The dataset viewer is not available for this split.
Error code: StreamingRowsError
Exception: ValueError
Message: Invalid string class label cs498@fe75efa77db39ac61c438f7a9fe85eda66d023f6
Traceback: 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 2386, in __iter__
example = _apply_feature_types_on_example(
example, self.features, token_per_repo_id=self.token_per_repo_id
)
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2303, in _apply_feature_types_on_example
encoded_example = features.encode_example(example)
File "/usr/local/lib/python3.14/site-packages/datasets/features/features.py", line 2178, in encode_example
return encode_nested_example(self, example)
File "/usr/local/lib/python3.14/site-packages/datasets/features/features.py", line 1460, in encode_nested_example
{k: encode_nested_example(schema[k], obj.get(k), level=level + 1) for k in schema}
~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/features/features.py", line 1483, in encode_nested_example
return schema.encode_example(obj) if obj is not None else None
~~~~~~~~~~~~~~~~~~~~~^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/features/features.py", line 1158, in encode_example
example_data = self.str2int(example_data)
File "/usr/local/lib/python3.14/site-packages/datasets/features/features.py", line 1095, in str2int
output = [self._strval2int(value) for value in values]
~~~~~~~~~~~~~~~~^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/features/features.py", line 1116, in _strval2int
raise ValueError(f"Invalid string class label {value}")
ValueError: Invalid string class label cs498@fe75efa77db39ac61c438f7a9fe85eda66d023f6Need help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.
CS 498 homework data
hw3_data.zip is the frozen, required HW3 Car-detection package (SHA-256
d70aa8544b52d56ca0569110434562ff74296ee80f63c8cd8b1c47364fc79523).
It contains train.npz, val.npz, and test.npz over 5,977/730/774
drive-disjoint KITTI frames. The processed targets use grid-aligned-v2.
hw3_multiclass_data.zip is a small optional bonus-only companion
(SHA-256 58811f16591d5ae9de97da8fa3bf871bfb65d101f8b6b5ac87666a5aa56e489c).
Its three aligned label archives add Pedestrian and Cyclist boxes/class IDs;
its Car boxes exactly match the core package. Use the handout's
data/download_multiclass_data.py after data/download_data.py. The companion
does not replace core BEVs, split membership, or the required result protocol.
Both packages derive from the
KITTI 3D object-detection training set.
Use is educational in CS 498; cite KITTI. Validation controls all model and
threshold decisions, and the final test split must remain held out until
those choices are frozen. File checksums are in SHA256SUMS.
HW4: compact NeRF Lego data
hw4_data.zip contains the 200 x 200 Blender-format Lego subset used by the
CS 498 HW4 handout: 50 training, 5 validation, and 12 held-out test poses.
Its SHA-256 is 502c9216170111bd9a6b7f7204442b23b69020924a11229ec0a820f825b3fbad. The handout downloader verifies every
member against hw4_SHA256SUMS before installation. The images are derived
from the NeRF synthetic Lego example data and retain the original camera
transforms; use is limited to the course and other permitted educational use.
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