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The dataset generation failed
Error code:   DatasetGenerationError
Exception:    IndexError
Message:      list index out of range
Traceback:    Traceback (most recent call last):
                File "/usr/local/lib/python3.14/site-packages/datasets/builder.py", line 1859, in _prepare_split_single
                  original_shard_lengths[original_shard_id] += len(table)
                  ~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^
              IndexError: list index out of range
              
              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/parquet_and_info.py", line 1369, in compute_config_parquet_and_info_response
                  parquet_operations, partial, estimated_dataset_info = stream_convert_to_parquet(
                                                                        ~~~~~~~~~~~~~~~~~~~~~~~~~^
                      builder, max_dataset_size_bytes=max_dataset_size_bytes
                      ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                  )
                  ^
                File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 948, in stream_convert_to_parquet
                  builder._prepare_split(split_generator=splits_generators[split], file_format="parquet")
                  ~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/builder.py", line 1694, in _prepare_split
                  for job_id, done, content in self._prepare_split_single(
                                               ~~~~~~~~~~~~~~~~~~~~~~~~~~^
                      gen_kwargs=gen_kwargs, job_id=job_id, **_prepare_split_args
                      ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                  ):
                  ^
                File "/usr/local/lib/python3.14/site-packages/datasets/builder.py", line 1880, in _prepare_split_single
                  raise DatasetGenerationError("An error occurred while generating the dataset") from e
              datasets.exceptions.DatasetGenerationError: An error occurred while generating the dataset

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End of preview.

WorldRover-6scenes

600 camera paths through six photoreal 3D environments, each rendered twice — once as a 360° panorama, once as a first-person pinhole view — with per-frame metric depth, camera pose and action labels. 1200 clips, 18.9 h of video per view (37.9 h total) at 30 fps, 2.05 M frames per view, ~7.6 TB.

Scene Clips per view Median clip Range Video per view
med_village 100 2 min 17 s 30 s – 6 min 40 s 4.54 h
venice 100 1 min 42 s 21 s – 8 min 32 s 4.19 h
apartment 100 1 min 39 s 29 s – 3 min 00 s 2.91 h
paris 100 1 min 39 s 37 s – 3 min 00 s 2.86 h
office 100 1 min 15 s 16 s – 3 min 01 s 2.25 h
art_nouveau 100 1 min 01 s 11 s – 4 min 07 s 2.19 h

Layout

<scene>/pano/<clip_id>/     equirectangular 4096x2048
<scene>/fp/<clip_id>/       pinhole 1280x720, hfov 65.5 deg (28 mm on a 36 mm sensor)
    rgb.mp4                 H.264, 30 fps
    depth/depth.mkv         FFV1 gray16le, lossless, log-quantized radial depth
    depth/depth.meta.json   near/far, frame count, decode formula
    camera_trajectory.csv   per-frame world pose + intrinsics
    description.json        scene, asset pack, licence, trajectory summary, render settings
    gamepad_format/         action labels (axis events + timeline)
    trajectory.png          top-down path plot (fp only)

Paired, frame for frame

pano/<clip_id> and fp/<clip_id> are the same camera path: the first-person clip is rendered from the panoramic clip's per-frame trajectory, so the two camera_trajectory.csv files agree row for row (only hfov_deg/focal_length_mm differ — 360°/0 mm for the equirect camera, 65.47°/28 mm for the pinhole). You get the same world state under two very different projections without an interpolated alignment.

Clips are 11 s to 8.5 min of continuous motion — no cuts, no teleports.

Conventions that are easy to get wrong

  • Depth is log-quantized and radial. depth_m = exp(gray/65535 * (log 200 − log 0.1) + log 0.1), and the value is distance along the ray, not along the optical axis — convert before unprojecting.
  • Frame counts. camera_trajectory.csv has one row more than the video has frames (the last row is the closing keyframe). The authoritative count is depth/depth.meta.json.
  • Poses are Unreal-style: left-handed, centimetres, X-forward / Y-right / Z-up, camera looking down its own +X.
  • Panoramic frames are equirectangular. A rectangular crop is not a perspective view — reproject before comparing against the first-person clip.

Render provenance

description.json records the exact render path per clip, and it is not identical across scenes. Five scenes (med_village, venice, office, apartment, art_nouveau) were rendered in two rounds — MPPC_RGBOnly then MPPC_DepthPlus — and stitched with a Lanczos kernel, so render.mppc is an object with rgb/depth keys. paris was re-rendered later through a corrected single-pass path (MPPC_VelocityDepthPlus with the extra pass dropped, linear-HDR output, fixed exposure, linear stitch kernel), so its render.mppc is a plain string and its render.cube additionally carries fixed_ev and tm_comp.

The reason for the paris re-render: a Lanczos resampling kernel has negative lobes, which on high-contrast sky/architecture boundaries interpolate linear HDR below zero; clamping to zero left a one-pixel pure-black rim along building silhouettes. Switching to a linear kernel took sky edges with undershoot from 15.5% to 3.4% — below the 6.1% baseline of the cube faces themselves. Per-frame auto-exposure was replaced with a fixed value at the same time, so brightness no longer drifts with what happens to be in view.

Tools

git clone https://github.com/AlayaLab/WorldRover
pip install -r WorldRover/tools/requirements.txt   # numpy, opencv-python; ffmpeg/ffprobe on PATH
cd WorldRover/tools                                # the package is not pip-installable yet
from worldrover import Clip

clip    = Clip("/data/WorldRover-6scenes/venice/fp/venice_000000")
rgb     = clip.rgb_frame(100)     # uint8 (H, W, 3), sRGB
depth_m = clip.depth_frame(100)   # planar depth in metres
pts     = clip.points_world(100)  # world points, centimetres
poses   = clip.poses              # per-frame pose + intrinsics

Clip takes a filesystem path to a clip directory. The reader takes the depth pixel format from that clip's own depth/depth.meta.json, so it handles both encodings used across these repositories, and it converts radial depth and the off-by-one trajectory row for you.

Related

License

Rendered video, depth, camera pose and action labels are released for research use. The underlying 3D environments are third-party commercial assets, are not redistributed here, and each clip's description.json records its asset pack and licence. Tools are MIT.

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