5.24 GB
5 files
Updated 2 days ago
Name
Size
metadata
train
MANIFEST.json153 kB
xet
README.md1.97 kB
xet
SHA256SUMS.txt1.33 kB
xet
README.md

VoLN-UAV Dataset

This Hugging Face dataset entry is intended for the navigation data used by VoLN-UAV. The environment assets are hosted separately so that users can fetch the simulator package and the trajectory data independently.

Hugging Face Entries

Data Organization

The release package provides the benchmark inputs required by VoLN-UAV:

  • scene-level Train/Validation/Test split manifests;
  • route JSON files with RGB frame references and pose-derived state fields;
  • benchmark metadata for scenes, episodes, and checksums;
  • optional copied RGB frames under source/frames/ when the package is built in copy mode.

Usage

  1. Download the dataset package and the env package.
  2. Unzip the dataset package.
  3. Set source_root in the benchmark config to the unzipped source/ directory.
  4. Run python -m voln_uav.cli.build_benchmark --config <config.yaml>.

The generated manifest.json contains the release summary and Hugging Face resource links.

Recommended Citation

Please cite the VoLN-UAV paper and this dataset repository once the manuscript metadata is finalized.

Download Layout

The dataset is uploaded as independent ZIP shards under metadata/, train/, val/, and test/. Each shard is below 5 GB. Extract metadata/VoLN-UAV-metadata.zip first, then extract the split shards you need into the same directory so that paths such as source/frames/<scene>/<trajectory>/<frame>.png match the JSONL metadata.

The train, validation, and test splits are episode-disjoint. The test split is held out on a separate scene, while train and validation may share scenes.

Use SHA256SUMS.txt to verify downloaded shards.

Total size
5.24 GB
Files
5
Last updated
Jul 9
Pre-warmed CDN
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Contributors