The dataset viewer is not available for this split.
Error code: FeaturesError
Exception: ArrowInvalid
Message: Schema at index 1 was different:
default: struct<name: string, version: string, data_dir: string, data_files: struct<train: string>, features: struct<session_id: struct<dtype: string, _type: string>, created_at: struct<dtype: string, _type: string>, duration: struct<dtype: string, _type: string>, frames: struct<dtype: string, _type: string>, cameras: struct<feature: struct<dtype: string, _type: string>, length: int64, _type: string>, robot_data: struct<dtype: string, _type: string>, status: struct<dtype: string, _type: string>, description: struct<dtype: string, _type: string>>>
vs
session_id: string
created_at: timestamp[s]
duration: double
frames: int64
cameras: list<item: string>
robot_data: bool
status: string
description: string
Traceback: Traceback (most recent call last):
File "/src/services/worker/src/worker/job_runners/split/first_rows.py", line 228, in compute_first_rows_from_streaming_response
iterable_dataset = iterable_dataset._resolve_features()
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/iterable_dataset.py", line 3422, in _resolve_features
features = _infer_features_from_batch(self.with_format(None)._head())
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/iterable_dataset.py", line 2187, in _head
return next(iter(self.iter(batch_size=n)))
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/iterable_dataset.py", line 2391, in iter
for key, example in iterator:
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/iterable_dataset.py", line 1882, in __iter__
for key, pa_table in self._iter_arrow():
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/iterable_dataset.py", line 1904, in _iter_arrow
yield from self.ex_iterable._iter_arrow()
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/iterable_dataset.py", line 559, in _iter_arrow
yield new_key, pa.Table.from_batches(chunks_buffer)
File "pyarrow/table.pxi", line 4116, in pyarrow.lib.Table.from_batches
File "pyarrow/error.pxi", line 154, in pyarrow.lib.pyarrow_internal_check_status
File "pyarrow/error.pxi", line 91, in pyarrow.lib.check_status
pyarrow.lib.ArrowInvalid: Schema at index 1 was different:
default: struct<name: string, version: string, data_dir: string, data_files: struct<train: string>, features: struct<session_id: struct<dtype: string, _type: string>, created_at: struct<dtype: string, _type: string>, duration: struct<dtype: string, _type: string>, frames: struct<dtype: string, _type: string>, cameras: struct<feature: struct<dtype: string, _type: string>, length: int64, _type: string>, robot_data: struct<dtype: string, _type: string>, status: struct<dtype: string, _type: string>, description: struct<dtype: string, _type: string>>>
vs
session_id: string
created_at: timestamp[s]
duration: double
frames: int64
cameras: list<item: string>
robot_data: bool
status: string
description: stringNeed 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:The task_ids "robot-teleoperation" is not in the official list: acceptability-classification, entity-linking-classification, fact-checking, intent-classification, language-identification, multi-class-classification, multi-label-classification, multi-input-text-classification, natural-language-inference, semantic-similarity-classification, sentiment-classification, topic-classification, semantic-similarity-scoring, sentiment-scoring, sentiment-analysis, hate-speech-detection, text-scoring, named-entity-recognition, part-of-speech, parsing, lemmatization, word-sense-disambiguation, coreference-resolution, extractive-qa, open-domain-qa, closed-domain-qa, news-articles-summarization, news-articles-headline-generation, dialogue-modeling, dialogue-generation, conversational, language-modeling, text-simplification, explanation-generation, abstractive-qa, open-domain-abstractive-qa, closed-domain-qa, open-book-qa, closed-book-qa, text2text-generation, slot-filling, masked-language-modeling, keyword-spotting, speaker-identification, audio-intent-classification, audio-emotion-recognition, audio-language-identification, multi-label-image-classification, multi-class-image-classification, face-detection, vehicle-detection, instance-segmentation, semantic-segmentation, panoptic-segmentation, image-captioning, image-inpainting, image-colorization, super-resolution, grasping, task-planning, tabular-multi-class-classification, tabular-multi-label-classification, tabular-single-column-regression, rdf-to-text, multiple-choice-qa, multiple-choice-coreference-resolution, document-retrieval, utterance-retrieval, entity-linking-retrieval, fact-checking-retrieval, univariate-time-series-forecasting, multivariate-time-series-forecasting, visual-question-answering, document-question-answering, pose-estimation
SO-101 Roboter Dataset
Dieses Dataset enthält Teleoperationsdaten für den SO-101 Roboter, aufgenommen mit Phosphobot.
Beschreibung
- Roboter: SO-101
- Kamera: Logitech HD Webcam eMeet C980 Pro (4 Kameras)
- Software: Phosphobot
- Aufnahme: Teleoperation mit visueller Rückmeldung
Struktur
so-arm101/
├── meta/
│ └── info.json # Dataset-Metadaten
├── sessions/ # Aufnahme-Sessions
│ └── [session_id]/ # Einzelne Sessions
│ ├── videos/ # Kamera-Videos
│ ├── robot_data/ # Roboter-Telemetrie
│ └── metadata.json # Session-Metadaten
└── README.md # Diese Datei
Verwendung
Dieses Dataset kann mit Phosphobot verwendet werden für:
- Roboter-Training
- Teleoperation
- Datensatz-Analyse
Lizenz
MIT License
Citation
@dataset{so_arm101_2025,
title={SO-101 Roboter Dataset},
author={MaxFridge},
year={2025},
url={https://huggingface.co/datasets/MaxFridge/so-arm101}
}
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