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100K-Hours-Multiple-Scenes-Ego-Centric-Dataset-Sample

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The dataset generation failed

Error code:   DatasetGenerationError
Exception:    CastError
Message:      Couldn't cast
reference_resolution: struct<w: int64, h: int64>
  child 0, w: int64
  child 1, h: int64
left: struct<intrinsics: struct<fx: double, fy: double, cx: double, cy: double>, distortion: struct<model: (... 37 chars omitted)
  child 0, 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 1, distortion: struct<model: string, coeffs: list<item: double>>
      child 0, model: string
      child 1, coeffs: list<item: double>
          child 0, item: double
right: struct<intrinsics: struct<fx: double, fy: double, cx: double, cy: double>, distortion: struct<model: (... 37 chars omitted)
  child 0, 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 1, distortion: struct<model: string, coeffs: list<item: double>>
      child 0, model: string
      child 1, coeffs: list<item: double>
          child 0, item: double
to
{'id': Value('int64'), 'start_timestamp': Value('string'), 'end_timestamp': Value('string'), 'atomic_action': Value('string'), 'action_description': Value('string'), 'action_description_en': Value('string'), 'interacting_hand': Value('string'), 'target_object_class': Value('string'), 'is_noise': Value('bool'), 'cleaning_reason': Value('null')}
because column names don't match
Traceback:    Traceback (most recent call last):
                File "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 1821, in _prepare_split_single
                  num_examples, num_bytes = writer.finalize()
                                            ^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/arrow_writer.py", line 781, in finalize
                  self.write_rows_on_file()
                File "/usr/local/lib/python3.12/site-packages/datasets/arrow_writer.py", line 663, in write_rows_on_file
                  self._write_table(table)
                File "/usr/local/lib/python3.12/site-packages/datasets/arrow_writer.py", line 773, in _write_table
                  pa_table = table_cast(pa_table, self._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 2249, in cast_table_to_schema
                  raise CastError(
              datasets.table.CastError: Couldn't cast
              reference_resolution: struct<w: int64, h: int64>
                child 0, w: int64
                child 1, h: int64
              left: struct<intrinsics: struct<fx: double, fy: double, cx: double, cy: double>, distortion: struct<model: (... 37 chars omitted)
                child 0, 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 1, distortion: struct<model: string, coeffs: list<item: double>>
                    child 0, model: string
                    child 1, coeffs: list<item: double>
                        child 0, item: double
              right: struct<intrinsics: struct<fx: double, fy: double, cx: double, cy: double>, distortion: struct<model: (... 37 chars omitted)
                child 0, 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 1, distortion: struct<model: string, coeffs: list<item: double>>
                    child 0, model: string
                    child 1, coeffs: list<item: double>
                        child 0, item: double
              to
              {'id': Value('int64'), 'start_timestamp': Value('string'), 'end_timestamp': Value('string'), 'atomic_action': Value('string'), 'action_description': Value('string'), 'action_description_en': Value('string'), 'interacting_hand': Value('string'), 'target_object_class': Value('string'), 'is_noise': Value('bool'), 'cleaning_reason': Value('null')}
              because column names don't match
              
              The above exception was the direct cause of the following exception:
              
              Traceback (most recent call last):
                File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 1347, in compute_config_parquet_and_info_response
                  parquet_operations = convert_to_parquet(builder)
                                       ^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 980, in convert_to_parquet
                  builder.download_and_prepare(
                File "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 882, in download_and_prepare
                  self._download_and_prepare(
                File "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 943, in _download_and_prepare
                  self._prepare_split(split_generator, **prepare_split_kwargs)
                File "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 1646, in _prepare_split
                  for job_id, done, content in self._prepare_split_single(
                                               ^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 1832, in _prepare_split_single
                  raise DatasetGenerationError("An error occurred while generating the dataset") from e
              datasets.exceptions.DatasetGenerationError: An error occurred while generating the dataset

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id int64	start_timestamp string	end_timestamp string	atomic_action string	action_description string	action_description_en string	interacting_hand string	target_object_class string	is_noise bool	cleaning_reason null
1	00:00:00	00:00:05	Extract	右手从洗衣机中取出一双拖鞋	Right hand extracts a pair of slippers from the washing machine	right_hand	slippers	false	null
2	00:00:05	00:00:08	Walk_Forward	手持拖鞋走向窗户	Walking towards the window while holding slippers	none	null	false	null
3	00:00:08	00:00:11	Place	将拖鞋放置在窗台上	Placing slippers on the window sill	right_hand	slippers	false	null
4	00:00:11	00:00:13	Walk_Forward	转身走回洗衣机旁	Turning around and walking back to the washing machine	none	null	false	null
5	00:00:13	00:00:17	Extract	右手从洗衣机中取出一条毛巾	Right hand extracts a towel from the washing machine	right_hand	towel	false	null
6	00:00:17	00:00:27	Unfold	双手展开并抖动毛巾	Unfolding and shaking the towel with both hands	both	towel	false	null
7	00:00:27	00:00:30	Walk_Forward	手持毛巾走向晾衣架	Walking towards the drying rack while holding the towel	none	null	false	null
8	00:00:30	00:00:35	Drape	将毛巾挂在衣架上	Draping the towel onto a hanger	both	towel	false	null
9	00:00:35	00:00:37	Hook	将衣架挂在晾衣杆上	Hooking the hanger onto the drying rod	both	hanger	false	null
10	00:00:37	00:00:50	Align	调整毛巾在衣架上的位置使其平整	Adjusting the towel on the hanger to make it straight	both	towel	false	null
11	00:00:50	00:00:58	Walk_Forward	转身走回洗衣机旁	Turning around and walking back to the washing machine	none	null	false	null
12	00:00:58	00:01:00	Reach	右手伸向洗衣机内部	Right hand reaching into the washing machine	right_hand	washing_machine	false	null
null	null	null	null	null	null	null	null	null	null

YAML Metadata Warning:empty or missing yaml metadata in repo card

Check out the documentation for more information.

100K-Hours-Multiple-Scenes-Ego-Centric-Data

Description

This dataset is just a sample of 100K Hours Multiple Scenes Ego-Centric Data, human manipulation data captured from a first-person view across real-world scenarios. Each record includes: ①time-aligned binocular video, ②binocular camera parameters, ③3D scene reconstruction point cloud file, ④human body joint data, ⑤stepwise semantic annotation file. This data can be used for training VLA model of embodied AI.

For more details, please refer to the link: https://www.nexdata.ai/datasets/llm/2093?source=Huggingface

Specifications

Data content

100,000 hours of human manipulation data captured from a first-person view across real-world scenarios. Each record includes: ①time-aligned binocular video, ②binocular camera parameters, ③3D scene reconstruction point cloud file, ④human body joint data, ⑤stepwise semantic annotation file

Collection devices

PICO 4 Ultra headset worn on the head, and IMU wristbands worn on both wrists

Data distribution

real-world scenarios(like kitchen, room, hotel, etc.) that including multiple daily manipulation tasks(like food preparation & cooking, cleaning, object organizing & storage, bed making, clothing folding, etc.)

Full Dataset Access

The complete dataset is available upon request. Visit Nexdata to learn more and submit an access request.

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