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 question set (frozen 2026-10-12), 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 frames the tokens were made from (added 2026-10-21).
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_2026-10-18.tar |
the question set: 2026-10-18/<type>/{accurate,rough}.jsonl for 25 question types, plus LIST.{csv,md} (also loose as LIST_2026-10-18.{csv,md}: per type, its counts, whether Gemini was involved, its sources) and reference_images.json |
epic-kitchens/questions/labels_2026-10-18.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_2026-10-18.json + _split.json |
the 68,465 trainable questions (64,439 train / 4,026 val, on 27 validation videos) |
epic-kitchens/questions/train_2026-10-18_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/frames/<video>.tar |
599 tars (179.1 GB, 1,708,038 JPEGs, <video>/<frame:06d>.jpg; bytes, md5 and sha256 in epic-kitchens/frames/frames_MANIFEST_2026-10-18.tsv): the undistorted 992 px frames (pinhole; 992x557, 992x743 for the two 4:3 videos P12_05 / P12_06) the tokens were made from. They hold every frame of the token cache (its depth, intrinsics and camera pose are in the token file) and every exact 1 fps frame the questions ask for; epic-kitchens/frames/frames_index_2026-10-18.tsv.gz says which is which (exact_1fps, rule_frame). 542 wanted frames do not exist (one past a video's last frame, or a corrupt last frame). Not fetched by download_epic_v3.sh: only native-Qwen training or vision-encoder fine-tuning needs them. They replace the 2026-10-06 tars (572 videos, a subset), which remain in this repo's history. |
epic-kitchens/v3_MANIFEST.tsv |
bytes, md5 and sha256 of every v3 file above except the tokens and frames |
Renamed on 2026-10-19 so every v3 file carries one date. The question files were named after the day the questions
were frozen: questions_2026-10-12.tar, LIST_2026-10-12.{csv,md}, labels_2026-10-12.jsonl and train_1012[_reftrain][_split].json.
Only the names changed. Every loose file is byte-identical, and the tar holds the same 65 files under the folder 2026-10-18/
instead of 2026-10-12/. The old files remain in this repo's history.
HD-EPIC reference geometry (added 2026-10-20)
| path | what |
|---|---|
hd-epic/reference_frames/hdepic_refgeo-4b_2026-10-18.tar |
2,847 files (22 MB), one per reference image of the HD-EPIC VQA questions (2,650 questions). Each holds the camera pose (Aria SLAM world), the depth of each token and each token's MEAN 3D point (12 x 12 tokens of a 384 px, 95-degree rectified frame). md5 65381813477968f5deef7aebb04e88e1 |
- Who needs it: only someone TESTING on HD-EPIC a model trained with
ref_pos=train. Unpack it into<code>/results/cache/hdepic/(it createsrefgeo-4b/). - One recording is empty: the 51 references of P03-20240217-131219 hold NaN, because its released SLAM poses stop at 22.8 of 54.6 minutes. None of its questions is in a scored set.
- Where it comes from: HD-EPIC (Perrett et al., CVPR 2025). Cite it and follow its terms.
- The rest of the HD-EPIC test data is not public: no HD-EPIC images, videos or tokens are in this share.
Earlier versions (kept, not used by v3)
| path | what |
|---|---|
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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