The dataset viewer is not available for this subset.
Exception: SplitsNotFoundError
Message: The split names could not be parsed from the dataset config.
Traceback: Traceback (most recent call last):
File "/src/services/worker/src/worker/job_runners/config/split_names.py", line 138, in compute
return CompleteJobResult(compute_split_names_from_info_response(dataset=self.dataset, config=self.config))
File "/src/services/worker/src/worker/job_runners/config/split_names.py", line 117, in compute_split_names_from_info_response
config_info_response = get_previous_step_or_raise(kind="config-info", dataset=dataset, config=config)
File "/src/libs/libcommon/src/libcommon/simple_cache.py", line 566, in get_previous_step_or_raise
raise CachedArtifactError(
libcommon.simple_cache.CachedArtifactError: The previous step failed.
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/inspect.py", line 499, in get_dataset_config_info
for split_generator in builder._split_generators(
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/packaged_modules/folder_based_builder/folder_based_builder.py", line 186, in _split_generators
raise ValueError("`file_name` must be present as dictionary key in metadata files")
ValueError: `file_name` must be present as dictionary key in metadata files
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 68, in compute_split_names_from_streaming_response
for split in get_dataset_split_names(
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/inspect.py", line 572, in get_dataset_split_names
info = get_dataset_config_info(
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/inspect.py", line 504, 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? Open a discussion for direct support.
CloudSEN12+ is a significant extension of the CloudSEN12 dataset, which doubles the number of expert-reviewed labels, making it, by a large margin, the largest cloud detection dataset to date for Sentinel-2. All labels from the previous version have been curated and refined, enhancing the dataset's trustworthiness. This new release is licensed under CC0, which puts it in the public domain and allows anyone to use, modify, and distribute it without permission or attribution.
Data Structure
We use GeoTIFF format to store the data
| Name | Scale | Wavelength | Description |
|---|---|---|---|
| B1 | 0.0001 | 443.9 nm (S2A)/442.3 nm (S2B) | Aerosols. |
| B2 | 0.0001 | 496.6 nm (S2A)/492.1 nm (S2B) | Blue. |
| B3 | 0.0001 | 560 nm (S2A)/559 nm (S2B) | Green. |
| B4 | 0.0001 | 664.5 nm (S2A)/665 nm (S2B) | Red. |
| B5 | 0.0001 | 703.9 nm (S2A)/703.8 nm (S2B) | Red Edge 1. |
| B6 | 0.0001 | 740.2 nm (S2A)/739.1 nm (S2B) | Red Edge 2. |
| B7 | 0.0001 | 782.5 nm (S2A)/779.7 nm (S2B) | Red Edge 3. |
| B8 | 0.0001 | 835.1 nm (S2A)/833 nm (S2B) | NIR. |
| B8A | 0.0001 | 864.8 nm (S2A)/864 nm (S2B) | Red Edge 4. |
| B9 | 0.0001 | 945 nm (S2A)/943.2 nm (S2B) | Water vapor. |
| B10 | 0.0001 | 1373.5 nm (S2A)/1376.9 nm (S2B) | Cirrus. |
| B11 | 0.0001 | 1613.7 nm (S2A)/1610.4 nm (S2B) | SWIR 1. |
| B12 | 0.0001 | 2202.4 nm (S2A)/2185.7 nm (S2B) | SWIR 2. |
| CM1 | 1 | - | Expert-labeled image. |
| CM2 | 1 | - | UnetMobV2-labeled image. |
Folder Structure
The CloudSEN12+ dataset is structured hierarchically, with the top level (A) dividing the dataset into two main categories: p509 and p2000 images, represented by gray folders. Moving to the next level (B), the images are further organized based on the label type, with each label type having a different folder. Within each label type, an additional level (C) groups the images based on a block of random data splitting, represented by blue folders. Moreover, within the p509 category, there is an additional division based on geographic location, highlighted by yellow folders (D). Each folder contains a set of five distinct images.
The fixed/ folder contains high and scribble labels, which have been improved in this new version. These changes have already been integrated into the p509 and p2000 folders.
The demo/ folder contains examples illustrating how to utilize the models trained with CLoudSEN12 to estimate the hardness and trustworthiness indices.
Download
There are two identical copies of the dataset available for users: one on HuggingFace and the other on ScienceDataBank.
HuggingFace
from huggingface_hub import hf_hub_download
for i in range(1, 19):
hf_hub_download(
repo_id="isp-uv-es/CloudSEN12Plus",
repo_type="dataset",
filename="synthetic/synthetic_%02d.zip" % i
)
ScienceDataBank
from huggingface_hub import hf_hub_download
for i in range(1, 19):
hf_hub_download(
repo_id="isp-uv-es/CloudSEN12Plus",
repo_type="dataset",
filename="synthetic/synthetic_%02d.zip" % i
)
Citation
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