The dataset viewer is not available for this split.
Error code: StreamingRowsError
Exception: OSError
Message: cannot find loader for this HDF5 file
Traceback: Traceback (most recent call last):
File "/src/services/worker/src/worker/job_runners/split/first_rows.py", line 322, in compute
compute_first_rows_from_parquet_response(
File "/src/services/worker/src/worker/job_runners/split/first_rows.py", line 88, in compute_first_rows_from_parquet_response
rows_index = indexer.get_rows_index(
File "/src/libs/libcommon/src/libcommon/parquet_utils.py", line 640, in get_rows_index
return RowsIndex(
File "/src/libs/libcommon/src/libcommon/parquet_utils.py", line 521, in __init__
self.parquet_index = self._init_parquet_index(
File "/src/libs/libcommon/src/libcommon/parquet_utils.py", line 538, in _init_parquet_index
response = get_previous_step_or_raise(
File "/src/libs/libcommon/src/libcommon/simple_cache.py", line 591, in get_previous_step_or_raise
raise CachedArtifactError(
libcommon.simple_cache.CachedArtifactError: The previous step failed.
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "/src/services/worker/src/worker/utils.py", line 96, in get_rows_or_raise
return get_rows(
File "/src/libs/libcommon/src/libcommon/utils.py", line 197, in decorator
return func(*args, **kwargs)
File "/src/services/worker/src/worker/utils.py", line 73, in get_rows
rows_plus_one = list(itertools.islice(ds, rows_max_number + 1))
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/iterable_dataset.py", line 1820, in __iter__
example = _apply_feature_types_on_example(
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/iterable_dataset.py", line 1388, in _apply_feature_types_on_example
decoded_example = features.decode_example(encoded_example, token_per_repo_id=token_per_repo_id)
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/features/features.py", line 1986, in decode_example
return {
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/features/features.py", line 1987, in <dictcomp>
column_name: decode_nested_example(feature, value, token_per_repo_id=token_per_repo_id)
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/features/features.py", line 1351, in decode_nested_example
return schema.decode_example(obj, token_per_repo_id=token_per_repo_id)
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/features/image.py", line 188, in decode_example
image.load() # to avoid "Too many open files" errors
File "/src/services/worker/.venv/lib/python3.9/site-packages/PIL/ImageFile.py", line 366, in load
raise OSError(msg)
OSError: cannot find loader for this HDF5 fileNeed help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.
Object-Centric Learning with Object Constancy (OCLOC) Datasets
This repository contains the datasets used in the paper "Unsupervised Object-Centric Learning from Multiple Unspecified Viewpoints".
CLEVR and SHOP Datasets
The datasets named CLEVR and SHOP used in this paper are constructed based on the CLEVR dataset [Johnson et al., CVPR-17] and the SHOP-VRB dataset [Nazarczuk & Mikolajczyk, ICRA-20], respectively. The official code provided by the CLEVR and SHOP-VRB datasets are slightly modified to support generating images of the same visual scene from multiple viewpoints. Images in these datasets are first generated with size 214 x 160 and then cropped to size 128 x 128 at locations 19 (up), 147 (down), 43 (left), and 171 (right).
GSO and ShapeNet Datasets
The dataset named GSO used in this paper is constructed based on the combination of the GSO [Downs et al., ICRA-22] and HDRI-Haven datasets. The dataset named ShapeNet used in this paper is constructed based on the combination of the ShapeNet [Chang et al.] and HDRI-Haven datasets. Images in these datasets are generated using Kubric with size 128 x 128.
Configurations of Datasets
Row 1: names of datasets. Row 2: splits of datasets. Row 3: the number of visual scenes in each split. Row 4: the ranges to sample the number of objects per scene. Row 5: the number of viewpoints to observe each visual scene. Row 6: the height and width of each image. Rows 7-9: the ranges to sample viewpoints.
| Dataset | CLEVR / SHOP | GSO / ShapeNet | ||||||
| Split | Train | Valid | Test 1 | Test 2 | Train | Valid | Test 1 | Test 2 |
| Scenes | 5000 | 100 | 100 | 100 | 5000 | 100 | 100 | 100 |
| Objects | 3 ~ 6 | 3 ~ 6 | 3 ~ 6 | 7 ~ 10 | 3 ~ 6 | 3 ~ 6 | 3 ~ 6 | 7 ~ 10 |
| Viewpoints | 60 | 12 | ||||||
| Image Size | 128 x 128 | |||||||
| Azimuth | [0, 2π] | |||||||
| Elevation | [0.15π, 0.3π] | |||||||
| Distance | [10.5, 12] | |||||||
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