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: CastError
Message: Couldn't cast
version: string
device: string
time_domain: string
cameras: struct<fisheye0: struct<model: string, resolution: struct<width: int64, height: int64>, intrinsics: (... 1218 chars omitted)
child 0, fisheye0: struct<model: string, resolution: struct<width: int64, height: int64>, intrinsics: struct<fx: double (... 216 chars omitted)
child 0, model: string
child 1, resolution: struct<width: int64, height: int64>
child 0, width: int64
child 1, height: int64
child 2, intrinsics: struct<fx: double, fy: double, cx: double, cy: double>
child 0, fx: double
child 1, fy: double
child 2, cx: double
child 3, cy: double
child 3, projection_center: struct<uc: double, vc: double>
child 0, uc: double
child 1, vc: double
child 4, distortion: struct<alpha: double, beta: double>
child 0, alpha: double
child 1, beta: double
child 5, extrinsics: struct<T: list<item: double>, R: list<item: list<item: double>>>
child 0, T: list<item: double>
child 0, item: double
child 1, R: list<item: list<item: double>>
child 0, item: list<item: double>
child 0, item: double
child 1, fisheye1: struct<model: string, resolution: struct<width: int64, height: int64>, intrinsics: struct<fx: double (... 216 chars omitted)
child 0, model: string
child 1, resolution: struct<width: int64, height: int64>
...
ht: int64>
child 0, width: int64
child 1, height: int64
child 2, intrinsics: struct<fx: double, fy: double, cx: double, cy: double>
child 0, fx: double
child 1, fy: double
child 2, cx: double
child 3, cy: double
child 3, projection_center: struct<uc: double, vc: double>
child 0, uc: double
child 1, vc: double
child 4, distortion: struct<alpha: double, beta: double>
child 0, alpha: double
child 1, beta: double
child 5, extrinsics: struct<T: list<item: double>, R: list<item: list<item: double>>>
child 0, T: list<item: double>
child 0, item: double
child 1, R: list<item: list<item: double>>
child 0, item: list<item: double>
child 0, item: double
depth_unit: string
baseline_mm: double
invalid_value: int64
note: string
height: int64
width: int64
R_rect_to_camleft: list<item: list<item: double>>
child 0, item: list<item: double>
child 0, item: double
Q: list<item: list<item: double>>
child 0, item: list<item: double>
child 0, item: double
view: string
R_camleft_to_device: list<item: list<item: double>>
child 0, item: list<item: double>
child 0, item: double
intrinsics: struct<fx: double, fy: double, cx: double, cy: double>
child 0, fx: double
child 1, fy: double
child 2, cx: double
child 3, cy: double
T_camleft_to_device: list<item: double>
child 0, item: double
to
{'version': Value('string'), 'note': Value('string'), 'view': Value('string'), 'width': Value('int64'), 'height': Value('int64'), 'depth_unit': Value('string'), 'invalid_value': Value('int64'), 'intrinsics': {'fx': Value('float64'), 'fy': Value('float64'), 'cx': Value('float64'), 'cy': Value('float64')}, 'baseline_mm': Value('float64'), 'R_rect_to_camleft': List(List(Value('float64'))), 'R_camleft_to_device': List(List(Value('float64'))), 'T_camleft_to_device': List(Value('float64')), 'Q': List(List(Value('float64')))}
because column names don't match
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 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 343, in _generate_tables
self._cast_table(pa_table, json_field_paths=json_field_paths),
~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/json/json.py", line 132, in _cast_table
pa_table = table_cast(pa_table, self.info.features.arrow_schema)
File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2378, in table_cast
return cast_table_to_schema(table, schema)
File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2306, in cast_table_to_schema
raise CastError(
...<3 lines>...
)
datasets.table.CastError: Couldn't cast
version: string
device: string
time_domain: string
cameras: struct<fisheye0: struct<model: string, resolution: struct<width: int64, height: int64>, intrinsics: (... 1218 chars omitted)
child 0, fisheye0: struct<model: string, resolution: struct<width: int64, height: int64>, intrinsics: struct<fx: double (... 216 chars omitted)
child 0, model: string
child 1, resolution: struct<width: int64, height: int64>
child 0, width: int64
child 1, height: int64
child 2, intrinsics: struct<fx: double, fy: double, cx: double, cy: double>
child 0, fx: double
child 1, fy: double
child 2, cx: double
child 3, cy: double
child 3, projection_center: struct<uc: double, vc: double>
child 0, uc: double
child 1, vc: double
child 4, distortion: struct<alpha: double, beta: double>
child 0, alpha: double
child 1, beta: double
child 5, extrinsics: struct<T: list<item: double>, R: list<item: list<item: double>>>
child 0, T: list<item: double>
child 0, item: double
child 1, R: list<item: list<item: double>>
child 0, item: list<item: double>
child 0, item: double
child 1, fisheye1: struct<model: string, resolution: struct<width: int64, height: int64>, intrinsics: struct<fx: double (... 216 chars omitted)
child 0, model: string
child 1, resolution: struct<width: int64, height: int64>
...
ht: int64>
child 0, width: int64
child 1, height: int64
child 2, intrinsics: struct<fx: double, fy: double, cx: double, cy: double>
child 0, fx: double
child 1, fy: double
child 2, cx: double
child 3, cy: double
child 3, projection_center: struct<uc: double, vc: double>
child 0, uc: double
child 1, vc: double
child 4, distortion: struct<alpha: double, beta: double>
child 0, alpha: double
child 1, beta: double
child 5, extrinsics: struct<T: list<item: double>, R: list<item: list<item: double>>>
child 0, T: list<item: double>
child 0, item: double
child 1, R: list<item: list<item: double>>
child 0, item: list<item: double>
child 0, item: double
depth_unit: string
baseline_mm: double
invalid_value: int64
note: string
height: int64
width: int64
R_rect_to_camleft: list<item: list<item: double>>
child 0, item: list<item: double>
child 0, item: double
Q: list<item: list<item: double>>
child 0, item: list<item: double>
child 0, item: double
view: string
R_camleft_to_device: list<item: list<item: double>>
child 0, item: list<item: double>
child 0, item: double
intrinsics: struct<fx: double, fy: double, cx: double, cy: double>
child 0, fx: double
child 1, fy: double
child 2, cx: double
child 3, cy: double
T_camleft_to_device: list<item: double>
child 0, item: double
to
{'version': Value('string'), 'note': Value('string'), 'view': Value('string'), 'width': Value('int64'), 'height': Value('int64'), 'depth_unit': Value('string'), 'invalid_value': Value('int64'), 'intrinsics': {'fx': Value('float64'), 'fy': Value('float64'), 'cx': Value('float64'), 'cy': Value('float64')}, 'baseline_mm': Value('float64'), 'R_rect_to_camleft': List(List(Value('float64'))), 'R_camleft_to_device': List(List(Value('float64'))), 'T_camleft_to_device': List(Value('float64')), 'Q': List(List(Value('float64')))}
because column names don't matchNeed help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.
YAML Metadata Warning:empty or missing yaml metadata in repo card
Check out the documentation for more information.
Description
1,042개의 멀티시나리오 Ego-Centric 데이터로 구성된 데이터셋으로, 각 데이터는 약 35초 길이의 완전한 동작 시퀀스를 포함합니다. 주거, 오피스, 인테리어, 리테일, 학교, 창고 등 6개 주요 환경과 34개 장소를 대상으로 데이터를 수집했습니다. 각 샘플에는 6개 카메라 영상, 관련 카메라 파라미터, 재구성 포인트 클라우드, SLAM 후처리 트래젝토리 및 손동작 키포인트 인식 결과 영상이 포함되어 있습니다.
자체 개발한 VSLAM 기술을 기반으로 밀리미터급 위치 측정을 지원하며, 멀티센서 하드웨어 트리거 동기화를 통해 1ms 이하의 정밀한 데이터 동기화를 구현했습니다. RGB 카메라는 최대 60fps의 고프레임레이트를 지원합니다. 본 데이터셋은 임베디드 AI, 공간 인식, 3D 재구성 등 다양한 모델의 학습 및 개발에 활용할 수 있으며, 고정밀 멀티시나리오 데이터와 표준화된 데이터 구성을 통해 높은 활용성을 제공합니다.
자세한 내용은 아래 링크를 참고해 주세요: https://ko.nexdata.ai/datasets/embodied-ai/2236?source=hf.kr
Specifications
Data size
1,042개 데이터, 각 데이터 약 35초
Data Distribution
주거 환경: 293개
오피스 환경: 217개
인테리어 환경: 52개
리테일 환경: 299개
학교 환경: 114개
창고 환경: 49개
Data Content
각 데이터에는 6개 카메라 영상, 관련 파라미터, 재구성 포인트 클라우드, SLAM 후처리 트래젝토리 및 손동작 키포인트 인식 결과 영상이 포함됩니다.
Capture Solution
자체 개발 VSLAM 기술을 적용하여 밀리미터급 위치 측정을 지원하며, 멀티센서 하드웨어 트리거를 통해 1ms 이하의 정밀한 동기화를 구현합니다.
Data Quality
RGB 카메라: 1600×1200, 60fps
흑백 어안 카메라: 640×480, 30fps
카메라는 하드웨어 트리거 방식으로 동기화 및 노출 제어가 이루어집니다.
Application
임베디드 AI, 공간 인식, 3D 재구성 등
Licensing Information
상업용 라이선스
- Downloads last month
- 50