Datasets:

MCP4RemoteSensing
/

mcp4rs-media-gallery-outputs

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/folder_based_builder/folder_based_builder.py", line 192, in _split_generators
                  raise ValueError(f"Found metadata files with different extensions: {list(metadata_ext)}")
              ValueError: Found metadata files with different extensions: ['.jsonl', '.csv']
              
              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 71, 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.

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MCP4RS Reproducible Media Gallery Outputs

This dataset contains generated sample outputs from the MCP4RS media-gallery workflow. It is intended to make the expensive or slow generated figures reusable for demos, documentation, teaching, and downstream analysis.

The original open-data source evidence is recorded in generated/provenance/*.json. figures/ contains processed intermediate frames, and media/ contains final gallery PNG/GIF outputs. assets/preview/ contains curated README and Hugging Face Space preview assets.

Creators

Name	Credit
Dongping Liu	creator and MCP4RS co-owner
Luyao Zhang	creator and MCP4RS co-owner

NeurIPS 2026 Dataset Hosting Notes

This package is prepared to align with the NeurIPS 2026 Evaluations & Datasets hosting guide:

The dataset is hosted on Hugging Face Datasets.
metadata.jsonl provides a structured artifact index.
croissant_metadata.json provides draft Croissant core metadata plus minimal Responsible AI fields.
Before OpenReview submission, download or verify the Hugging Face-generated Croissant file and validate the completed Croissant metadata with the NeurIPS-recommended validator.
If this dataset is part of a NeurIPS submission, include the dataset URL and the validated Croissant metadata file in OpenReview.

Croissant reference: Akhtar, M. et al. (2024). Croissant: A Metadata Format for ML-Ready Datasets. NeurIPS 2024 Datasets and Benchmarks Track. https://proceedings.neurips.cc/paper_files/paper/2024/hash/9547b09b722f2948ff3ddb5d86002bc0-Abstract-Datasets_and_Benchmarks_Track.html

Responsible AI Summary

Limitations: generated visualization outputs for demo/reproducibility; not an operational monitoring or calibrated benchmark dataset.
Biases: selected demonstration scenes may over-represent visually interesting regions, sensors, dates, and conditions.
Personal/sensitive information: not intended to contain personal data; use high-resolution upstream imagery responsibly where applicable.
Use cases: demo reproduction, teaching, provenance inspection, and open-data workflow documentation.
Social impact: lowers recomputation cost and improves transparency, but users should not over-interpret rendered previews as authoritative measurements.
Synthetic data: false; outputs are rendered/processed from open remote-sensing and environmental source data, not synthetically generated scenes.

Open Data And Tool Acknowledgements

Open data sources include:

ESA/Copernicus Sentinel-1 and Sentinel-2 data accessed through open STAC-style catalogs where available.
USGS/NASA Landsat open data accessed through open catalog assets where available.
USDA NAIP imagery accessed through open catalog assets where available.
Copernicus DEM terrain data accessed through open catalog assets where available.
NASA GIBS/VIIRS nightlights WMS imagery.
NASA MODIS land-surface temperature products used by the physical-layers example.
NOAA GOES and NOAA OISST open datasets used by the physical-layers example.
NASA POWER open meteorological and solar-resource data used by the physical-layers example.

Open-source tools include:

Python
Gradio
Hugging Face Hub
pystac-client
Microsoft Planetary Computer Python tooling
Rasterio
NumPy
Matplotlib
Pillow
Requests

Folder	Meaning	File count
`media/`	Generated workflow artifacts	7
`figures/`	Generated workflow artifacts	85
`generated/provenance/`	Generated workflow artifacts	7
`assets/preview/`	Generated workflow artifacts	13

Reproducibility

Source repository commit: 3d0a4f6
Dataset upload time: 2026-07-25T20:35:05.126630+00:00
Dataset repo: MCP4RemoteSensing/mcp4rs-media-gallery-outputs

To regenerate locally:

python scripts/export_media_sources.py
python scripts/generate_media_gallery.py --continue-on-error
python scripts/update_preview_assets.py --require-full

Then upload a refreshed dataset:

python scripts/upload_hf_dataset.py --repo-id MCP4RemoteSensing/mcp4rs-media-gallery-outputs

The upload script creates:

README.md
metadata.jsonl
dataset_manifest.json
croissant_metadata.json

Notes

This is a generated-output dataset, not a replacement for the underlying satellite data providers. Please cite or acknowledge the original data providers listed in the provenance JSON files where appropriate.

Downloads last month: 14

Total file size:

138 MB