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Datasets:
Ehzoahis
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SegMunich

Tasks:
Image Segmentation
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The dataset viewer is not available for this dataset.
Cannot get the config names for the dataset.
Error code:   ConfigNamesError
Exception:    RuntimeError
Message:      Dataset scripts are no longer supported, but found SegMunich.py
Traceback:    Traceback (most recent call last):
                File "/src/services/worker/src/worker/job_runners/dataset/config_names.py", line 67, in compute_config_names_response
                  config_names = get_dataset_config_names(
                      path=dataset,
                      token=hf_token,
                  )
                File "/usr/local/lib/python3.14/site-packages/datasets/inspect.py", line 161, in get_dataset_config_names
                  dataset_module = dataset_module_factory(
                      path,
                  ...<4 lines>...
                      **download_kwargs,
                  )
                File "/usr/local/lib/python3.14/site-packages/datasets/load.py", line 1215, in dataset_module_factory
                  raise e1 from None
                File "/usr/local/lib/python3.14/site-packages/datasets/load.py", line 1175, in dataset_module_factory
                  raise RuntimeError(f"Dataset scripts are no longer supported, but found {filename}")
              RuntimeError: Dataset scripts are no longer supported, but found SegMunich.py

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SegMunich

SegMunich is a segmentation task dataset that is Sentinel-2 satellite based. It contains spectral imagery of Munich's urban landscape over a span of three years.

Please refer to the original paper for more detailed information about the original SegMunich dataset:

How to Use This Dataset 

from datasets import load_dataset

dataset = load_dataset("GFM-Bench/SegMunich")

Also, please see our GFM-Bench repository for more information about how to use the dataset! 🤗

Dataset Metadata

The following metadata provides details about the Sentinel-2 imagery used in the dataset:

  • Number of Sentinel-2 Bands: 10
  • Sentinel-2 Bands: B01 (Coastal aerosol), B02 (Blue), B03 (Green), B04 (Red), B05 (Vegetation red edge), B06 (Vegetation red edge), B07 (Vegetation red edge), B8A (Narrow NIR), B11 (SWIR), B12 (SWIR)
  • Image Resolution: 128 x 128 pixels
  • Spatial Resolution: 10 meters
  • Number of Classes: 13

Dataset Splits

The SegMunich dataset consists following splits:

  • train: 3,000 samples
  • val: 403 samples
  • test: 403 samples

Dataset Features:

The SegMunich dataset consists of following features:

  • optical: the Sentinel-2 image.
  • label: the segmentation labels.
  • optical_channel_wv: the central wavelength of each Sentinel-2 bands.
  • spatial_resolution: the spatial resolution of images.

Citation

If you use the SegMunich dataset in your work, please cite the original paper:

@article{hong2024spectralgpt,
  title={SpectralGPT: Spectral remote sensing foundation model},
  author={Hong, Danfeng and Zhang, Bing and Li, Xuyang and Li, Yuxuan and Li, Chenyu and Yao, Jing and Yokoya, Naoto and Li, Hao and Ghamisi, Pedram and Jia, Xiuping and others},
  journal={IEEE Transactions on Pattern Analysis and Machine Intelligence},
  year={2024},
  publisher={IEEE}
}

and if you also find our benchmark useful, please consider citing our paper:

@misc{si2025scalablefoundationmodelmultimodal,
      title={Towards Scalable Foundation Model for Multi-modal and Hyperspectral Geospatial Data}, 
      author={Haozhe Si and Yuxuan Wan and Minh Do and Deepak Vasisht and Han Zhao and Hendrik F. Hamann},
      year={2025},
      eprint={2503.12843},
      archivePrefix={arXiv},
      primaryClass={cs.CV},
      url={https://arxiv.org/abs/2503.12843}, 
}
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