Datasets:
The dataset viewer is not available for this subset.
Exception: SplitsNotFoundError
Message: The split names could not be parsed from the dataset config.
Traceback: Traceback (most recent call last):
File "/usr/local/lib/python3.14/site-packages/datasets/inspect.py", line 286, in get_dataset_config_info
for split_generator in builder._split_generators(
~~~~~~~~~~~~~~~~~~~~~~~~~^
StreamingDownloadManager(base_path=builder.base_path, download_config=download_config)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
)
^
File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/webdataset/webdataset.py", line 81, in _split_generators
first_examples = list(islice(pipeline, self.NUM_EXAMPLES_FOR_FEATURES_INFERENCE))
File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/webdataset/webdataset.py", line 32, in _get_pipeline_from_tar
fs: fsspec.AbstractFileSystem = fsspec.filesystem("memory")
~~~~~~~~~~~~~~~~~^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/fsspec/registry.py", line 302, in filesystem
cls = get_filesystem_class(protocol)
File "/usr/local/lib/python3.14/site-packages/fsspec/registry.py", line 239, in get_filesystem_class
raise ValueError(f"Protocol not known: {protocol}")
ValueError: Protocol not known: memory
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/split_names.py", line 71, in compute_split_names_from_streaming_response
for split in get_dataset_split_names(
~~~~~~~~~~~~~~~~~~~~~~~^
path=dataset,
^^^^^^^^^^^^^
config_name=config,
^^^^^^^^^^^^^^^^^^^
token=hf_token,
^^^^^^^^^^^^^^^
)
^
File "/usr/local/lib/python3.14/site-packages/datasets/inspect.py", line 340, in get_dataset_split_names
info = get_dataset_config_info(
path,
...<6 lines>...
**config_kwargs,
)
File "/usr/local/lib/python3.14/site-packages/datasets/inspect.py", line 291, in get_dataset_config_info
raise SplitsNotFoundError("The split names could not be parsed from the dataset config.") from err
datasets.inspect.SplitsNotFoundError: The split names could not be parsed from the dataset config.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.
RekaDaily-10k (raw)
Raw, unscripted, first-person daily-life video, collected through Claru, Reka's data collection marketplace — recorded by paid collectors in their own homes and workplaces on head-mounted and handheld phones, across multiple regions.
Videos are exactly as collected — no re-encoding, no cuts, no filtering beyond
basic integrity checks. A processed tier (short clips with machine captions) is
released separately under the same RekaDaily-10k prefix.
This dataset is being released incrementally toward the full release.
Structure
Videos are packed into WebDataset tar archives (~8 GB), organized by collection project:
data/<project>/shard-NNNNN.tar # pairs of <video_id>.<mp4|mov> + <video_id>.json
metadata/browse.parquet # one row per video: thumbnail + every metadata field
metadata/index.parquet # the same metadata fields, without thumbnails
The metadata/ parquets are refreshed at the end of each upload batch, so they
can trail the newest shards briefly while a batch is in flight.
Load the video shards with any WebDataset reader, e.g.:
import webdataset as wds
url = "https://huggingface.co/datasets/RekaAI/RekaDaily-10k-raw/resolve/main/data/egocentric_household_tasks/shard-00000.tar"
ds = wds.WebDataset(url)
The tar shards are not previewed in the Hub's Dataset Viewer (its WebDataset preview is currently broken platform-wide for video archives); they download and stream normally.
Projects: egocentric_household_tasks, egocentric_commercial_environments,
video_capture_activities, video_capture,
video_capture_first_person_videos_phone.
Metadata fields
Each .json sidecar carries the fields below; metadata/index.parquet and
metadata/browse.parquet carry the same set, one row per video (browse adds
the thumbnail image column):
| field | description |
|---|---|
video_id |
unique id, matches the media file name |
project |
Claru collection project |
flow, activities |
activity taxonomy (activities-type projects): session scenario + performed actions |
category, subcategory |
category taxonomy (video-capture-type projects) |
lighting |
lighting condition, where captured |
duration_s, fps, width, height, num_frames, codec |
probe stats |
collector |
salted-hash collector id — distinct values ≈ distinct environments |
Each video populates one taxonomy family (flow/activities or category/subcategory) depending on its project type.
Consent, privacy & takedown
This dataset was collected through Claru, Reka's data collection marketplace, as described in the release announcement. Collectors are paid contractors who opt in, and every session is recorded with the wearer's knowledge and agreement. Collectors are instructed to record only with the agreement of other adults present and to keep others out of frame where that is not possible.
Every video in this release has been processed to remove container metadata — GPS coordinates, device identifiers, and capture timestamps — and verified clean before upload, in addition to the automated PII screening described in the announcement. Screening is not perfect. If you find something in this release that should not be there, tell us and we will remove it: contact contact@reka.ai.
License
Apache 2.0 — use, redistribute, and build on this data, including commercially, with attribution per the license terms.
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