      child 1, sample_id: string
      child 2, subset_size: int64
mixed_one_outlier: list<ite
...
     child 3, 21: list<item: int64>
          child 0, item: int64
      child 4, 3: list<item: int64>
          child 0, item: int64
      child 5, 6: list<item: int64>
          child 0, item: int64
      child 6, 9: list<item: int64>
          child 0, item: int64
  child 7, stump: struct<12: list<item: int64>, 15: list<item: int64>, 18: list<item: int64>, 21: list<item: int64>, 3 (... 64 chars omitted)
      child 0, 12: list<item: int64>
          child 0, item: int64
      child 1, 15: list<item: int64>
          child 0, item: int64
      child 2, 18: list<item: int64>
          child 0, item: int64
      child 3, 21: list<item: int64>
          child 0, item: int64
      child 4, 3: list<item: int64>
          child 0, item: int64
      child 5, 6: list<item: int64>
          child 0, item: int64
      child 6, 9: list<item: int64>
          child 0, item: int64
  child 8, treehill: struct<12: list<item: int64>, 15: list<item: int64>, 18: list<item: int64>, 21: list<item: int64>, 3 (... 64 chars omitted)
      child 0, 12: list<item: int64>
          child 0, item: int64
      child 1, 15: list<item: int64>
          child 0, item: int64
      child 2, 18: list<item: int64>
          child 0, item: int64
      child 3, 21: list<item: int64>
          child 0, item: int64
      child 4, 3: list<item: int64>
          child 0, item: int64
      child 5, 6: list<item: int64>
          child 0, item: int64
      child 6, 9: list<item: int64>
          child 0, item: int64
to
{'dataset_root': Value('string'), 'scenes': {'bicycle': {'12': List(Value('int64')), '15': List(Value('int64')), '18': List(Value('int64')), '21': List(Value('int64')), '3': List(Value('int64')), '6': List(Value('int64')), '9': List(Value('int64'))}, 'bonsai': {'12': List(Value('int64')), '15': List(Value('int64')), '18': List(Value('int64')), '21': List(Value('int64')), '3': List(Value('int64')), '6': List(Value('int64')), '9': List(Value('int64'))}, 'counter': {'12': List(Value('int64')), '15': List(Value('int64')), '18': List(Value('int64')), '21': List(Value('int64')), '3': List(Value('int64')), '6': List(Value('int64')), '9': List(Value('int64'))}, 'flowers': {'12': List(Value('int64')), '15': List(Value('int64')), '18': List(Value('int64')), '21': List(Value('int64')), '3': List(Value('int64')), '6': List(Value('int64')), '9': List(Value('int64'))}, 'garden': {'12': List(Value('int64')), '15': List(Value('int64')), '18': List(Value('int64')), '21': List(Value('int64')), '3': List(Value('int64')), '6': List(Value('int64')), '9': List(Value('int64'))}, 'kitchen': {'12': List(Value('int64')), '15': List(Value('int64')), '18': List(Value('int64')), '21': List(Value('int64')), '3': List(Value('int64')), '6': List(Value('int64')), '9': List(Value('int64'))}, 'room': {'12': List(Value('int64')), '15': List(Value('int64')), '18': List(Value('int64')), '21': List(Value('int64')), '3': List(Value('int64')), '6': List(Value('int64')), '9': List(Value('int64'))}, 'stump': {'12': List(Value('int64')), '15': List(Value('int64')), '18': List(Value('int64')), '21': List(Value('int64')), '3': List(Value('int64')), '6': List(Value('int64')), '9': List(Value('int64'))}, 'treehill': {'12': List(Value('int64')), '15': List(Value('int64')), '18': List(Value('int64')), '21': List(Value('int64')), '3': List(Value('int64')), '6': List(Value('int64')), '9': List(Value('int64'))}}, 'subset_sizes': List(Value('int64'))}
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 295, 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
              dataset_root: string
              full_mixture_distinct_scene: list<item: struct<image_rel_paths: list<item: string>, sample_id: string, subset_size: int64>>
                child 0, item: struct<image_rel_paths: list<item: string>, sample_id: string, subset_size: int64>
                    child 0, image_rel_paths: list<item: string>
                        child 0, item: string
                    child 1, sample_id: string
                    child 2, subset_size: int64
              identical_images: list<item: struct<image_rel_paths: list<item: string>, sample_id: string, subset_size: int64>>
                child 0, item: struct<image_rel_paths: list<item: string>, sample_id: string, subset_size: int64>
                    child 0, image_rel_paths: list<item: string>
                        child 0, item: string
                    child 1, sample_id: string
                    child 2, subset_size: int64
              mixed: list<item: struct<image_rel_paths: list<item: string>, sample_id: string, subset_size: int64>>
                child 0, item: struct<image_rel_paths: list<item: string>, sample_id: string, subset_size: int64>
                    child 0, image_rel_paths: list<item: string>
                        child 0, item: string
                    child 1, sample_id: string
                    child 2, subset_size: int64
              mixed_controlled: list<item: struct<image_rel_paths: list<item: string>, sample_id: string, subset_size: int64>>
                child 0, item: struct<image_rel_paths: list<item: string>, sample_id: string, subset_size: int64>
                    child 0, image_rel_paths: list<item: string>
                        child 0, item: string
                    child 1, sample_id: string
                    child 2, subset_size: int64
              mixed_one_outlier: list<ite
              ...
                   child 3, 21: list<item: int64>
                        child 0, item: int64
                    child 4, 3: list<item: int64>
                        child 0, item: int64
                    child 5, 6: list<item: int64>
                        child 0, item: int64
                    child 6, 9: list<item: int64>
                        child 0, item: int64
                child 7, stump: struct<12: list<item: int64>, 15: list<item: int64>, 18: list<item: int64>, 21: list<item: int64>, 3 (... 64 chars omitted)
                    child 0, 12: list<item: int64>
                        child 0, item: int64
                    child 1, 15: list<item: int64>
                        child 0, item: int64
                    child 2, 18: list<item: int64>
                        child 0, item: int64
                    child 3, 21: list<item: int64>
                        child 0, item: int64
                    child 4, 3: list<item: int64>
                        child 0, item: int64
                    child 5, 6: list<item: int64>
                        child 0, item: int64
                    child 6, 9: list<item: int64>
                        child 0, item: int64
                child 8, treehill: struct<12: list<item: int64>, 15: list<item: int64>, 18: list<item: int64>, 21: list<item: int64>, 3 (... 64 chars omitted)
                    child 0, 12: list<item: int64>
                        child 0, item: int64
                    child 1, 15: list<item: int64>
                        child 0, item: int64
                    child 2, 18: list<item: int64>
                        child 0, item: int64
                    child 3, 21: list<item: int64>
                        child 0, item: int64
                    child 4, 3: list<item: int64>
                        child 0, item: int64
                    child 5, 6: list<item: int64>
                        child 0, item: int64
                    child 6, 9: list<item: int64>
                        child 0, item: int64
              to
              {'dataset_root': Value('string'), 'scenes': {'bicycle': {'12': List(Value('int64')), '15': List(Value('int64')), '18': List(Value('int64')), '21': List(Value('int64')), '3': List(Value('int64')), '6': List(Value('int64')), '9': List(Value('int64'))}, 'bonsai': {'12': List(Value('int64')), '15': List(Value('int64')), '18': List(Value('int64')), '21': List(Value('int64')), '3': List(Value('int64')), '6': List(Value('int64')), '9': List(Value('int64'))}, 'counter': {'12': List(Value('int64')), '15': List(Value('int64')), '18': List(Value('int64')), '21': List(Value('int64')), '3': List(Value('int64')), '6': List(Value('int64')), '9': List(Value('int64'))}, 'flowers': {'12': List(Value('int64')), '15': List(Value('int64')), '18': List(Value('int64')), '21': List(Value('int64')), '3': List(Value('int64')), '6': List(Value('int64')), '9': List(Value('int64'))}, 'garden': {'12': List(Value('int64')), '15': List(Value('int64')), '18': List(Value('int64')), '21': List(Value('int64')), '3': List(Value('int64')), '6': List(Value('int64')), '9': List(Value('int64'))}, 'kitchen': {'12': List(Value('int64')), '15': List(Value('int64')), '18': List(Value('int64')), '21': List(Value('int64')), '3': List(Value('int64')), '6': List(Value('int64')), '9': List(Value('int64'))}, 'room': {'12': List(Value('int64')), '15': List(Value('int64')), '18': List(Value('int64')), '21': List(Value('int64')), '3': List(Value('int64')), '6': List(Value('int64')), '9': List(Value('int64'))}, 'stump': {'12': List(Value('int64')), '15': List(Value('int64')), '18': List(Value('int64')), '21': List(Value('int64')), '3': List(Value('int64')), '6': List(Value('int64')), '9': List(Value('int64'))}, 'treehill': {'12': List(Value('int64')), '15': List(Value('int64')), '18': List(Value('int64')), '21': List(Value('int64')), '3': List(Value('int64')), '6': List(Value('int64')), '9': List(Value('int64'))}}, 'subset_sizes': List(Value('int64'))}
              because column names don't match
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SysCON3D

Portable release bundle for the SysCON3D benchmark and demo.
mipnerf360_calibration_splits.json: consistent-scene calibration splits.
mipnerf360_impossible_splits.json: precomputed SysCON3D benchmark samples.
archives/syscon3d_mipnerf360_*.tar: tar shards containing mipnerf360/... payload files.
Release summary

scenes: bicycle, bonsai, counter, flowers, garden, kitchen, room, stump, treehill
copy mode: all-images4
storage mode: tar-shards
copied files: 2464
copied size (GiB): 1.432
archive files: 1
Notes

The manifests in this folder use dataset_root: mipnerf360, so they are portable across local runs and Spaces.
If this release uses archives/, extract those tar files before running tools that expect the raw mipnerf360/ directory.
If you release this bundle publicly, fill in the appropriate citation and licensing text for the underlying source data.
Downloads last month: 25
Total file size:
1.54 GB
SysCON3D

Contents

Release summary

Notes
