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Error code: DatasetGenerationError
Exception: TypeError
Message: Mask must be a pyarrow.Array of type boolean
Traceback: Traceback (most recent call last):
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 1586, in _prepare_split_single
writer.write(example, key)
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/arrow_writer.py", line 553, in write
self.write_examples_on_file()
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/arrow_writer.py", line 511, in write_examples_on_file
self.write_batch(batch_examples=batch_examples)
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/arrow_writer.py", line 631, in write_batch
self.write_table(pa_table, writer_batch_size)
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/arrow_writer.py", line 646, in write_table
pa_table = embed_table_storage(pa_table)
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/table.py", line 2248, in embed_table_storage
arrays = [
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/table.py", line 2249, in <listcomp>
embed_array_storage(table[name], feature, token_per_repo_id=token_per_repo_id)
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/table.py", line 1795, in wrapper
return pa.chunked_array([func(chunk, *args, **kwargs) for chunk in array.chunks])
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/table.py", line 1795, in <listcomp>
return pa.chunked_array([func(chunk, *args, **kwargs) for chunk in array.chunks])
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/table.py", line 2124, in embed_array_storage
return feature.embed_storage(array, token_per_repo_id=token_per_repo_id)
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/features/image.py", line 292, in embed_storage
storage = pa.StructArray.from_arrays([bytes_array, path_array], ["bytes", "path"], mask=bytes_array.is_null())
File "pyarrow/array.pxi", line 3257, in pyarrow.lib.StructArray.from_arrays
File "pyarrow/array.pxi", line 3697, in pyarrow.lib.c_mask_inverted_from_obj
TypeError: Mask must be a pyarrow.Array of type boolean
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/builder.py", line 1595, in _prepare_split_single
num_examples, num_bytes = writer.finalize()
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/arrow_writer.py", line 658, in finalize
self.write_examples_on_file()
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/arrow_writer.py", line 511, in write_examples_on_file
self.write_batch(batch_examples=batch_examples)
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/arrow_writer.py", line 631, in write_batch
self.write_table(pa_table, writer_batch_size)
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/arrow_writer.py", line 646, in write_table
pa_table = embed_table_storage(pa_table)
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/table.py", line 2248, in embed_table_storage
arrays = [
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/table.py", line 2249, in <listcomp>
embed_array_storage(table[name], feature, token_per_repo_id=token_per_repo_id)
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/table.py", line 1795, in wrapper
return pa.chunked_array([func(chunk, *args, **kwargs) for chunk in array.chunks])
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/table.py", line 1795, in <listcomp>
return pa.chunked_array([func(chunk, *args, **kwargs) for chunk in array.chunks])
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/table.py", line 2124, in embed_array_storage
return feature.embed_storage(array, token_per_repo_id=token_per_repo_id)
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/features/image.py", line 292, in embed_storage
storage = pa.StructArray.from_arrays([bytes_array, path_array], ["bytes", "path"], mask=bytes_array.is_null())
File "pyarrow/array.pxi", line 3257, in pyarrow.lib.StructArray.from_arrays
File "pyarrow/array.pxi", line 3697, in pyarrow.lib.c_mask_inverted_from_obj
TypeError: Mask must be a pyarrow.Array of type boolean
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/parquet_and_info.py", line 1451, in compute_config_parquet_and_info_response
parquet_operations, partial, estimated_dataset_info = stream_convert_to_parquet(
File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 994, in stream_convert_to_parquet
builder._prepare_split(
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 1447, in _prepare_split
for job_id, done, content in self._prepare_split_single(
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 1604, in _prepare_split_single
raise DatasetGenerationError("An error occurred while generating the dataset") from e
datasets.exceptions.DatasetGenerationError: An error occurred while generating the datasetNeed help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.
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WorldFloodsv2 dataset
This repository contains the WorldFloodsv2 dataset released with the publication:
E. Portalés-Julià, G. Mateo-García, C. Purcell, and L. Gómez-Chova Global flood extent segmentation in optical satellite images. Scientific Reports 13, 20316 (2023). DOI: 10.1038/s41598-023-47595-7.
The WorldFloodsv2 database contains 509 pairs of Sentinel-2 images and flood segmentation masks. Splitted in train, val and test sets. It requires approximately 76GB of hard-disk storage.
Download the dataset
huggingface-cli download --cache-dir /path/to/cachedir --local-dir /path/to/localdir/WorldFloodsv2 --repo-type dataset isp-uv-es/WorldFloodsv2
Explore the dataset
The following ml4floods tutorials may help you explore and use this dataset:
- The exploring WorldFloodsv2 tutorial shows how to process the dataset and plot the images and masks.
- The WorldFloodsV2 torch dataset tutorial shows how to load the dataset with pytorch data loaders.
Licence
The WorldFloods database and all pre-trained models are released under a Creative Commons non-commercial licence
Cite
If you find this work useful, please cite:
@article{portales-julia_global_2023,
title = {Global flood extent segmentation in optical satellite images},
volume = {13},
issn = {2045-2322},
doi = {10.1038/s41598-023-47595-7},
number = {1},
urldate = {2023-11-30},
journal = {Scientific Reports},
author = {Portalés-Julià, Enrique and Mateo-García, Gonzalo and Purcell, Cormac and Gómez-Chova, Luis},
month = nov,
year = {2023},
pages = {20316},
}
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