Dataset Viewer
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: TypeError
Message: Couldn't cast array of type
struct<place_CellPhone|surface|10|94_from_Bed|10|0_to_DiningTable|5|1|0_1771159778452_step0: struct<status: string, frames: list<item: struct<snapshot_label: string, file_paths: struct<rgb: string, depth: string, semantic: string, instance: string, meta: string>, topology_clusters: list<item: struct<receptacle: string, relation: string, room: string, members: list<item: string>, bounding_boxes: list<item: list<item: int64>>, distances_to_camera: list<item: double>, positions_3d: list<item: list<item: double>>, qa_pairs: struct<Q1_sort: list<item: string>, Q2_rel: struct<Book|surface|5|56: list<item: struct<object: string, direction: string, distance_3d: double>>, Bowl|surface|5|49: list<item: struct<object: string, direction: string, distance_3d: double>>, DeskLamp|surface|5|46: list<item: struct<object: string, direction: string, distance_3d: double>>, Laptop|surface|5|44: list<item: struct<object: string, direction: string, distance_3d: double>>, Pen|surface|5|47: list<item: struct<object: string, direction: string, distance_3d: double>>, Pencil|surface|5|54: list<item: struct<object: string, direction: string, distance_3d: double>>, Plate|surface|5|45: list<item: struct<object: string, direction: string, distance_3d: double>>, RemoteControl|surface|5|43: list<item: struct<object: string, direction: string, distance_3d: double>>, Watch|surface|5|52: list<item: struct<object: string, direction: string, distance_3d: double>>, Book|surface|5|53: list<item: null>, Pillow|surfac
...
aths: struct<rgb: string, depth: string, semantic: string, instance: string, meta: string>, topology_clusters: list<item: struct<receptacle: string, relation: string, room: string, members: list<item: string>, bounding_boxes: list<item: list<item: int64>>, distances_to_camera: list<item: double>, positions_3d: list<item: list<item: double>>, qa_pairs: struct<Q1_sort: list<item: string>, Q2_rel: struct<Book|surface|5|56: list<item: struct<object: string, direction: string, distance_3d: double>>, Bowl|surface|5|49: list<item: struct<object: string, direction: string, distance_3d: double>>, CellPhone|surface|10|94: list<item: struct<object: string, direction: string, distance_3d: double>>, DeskLamp|surface|5|46: list<item: struct<object: string, direction: string, distance_3d: double>>, Laptop|surface|5|44: list<item: struct<object: string, direction: string, distance_3d: double>>, Pen|surface|5|47: list<item: struct<object: string, direction: string, distance_3d: double>>, Pencil|surface|5|54: list<item: struct<object: string, direction: string, distance_3d: double>>, Plate|surface|5|45: list<item: struct<object: string, direction: string, distance_3d: double>>, RemoteControl|surface|5|43: list<item: struct<object: string, direction: string, distance_3d: double>>, Watch|surface|5|52: list<item: struct<object: string, direction: string, distance_3d: double>>, Book|surface|5|53: list<item: null>, Pillow|surface|5|55: list<item: null>>, Q3_type_count: int64, Q4_count: int64>>>>>>>
to
{'remove_Apple|surface|2|0_from_CounterTop|2|0_1771159574857_step0': {'status': Value('string'), 'frames': List({'snapshot_label': Value('string'), 'file_paths': {'rgb': Value('string'), 'depth': Value('string'), 'semantic': Value('string'), 'instance': Value('string'), 'meta': Value('string')}, 'topology_clusters': List({'receptacle': Value('string'), 'relation': Value('string'), 'room': Value('string'), 'members': List(Value('string')), 'bounding_boxes': List(List(Value('int64'))), 'distances_to_camera': List(Value('float64')), 'positions_3d': List(List(Value('float64'))), 'qa_pairs': {'Q1_sort': List(Value('string')), 'Q2_rel': {'Apple|surface|2|0': List({'object': Value('string'), 'direction': Value('string'), 'distance_3d': Value('float64')}), 'Bowl|surface|2|11': List({'object': Value('string'), 'direction': Value('string'), 'distance_3d': Value('float64')}), 'Egg|surface|2|1': List({'object': Value('string'), 'direction': Value('string'), 'distance_3d': Value('float64')}), 'Fork|surface|2|17': List({'object': Value('string'), 'direction': Value('string'), 'distance_3d': Value('float64')}), 'Kettle|surface|2|5': List({'object': Value('string'), 'direction': Value('string'), 'distance_3d': Value('float64')}), 'Kettle|surface|2|6': List({'object': Value('string'), 'direction': Value('string'), 'distance_3d': Value('float64')}), 'Ladle|surface|2|16': List({'object': Value('string'), 'direction': Value('string'), 'distance_3d': Value('float64')}), 'Lettuce|surface|2|3': Lis
...
{'object': Value('string'), 'direction': Value('string'), 'distance_3d': Value('float64')}), 'Kettle|surface|2|6': List({'object': Value('string'), 'direction': Value('string'), 'distance_3d': Value('float64')}), 'Ladle|surface|2|16': List({'object': Value('string'), 'direction': Value('string'), 'distance_3d': Value('float64')}), 'Lettuce|surface|2|3': List({'object': Value('string'), 'direction': Value('string'), 'distance_3d': Value('float64')}), 'Pencil|surface|2|13': List({'object': Value('string'), 'direction': Value('string'), 'distance_3d': Value('float64')}), 'Plate|surface|2|15': List({'object': Value('string'), 'direction': Value('string'), 'distance_3d': Value('float64')}), 'Potato|surface|2|9': List({'object': Value('string'), 'direction': Value('string'), 'distance_3d': Value('float64')}), 'SaltShaker|surface|2|4': List({'object': Value('string'), 'direction': Value('string'), 'distance_3d': Value('float64')}), 'SoapBottle|surface|2|14': List({'object': Value('string'), 'direction': Value('string'), 'distance_3d': Value('float64')}), 'SprayBottle|surface|2|2': List({'object': Value('string'), 'direction': Value('string'), 'distance_3d': Value('float64')}), 'Tomato|surface|2|7': List({'object': Value('string'), 'direction': Value('string'), 'distance_3d': Value('float64')}), 'WineBottle|surface|2|8': List({'object': Value('string'), 'direction': Value('string'), 'distance_3d': Value('float64')})}, 'Q3_type_count': Value('int64'), 'Q4_count': Value('int64')}})})}}
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 299, 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 2255, in cast_table_to_schema
cast_array_to_feature(
File "/usr/local/lib/python3.12/site-packages/datasets/table.py", line 1804, in wrapper
return pa.chunked_array([func(chunk, *args, **kwargs) for chunk in array.chunks])
^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/table.py", line 2011, in cast_array_to_feature
_c(array.field(name) if name in array_fields else null_array, subfeature)
File "/usr/local/lib/python3.12/site-packages/datasets/table.py", line 1806, in wrapper
return func(array, *args, **kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/table.py", line 2011, in cast_array_to_feature
_c(array.field(name) if name in array_fields else null_array, subfeature)
File "/usr/local/lib/python3.12/site-packages/datasets/table.py", line 1806, in wrapper
return func(array, *args, **kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/table.py", line 2101, in cast_array_to_feature
raise TypeError(f"Couldn't cast array of type\n{_short_str(array.type)}\nto\n{_short_str(feature)}")
TypeError: Couldn't cast array of type
struct<place_CellPhone|surface|10|94_from_Bed|10|0_to_DiningTable|5|1|0_1771159778452_step0: struct<status: string, frames: list<item: struct<snapshot_label: string, file_paths: struct<rgb: string, depth: string, semantic: string, instance: string, meta: string>, topology_clusters: list<item: struct<receptacle: string, relation: string, room: string, members: list<item: string>, bounding_boxes: list<item: list<item: int64>>, distances_to_camera: list<item: double>, positions_3d: list<item: list<item: double>>, qa_pairs: struct<Q1_sort: list<item: string>, Q2_rel: struct<Book|surface|5|56: list<item: struct<object: string, direction: string, distance_3d: double>>, Bowl|surface|5|49: list<item: struct<object: string, direction: string, distance_3d: double>>, DeskLamp|surface|5|46: list<item: struct<object: string, direction: string, distance_3d: double>>, Laptop|surface|5|44: list<item: struct<object: string, direction: string, distance_3d: double>>, Pen|surface|5|47: list<item: struct<object: string, direction: string, distance_3d: double>>, Pencil|surface|5|54: list<item: struct<object: string, direction: string, distance_3d: double>>, Plate|surface|5|45: list<item: struct<object: string, direction: string, distance_3d: double>>, RemoteControl|surface|5|43: list<item: struct<object: string, direction: string, distance_3d: double>>, Watch|surface|5|52: list<item: struct<object: string, direction: string, distance_3d: double>>, Book|surface|5|53: list<item: null>, Pillow|surfac
...
aths: struct<rgb: string, depth: string, semantic: string, instance: string, meta: string>, topology_clusters: list<item: struct<receptacle: string, relation: string, room: string, members: list<item: string>, bounding_boxes: list<item: list<item: int64>>, distances_to_camera: list<item: double>, positions_3d: list<item: list<item: double>>, qa_pairs: struct<Q1_sort: list<item: string>, Q2_rel: struct<Book|surface|5|56: list<item: struct<object: string, direction: string, distance_3d: double>>, Bowl|surface|5|49: list<item: struct<object: string, direction: string, distance_3d: double>>, CellPhone|surface|10|94: list<item: struct<object: string, direction: string, distance_3d: double>>, DeskLamp|surface|5|46: list<item: struct<object: string, direction: string, distance_3d: double>>, Laptop|surface|5|44: list<item: struct<object: string, direction: string, distance_3d: double>>, Pen|surface|5|47: list<item: struct<object: string, direction: string, distance_3d: double>>, Pencil|surface|5|54: list<item: struct<object: string, direction: string, distance_3d: double>>, Plate|surface|5|45: list<item: struct<object: string, direction: string, distance_3d: double>>, RemoteControl|surface|5|43: list<item: struct<object: string, direction: string, distance_3d: double>>, Watch|surface|5|52: list<item: struct<object: string, direction: string, distance_3d: double>>, Book|surface|5|53: list<item: null>, Pillow|surface|5|55: list<item: null>>, Q3_type_count: int64, Q4_count: int64>>>>>>>
to
{'remove_Apple|surface|2|0_from_CounterTop|2|0_1771159574857_step0': {'status': Value('string'), 'frames': List({'snapshot_label': Value('string'), 'file_paths': {'rgb': Value('string'), 'depth': Value('string'), 'semantic': Value('string'), 'instance': Value('string'), 'meta': Value('string')}, 'topology_clusters': List({'receptacle': Value('string'), 'relation': Value('string'), 'room': Value('string'), 'members': List(Value('string')), 'bounding_boxes': List(List(Value('int64'))), 'distances_to_camera': List(Value('float64')), 'positions_3d': List(List(Value('float64'))), 'qa_pairs': {'Q1_sort': List(Value('string')), 'Q2_rel': {'Apple|surface|2|0': List({'object': Value('string'), 'direction': Value('string'), 'distance_3d': Value('float64')}), 'Bowl|surface|2|11': List({'object': Value('string'), 'direction': Value('string'), 'distance_3d': Value('float64')}), 'Egg|surface|2|1': List({'object': Value('string'), 'direction': Value('string'), 'distance_3d': Value('float64')}), 'Fork|surface|2|17': List({'object': Value('string'), 'direction': Value('string'), 'distance_3d': Value('float64')}), 'Kettle|surface|2|5': List({'object': Value('string'), 'direction': Value('string'), 'distance_3d': Value('float64')}), 'Kettle|surface|2|6': List({'object': Value('string'), 'direction': Value('string'), 'distance_3d': Value('float64')}), 'Ladle|surface|2|16': List({'object': Value('string'), 'direction': Value('string'), 'distance_3d': Value('float64')}), 'Lettuce|surface|2|3': Lis
...
{'object': Value('string'), 'direction': Value('string'), 'distance_3d': Value('float64')}), 'Kettle|surface|2|6': List({'object': Value('string'), 'direction': Value('string'), 'distance_3d': Value('float64')}), 'Ladle|surface|2|16': List({'object': Value('string'), 'direction': Value('string'), 'distance_3d': Value('float64')}), 'Lettuce|surface|2|3': List({'object': Value('string'), 'direction': Value('string'), 'distance_3d': Value('float64')}), 'Pencil|surface|2|13': List({'object': Value('string'), 'direction': Value('string'), 'distance_3d': Value('float64')}), 'Plate|surface|2|15': List({'object': Value('string'), 'direction': Value('string'), 'distance_3d': Value('float64')}), 'Potato|surface|2|9': List({'object': Value('string'), 'direction': Value('string'), 'distance_3d': Value('float64')}), 'SaltShaker|surface|2|4': List({'object': Value('string'), 'direction': Value('string'), 'distance_3d': Value('float64')}), 'SoapBottle|surface|2|14': List({'object': Value('string'), 'direction': Value('string'), 'distance_3d': Value('float64')}), 'SprayBottle|surface|2|2': List({'object': Value('string'), 'direction': Value('string'), 'distance_3d': Value('float64')}), 'Tomato|surface|2|7': List({'object': Value('string'), 'direction': Value('string'), 'distance_3d': Value('float64')}), 'WineBottle|surface|2|8': List({'object': Value('string'), 'direction': Value('string'), 'distance_3d': Value('float64')})}, 'Q3_type_count': Value('int64'), 'Q4_count': Value('int64')}})})}}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.
SpaMEM
Embodied spatial reasoning dataset for evaluating dynamic spatial memory in vision-language models. Episodes are collected in ProcTHOR with a resident-agent simulator.
Layout
manifest.csv # one row per episode
house_train_<id>/
episode_resident_sim_<ts>.tar.gz # episode data
episode_resident_sim_<ts>.spamem_full_data.json # episode metadata
Each tarball, when extracted, gives:
episode_resident_sim_<ts>/
action0/ action1/ ... action14/
<action_name>_<step>/
meta/ pre_ang{0,45,...,315}_{low,high}.json
semantic/ pre_ang{0,45,...,315}_{low,high}.png
...
Run logs and benchmark metric folders are excluded from the public release.
Quickstart
from huggingface_hub import hf_hub_download
import tarfile
# Grab one episode
path = hf_hub_download(
repo_id="mill-ct-liao/SpaMEM",
filename="house_train_4/episode_resident_sim_1771160706058.tar.gz",
repo_type="dataset",
)
with tarfile.open(path) as tf:
tf.extractall("./extracted")
To list all episodes available:
import pandas as pd
from huggingface_hub import hf_hub_download
mf = hf_hub_download(
repo_id="mill-ct-liao/SpaMEM",
filename="manifest.csv",
repo_type="dataset",
)
print(pd.read_csv(mf).head())
Statistics
- Episodes: 105
- Total compressed size: 19.5 GB
- Total files (across all episodes): 263,352
Citation
TBD — paper under review at ECCV 2026.
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