The dataset viewer is not available for this split.
Error code: StreamingRowsError
Exception: UnidentifiedImageError
Message: cannot identify image file <_io.BytesIO object at 0x7fd7705b4b80>
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 2567, in __iter__
for key, example in ex_iterable:
^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 2103, in __iter__
batch = formatter.format_batch(pa_table)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/formatting/formatting.py", line 472, in format_batch
batch = self.python_features_decoder.decode_batch(batch)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/formatting/formatting.py", line 234, in decode_batch
return self.features.decode_batch(batch, token_per_repo_id=self.token_per_repo_id) if self.features else batch
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/features/features.py", line 2254, in decode_batch
decode_nested_example(self[column_name], value, token_per_repo_id=token_per_repo_id)
File "/usr/local/lib/python3.12/site-packages/datasets/features/features.py", line 1508, in decode_nested_example
return schema.decode_example(obj, token_per_repo_id=token_per_repo_id) if obj is not None else None
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/features/image.py", line 190, in decode_example
image = PIL.Image.open(bytes_)
^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/PIL/Image.py", line 3498, in open
raise UnidentifiedImageError(msg)
PIL.UnidentifiedImageError: cannot identify image file <_io.BytesIO object at 0x7fd7705b4b80>Need help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.
Varying Altitude Dataset (*Under Review at NeurIPS 2025 data track)
Varying Altitude Dataset is a multi-scale, multi-view image dataset collected using Google Earth Studio. It captures the same geographic locations from three distinct altitude tiers to support research in 3D reconstruction, camera localization, and novel view synthesis. The tiers include:
Satellite View: Overhead ortho-images offering a broad, map-like geodetic context. Aerial View: Captured using a scripted triple-helix camera path that mimics a spiraling drone descent. At each spatial waypoint, three simultaneous images are taken with different camera angles (left, center, right), providing diverse viewpoints and varied baselines. Ground View: Simulated human-level perspectives obtained by virtually walking around the location on accessible paths. Together, these tiers enable cross-altitude and cross-view analysis, making the dataset well-suited for evaluating visual understanding tasks in geographically diverse urban and natural environments.
Each location in our dataset follows a consistent folder structure to support reproducibility and structured parsing. Within each location-specific folder (e.g., IDxxxx, IDxxxx_left, IDxxxx_right, IDxxxx_satellite, or IDxxxx_street), there are three key components:
footage/ — A subfolder containing the full sequence of images captured from Google Earth Studio for that specific viewpoint and trajectory.
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