Datasets:
The dataset viewer is not available for this split.
Error code: StreamingRowsError
Exception: ValueError
Message: Expected object or value
Traceback: Traceback (most recent call last):
File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/json/json.py", line 290, in _generate_tables
pa_table = paj.read_json(
io.BytesIO(batch), read_options=paj.ReadOptions(block_size=block_size)
)
File "pyarrow/_json.pyx", line 342, in pyarrow._json.read_json
File "pyarrow/error.pxi", line 155, in pyarrow.lib.pyarrow_internal_check_status
File "pyarrow/error.pxi", line 92, in pyarrow.lib.check_status
raise convert_status(status)
pyarrow.lib.ArrowInvalid: JSON parse error: Column() changed from object to string in row 0
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "/src/services/worker/src/worker/utils.py", line 147, in get_rows_or_raise
return get_rows(
dataset=dataset,
...<4 lines>...
column_names=column_names,
)
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 127, in get_rows
rows_plus_one = list(itertools.islice(safe_iter(ds, dataset=dataset), rows_max_number + 1))
File "/src/services/worker/src/worker/utils.py", line 483, in safe_iter
yield from ds.decode(False) if ds.features else ds
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2840, in __iter__
for key, example in ex_iterable:
^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2373, in __iter__
for key, pa_table in self._iter_arrow():
~~~~~~~~~~~~~~~~^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2398, in _iter_arrow
for key, pa_table in self.ex_iterable._iter_arrow():
~~~~~~~~~~~~~~~~~~~~~~~~~~~~^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 536, in _iter_arrow
for key, pa_table in iterator:
^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 419, in _iter_arrow
for key, pa_table in self.generate_tables_fn(**gen_kwags):
~~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/json/json.py", line 304, in _generate_tables
batch = json_encode_fields_in_json_lines(original_batch, json_field_paths)
File "/usr/local/lib/python3.14/site-packages/datasets/utils/json.py", line 111, in json_encode_fields_in_json_lines
examples = [ujson_loads(line) for line in original_batch.splitlines()]
~~~~~~~~~~~^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/utils/json.py", line 20, in ujson_loads
return pd.io.json.ujson_loads(*args, **kwargs)
~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^
ValueError: Expected object or valueNeed help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.
GeoBench V1 - pickle-free sharded edition
This is a data-only metadata conversion of the six classification datasets in isaaccorley/geobenchv1-webdataset, pinned at revision cb847e5ff87a2c8f00064d631ed7b6a39a084c68. The original benchmark is GEO-Bench.
The image arrays, sample IDs, labels, shard boundaries, and train/validation/test partitions are unchanged. Sample metadata is stored as JSON instead of pickle. No pickle deserialization is needed to read this edition.
| Dataset | Samples | Shards | Classes | Task |
|---|---|---|---|---|
| m-bigearthnet | 22,000 | 22 | 43 | Multilabel classification |
| m-brick-kiln | 17,061 | 18 | 2 | Classification |
| m-eurosat | 4,000 | 4 | 10 | Classification |
| m-forestnet | 8,446 | 9 | 12 | Classification |
| m-pv4ger | 13,812 | 14 | 2 | Classification |
| m-so2sat | 21,964 | 22 | 17 | Classification |
| Total | 87,283 | 89 |
Format
Each dataset directory contains its original partition/statistics JSON files, original README and LICENSE, and shard_*.tar files. Each sample has two archive members:
<sample_id>.bands.npz
<sample_id>.meta.json
The .bands.npz payloads are copied byte-for-byte from the source. Their embedded arrays are numeric and can be loaded with numpy.load(..., allow_pickle=False).
The JSON metadata contains label (a class ID or multilabel vector), bands_order (ordered source-band names), and per-band transform and crs values. Affine transforms are numeric lists, CRS values are strings, and missing georeferencing is null. Each JSON record includes an _conversion notice describing the format change.
The unused task_specs.pkl sidecars are omitted. Python band-description objects, date objects, and auxiliary per-band records are not included in the JSON schema; source-band names, including temporal suffixes, are preserved. Original label maps and label statistics are retained wherever the source supplies them.
Reading with torchgeo-bench
Use a torchgeo-bench version that supports V1 .meta.json shards. Legacy pickle-only readers are not compatible with this metadata format. Download explicitly with the Hugging Face CLI into a fresh directory:
hf download calebrob6/geobenchv1-webdataset --repo-type dataset \
--include "m-eurosat/*" --local-dir data/classification_v1.0_wds
torchgeo-bench run model=rcf "dataset.names=[m-eurosat]"
SHA256SUMS contains one checksum per tar archive. For a complete download, run sha256sum -c SHA256SUMS from the repository root.
Licenses and attribution
The original per-dataset LICENSE and README files are preserved verbatim, including their attribution and source links. The format conversions are distributed under the same applicable dataset licenses; there is no blanket license that replaces those terms.
| Dataset | Upstream license |
|---|---|
| m-bigearthnet | Community Data License Agreement - Permissive 1.0 |
| m-brick-kiln | CC BY-SA 4.0 |
| m-eurosat | CC BY 4.0 for imagery; MIT for labels |
| m-forestnet | CC BY 4.0 |
| m-pv4ger | MIT |
| m-so2sat | CC BY 4.0 |
All tar archives have been modified to replace pickle metadata with JSON. Image-array payloads and benchmark partitions have not been modified. See each dataset's original notices for its creators and applicable licensing details.
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