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 83, 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 66, 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.

YAML Metadata Warning:empty or missing yaml metadata in repo card

Check out the documentation for more information.

MSKit — Mini Simulation Kit

MSKit is a lightweight Python library for running terrain-based simulations backed by real-world elevation data from JAXA's AW3D30 30m Digital Elevation Model.

Tiles are streamed on-demand from the MegaBites-AI/AW3D30-DEM-Tiles dataset hosted on Hugging Face — no manual data download required.

Installation

pip install mskit

With optional visualisation support:

pip install mskit[viz]

Quick Start

from mskit import DEMLoader, RandomWalk, Projectile, WaterFlow, TerrainAgent

# Create a loader — tiles are fetched automatically as needed
loader = DEMLoader()

# ── Random Walk ──────────────────────────────────────────────────────────────
rw = RandomWalk(loader, start_lat=35.68, start_lon=139.69, step_m=300)
path = rw.run(steps=500)
print(f"Distance: {rw.total_distance_km():.2f} km")
print(f"Elevation gain: {rw.elevation_gain_m():.0f} m")

# ── Projectile ───────────────────────────────────────────────────────────────
proj = Projectile(loader, lat=36.0, lon=137.5,
                  azimuth_deg=45, elevation_deg=30, speed_ms=80)
traj = proj.run()
print(f"Range: {proj.range_km():.3f} km | Flight time: {proj.flight_time():.1f} s")

# ── Water Flow ───────────────────────────────────────────────────────────────
wf = WaterFlow(loader, patch_km=10)
flow = wf.run(lat=35.6, lon=137.5)
print(f"Flow length: {len(flow)} steps | Descent: {wf.total_descent_m():.0f} m")

# ── Terrain-Navigating AI Agent ──────────────────────────────────────────────
agent = TerrainAgent(loader,
    start_lat=35.60,  start_lon=139.70,
    target_lat=35.65, target_lon=139.75)
dataset = agent.generate_episode(max_steps=300, policy="mixed")
arr = agent.to_numpy()   # shape (N, 7): [step, lat, lon, elev, action, reward, done]
print(f"Episode: {len(dataset)} steps | Reached target: {agent.reached_target()}")

Simulations

Class	Description
`DEMLoader`	Multi-tile loader with LRU cache. Core data access layer.
`DEMTile`	Single 1°×1° elevation tile with spatial query methods.
`RandomWalk`	Slope-biased 2D random walk on real terrain.
`Projectile`	Ballistic trajectory simulation that terminates on terrain impact.
`WaterFlow`	D8 water runoff routing on real elevation grids.
`TerrainAgent`	RL-ready navigation agent producing training trajectories.

Dataset

Elevation tiles are served from:

MegaBites-AI/AW3D30-DEM-Tiles

Source: JAXA ALOS World 3D 30m (AW3D30 v3.2)
Coverage: Global
Resolution: 30 m/pixel, 1°×1° tiles (3600×3600 px)
Format: Compressed NumPy .npy (int16, metres)
Cache: Tiles are cached locally at ~/.cache/mskit/dem/

Uploading Tiles

To upload tiles to the dataset (MegaBites team only):

# Upload Japan tiles
python scripts/upload_tiles.py --region japan --token $HF_TOKEN

# Upload a custom bounding box
python scripts/upload_tiles.py --lat-range 30 45 --lon-range 130 145 --token $HF_TOKEN

# Dry run first
python scripts/upload_tiles.py --region japan --dry-run

License

MSKit code: MIT License

Produced by MegaBites AI

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