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 80, in _split_generators
raise ValueError(
...<2 lines>...
)
ValueError: The TAR archives of the dataset should be in WebDataset format, but the files in the archive don't share the same prefix or the same types.
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.
Aryan006/cone-distance-v1
Cones, barriers, barrels and stop signs from nuScenes, Argoverse 2, COCO and
BDD100K, merged into one schema with camera intrinsics and ground-truth distance
attached. Built for monocular geometric distance estimation: distance comes from
focal length and pixel geometry at inference time, and the LiDAR-derived
gt_distance_m here is scoring ground truth only.
Contents
| File | What it is |
|---|---|
manifest.parquet |
one row per object; the source of truth |
calib/<sensor_id>.yaml |
K, cam_height_m, R_ego_from_cam per camera |
class_priors.yaml |
per-class physical size, derived from the 3D cuboids |
data.yaml |
Ultralytics dataset config (path is relative; rewrite on download) |
shards/*.tar |
images and YOLO labels, {split}/images/ and {split}/labels/ |
from huggingface_hub import snapshot_download
snapshot_download("Aryan006/cone-distance-v1", repo_type="dataset", local_dir="data/hub")
# then extract every shards/*.tar into data/hub/ and point Ultralytics at data.yaml
Instances per source and class
class barrel barrier cone stop_sign
source
av2 11295 0 3050 1362
coco 0 0 0 1786
nuscenes 0 3224 3112 0
Ground-truth distance
gt_distance_m is forward depth along the camera optical axis — the Z
component of the object centre in the camera frame — not Euclidean range.
Null for COCO and BDD100K, which have no depth ground truth.
count min 50% max
class
barrel 11295.0 6.112889 63.412934 153.664738
barrier 3224.0 4.190958 22.377529 87.990130
cone 6162.0 3.514974 32.560524 141.995047
stop_sign 1362.0 7.656534 42.930884 104.231571
Frames per split
split
train 8446
val 1815
Split by scene, not by frame: adjacent video frames are near-duplicates, so a frame-level split leaks the val set into training and inflates val mAP a long way. Scenes are split independently within each source so every source reaches val.
Notes
barrel(AV2 orange drum) andbarrier(nuScenes jersey/fence barrier) are deliberately separate classes. They are visually unrelated.- Boxes shorter than 15 px, nuScenes visibility below 0.4, and boxes more than 50% truncated at the frame edge are filtered out.
- BDD100K contributes negative frames only, excluding any frame containing a traffic sign — its generic sign class hides real stop signs.
- Source datasets keep their own licences (nuScenes and Argoverse 2 are non-commercial research licences; COCO is CC BY 4.0). This repo redistributes derived crops and labels under those terms.
- Downloads last month
- 68