Error code:   ConfigNamesError
Exception:    ValueError
Message:      Feature type 'Mask' not found. Available feature types: ['Value', 'ClassLabel', 'Translation', 'TranslationVariableLanguages', 'LargeList', 'List', 'Array2D', 'Array3D', 'Array4D', 'Array5D', 'Audio', 'Image', 'Video', 'Pdf']
Traceback:    Traceback (most recent call last):
                File "/src/services/worker/src/worker/job_runners/dataset/config_names.py", line 66, in compute_config_names_response
                  config_names = get_dataset_config_names(
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/inspect.py", line 161, in get_dataset_config_names
                  dataset_module = dataset_module_factory(
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/load.py", line 1031, in dataset_module_factory
                  raise e1 from None
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/load.py", line 996, in dataset_module_factory
                  return HubDatasetModuleFactory(
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/load.py", line 605, in get_module
                  dataset_infos = DatasetInfosDict.from_dataset_card_data(dataset_card_data)
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/info.py", line 386, in from_dataset_card_data
                  dataset_info = DatasetInfo._from_yaml_dict(dataset_card_data["dataset_info"])
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/info.py", line 317, in _from_yaml_dict
                  yaml_data["features"] = Features._from_yaml_list(yaml_data["features"])
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/features/features.py", line 2027, in _from_yaml_list
                  return cls.from_dict(from_yaml_inner(yaml_data))
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/features/features.py", line 1872, in from_dict
                  obj = generate_from_dict(dic)
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/features/features.py", line 1459, in generate_from_dict
                  return {key: generate_from_dict(value) for key, value in obj.items()}
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/features/features.py", line 1459, in <dictcomp>
                  return {key: generate_from_dict(value) for key, value in obj.items()}
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/features/features.py", line 1465, in generate_from_dict
                  raise ValueError(f"Feature type '{_type}' not found. Available feature types: {list(_FEATURE_TYPES.keys())}")
              ValueError: Feature type 'Mask' not found. Available feature types: ['Value', 'ClassLabel', 'Translation', 'TranslationVariableLanguages', 'LargeList', 'List', 'Array2D', 'Array3D', 'Array4D', 'Array5D', 'Audio', 'Image', 'Video', 'Pdf']

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.

Sen1Floods11

Sen1Floods11: a georeferenced dataset to train and test deep learning flood algorithms for Sentinel-1 (Example). This data was generated by Cloud to Street, a Public Benefit Corporation: https://www.cloudtostreet.info/. For questions about this dataset or code please email [email protected]. Please cite this data as:

Bonafilia, D., Tellman, B., Anderson, T., Issenberg, E. 2020. Sen1Floods11: a georeferenced dataset to train and test deep learning flood algorithms for Sentinel-1. The IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Workshops, 2020, pp. 210-211.

Available Open access at: http://openaccess.thecvf.com/content_CVPRW_2020/html/w11/Bonafilia_Sen1Floods11_A_Georeferenced_Dataset_to_Train_and_Test_Deep_Learning_CVPRW_2020_paper.html

Dataset Access

The dataset is available for access through HF at: senfloods11

Bucket Structure

The sen1floods11 bucket is split into subfolders containing data, checkpoints, training/testing splits, and a STAC compliant catalog. More detail on each is provided in the docs README.

Dataset Information

Each file follows the naming scheme EVENT_CHIPID_LAYER.tif (e.g. Bolivia_103757_S2Hand.tif). Chip IDs are unique, and not shared between events. Events are named by country and further information on each event (including dates) can be found in the event metadata below. Each layer has a separate GeoTIFF, and can contain multiple bands in a stacked GeoTIFF. All images are projected to WGS 84 (EPSG:4326) at 10 m ground resolution.

Layer	Description	Values	Format	Bands
QC	Hand labeled chips containing ground truth	-1: No Data / Not Valid 0: Not Water 1: Water	GeoTIFF 512 x 512 1 band Int16	0: QC
S1	Raw Sentinel-1 imagery. IW mode, GRD product See here for information on preprocessing	Unit: dB	GeoTIFF 512 x 512 2 bands Float32	0: VV 1: VH
S2	Raw Sentinel-2 MSI Level-1C imagery Contains all spectral bands (1 - 12) Does not contain QA mask	Unit: TOA reflectance (scaled by 10000)	GeoTIFF 512 x 512 13 bands UInt16	0: B1 (Coastal) 1: B2 (Blue) 2: B3 (Green) 3: B4 (Red) 4: B5 (RedEdge-1) 5: B6 (RedEdge-2) 6: B7 (RedEdge-3) 7: B8 (NIR) 8: B8A (Narrow NIR) 9: B9 (Water Vapor) 10: B10 (Cirrus) 11: B11 (SWIR-1) 12: B12 (SWIR-2)

Example images

A sample of the dataset for chip Spain_7370579 is provided at in ./sample

Example Use

Train.ipynb shows how to train and validate the model on a dataset.

Event Metadata

Locations of the flood events and metadata is contained in Sen1Floods11_Metadata.geojson. The following fields can be found:

Field	Description
ID	Unique ID for each event
location	Flood event location (country)
ISO_CC	ISO Country Code for flood event location
s1_date	Date (YYYY-MM-dd) that Sentinel-1 image was acquired
s2_date	Date (YYYY-MM-dd) that Sentinel-2 image was acquired
orbit	Orbit (ASCENDING or DESCENDING) that Sentinel-1 image was acquired
rel_orbit_num	Relative Orbit Number that Sentinel-1 image was acquired
coincident_size	Number of coincident tiles from S2
VH_thresh	Threshold used for Sentinel-1 VH band to classify water in reference S1 classification
train_chip	Number of chips used for training
val_chip	Number of chips used for validation

Downloads last month: 1,259