Dataset Viewer
The dataset viewer is not available for this subset.
Cannot get the split names for the config 'default' of the dataset.
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 88, in _split_generators
inferred_arrow_schema = pa.concat_tables(pa_tables, promote_options="default").schema
~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "pyarrow/table.pxi", line 6268, in pyarrow.lib.concat_tables
File "pyarrow/error.pxi", line 155, in pyarrow.lib.pyarrow_internal_check_status
File "pyarrow/error.pxi", line 92, in pyarrow.lib.check_status
raise convert_status(status)
pyarrow.lib.ArrowTypeError: Unable to merge: Field json has incompatible types: list<item: struct<scene_id: string, dataset_type: string, question_type: string, question_id: string, question_for_test: string, answer_for_test: string, question_frame: int64, answer_for_test_frame: int64, clock_origin_frame: int64, native_fps: double, n_window_frames: int64, prompt_mode: string, refs: list<item: struct<video_id: string, ref_time: double, ref_announce_time: double, ref_box: list<item: double>>>, n_refs: int64, n_refs_image_fed: int64, est_seq_tokens: int64>> vs struct<subset: string, recipe: string, source: string, mcq_instr: string, rezero_clock: bool, prompt_mode: string, refs_image_fed: bool, fps: double, min_frames: int64, max_frames: int64, max_seq_estimate: int64, frame_rule: string, frame_tol: double, n_train: int64, n_val: int64, dropped: struct<not_in_split: int64, too_few_usable_frames: int64, over_max_seq_estimate: int64>>
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 68, 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.
VoxMem EPIC-KITCHENS share
This share holds derived data of the VoxMem project, built from EPIC-KITCHENS-100. The videos are (c) the EPIC-KITCHENS team under CC BY-NC 4.0, and this share keeps that license: it is for non-commercial research. The original MP4s are not here.
Current version: 2026-10-18 (v3). It holds:
- the 10-12 question set, both tiers (accurate and rough), including the questions built with Gemini;
- one label row per question;
- the trainable lists;
- the token cache, 599 videos (the 572 of the previous version + 27 new ones, poses from EPIC-Fields only);
- the hand masks, the reference-frame tokens and their exact-frame 3D, and the fps table.
The voxels are not shared. The training machine builds them from the token cache with one script.
To train, use the code, not this page:
- the guide is
docs/TRAIN_ELSEWHERE_EPIC_V3.mdin the VoxMem repo, branchhdepic-gen-epic-questions; bash scripts/kit/download_epic_v3.shdownloads, checks and unpacks everything below into place.
Every path here is the path under the VoxMem data root (src/voxmem/paths.py), except the two reftok-4b /
refgeo-4b tars, which unpack into <code>/results/cache/hdepic/.
v3 (2026-10-18)
| path | what |
|---|---|
epic-kitchens/tokens/qwen3vl-4b_512px/<video>.npz |
599 files (3.43 TB), one per video. Each holds the Qwen3-VL-4B visual tokens (144 per 512x288 frame), similarity features, 3D points, camera pose, depth and the frame-rule table. Every frame is chosen by the frame rule: each wanted 1 fps frame exactly, else the nearest frame with a camera pose within +-0.5 s, else that second is dropped. sha256 in epic-kitchens/tokens/tokens_MANIFEST.tsv and SHA256SUMS_tokens.txt. |
epic-kitchens/questions/questions_2026-10-12.tar |
the question set: 2026-10-12/<type>/{accurate,rough}.jsonl for 25 question types, plus LIST.{csv,md} (also loose as LIST_2026-10-12.{csv,md}: per type, its counts, whether Gemini was involved, its sources) and reference_images.json |
epic-kitchens/questions/labels_2026-10-12.jsonl |
one row per question. The main columns: tier, gemini, split, coverage, n_frames, scene_id, voxel_tokens, est_tokens, trainable, reason (the first rule failed) and trainable_ref_train. |
epic-kitchens/questions/train_1012.json + _split.json |
the 68,465 trainable questions (64,439 train / 4,026 val, on 27 validation videos) |
epic-kitchens/questions/train_1012_reftrain.json + _split.json |
the 67,070 of them whose every reference image has 3D (for --ref_pos train) |
epic-kitchens/hand_masks/hand_masks_2026-10-18.tar |
box + palm hand masks, 599 videos each (unpacks to epic-kitchens/hand_masks/{box,palm}/). They supersede the loose 572-video hand_masks/{box,palm}/ files, whose rows are identical. |
epic-kitchens/meta/fps_table_2026-10-18.tar |
Videos/<P>/{frames,durations}.txt for the 599 videos: the voxel builder's fps table |
epic-kitchens/reference_frames/reftok-4b_2026-10-18.tar |
24,727 reference-image token files (144 x 2560, or 192 x 2560 for the two 4:3 videos) |
epic-kitchens/reference_frames/refgeo-4b_2026-10-18.tar |
23,015 exact-frame 3D files, one per reference image: per-token xyz and depth, camera pose, source. They come from the frame's EPIC-Fields pose, or a pose interpolated within 0.5 s, plus DA3 depth; otherwise from the nearest posed cached frame within 0.5 s. |
epic-kitchens/reference_frames/ref512_jpg_2026-10-18.tar |
the 512 px reference images the tokens were made from (needed only to re-bake them) |
epic-kitchens/v3_MANIFEST.tsv |
bytes, md5 and sha256 of every v3 file above except the tokens |
Earlier versions (kept, not used by v3)
| path | what |
|---|---|
epic-kitchens/frames/<video>.tar |
rectified 992 px frames of the 2026-10-06 version, <video>/<frame:06d>.jpg, 572 videos |
epic-kitchens/questions/questions.tar |
the 2026-10-06 question set (all.json, covered.json, split_videos.json) |
epic-kitchens/train/train.tar |
the v1 training lists (text_only/epic_v1_*, reference_frames/epic_v1_refzs_*) |
epic-kitchens/reference_frames/reference_frames.tar |
the v1 reference images |
epic-kitchens/raw/*.tar |
EPIC-Fields poses, Intermediate-Data (per-frame poses), VISOR and the EPIC annotations |
<category>/outdated-2026-09-24/ |
the 2026-09-24 version (old layout: its members start with task_runtime/) |
MD5SUMS.txt lists every tar and loose v3 file, and SHA256SUMS_tokens.txt lists every token file.
bash download.sh <DATA> checks both and unpacks the tars that belong under the data root.
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