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The dataset generation failed because of a cast error
Error code: DatasetGenerationCastError
Exception: DatasetGenerationCastError
Message: An error occurred while generating the dataset
All the data files must have the same columns, but at some point there are 8 new columns ({'ignore_index', 'num_samples', 'split', 'attributes', 'Dataset', 'std', 'mean', 'classes'}) and 3 missing columns ({'config', 'chunks', 'updated_at'}).
This happened while the json dataset builder was generating data using
hf://datasets/JessicaYuan/EarthNets_MMFlood/optimized_mmflood_sar_train/metadata.json (at revision 1728b0f1e552b60c0c0cbbd954b92617d9e1cbfa)
Please either edit the data files to have matching columns, or separate them into different configurations (see docs at https://hf.co/docs/hub/datasets-manual-configuration#multiple-configurations)
Traceback: Traceback (most recent call last):
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 1870, in _prepare_split_single
writer.write_table(table)
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/arrow_writer.py", line 622, in write_table
pa_table = table_cast(pa_table, self._schema)
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/table.py", line 2292, in table_cast
return cast_table_to_schema(table, schema)
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/table.py", line 2240, in cast_table_to_schema
raise CastError(
datasets.table.CastError: Couldn't cast
Dataset: string
split: string
num_samples: int64
mean: list<item: double>
child 0, item: double
std: list<item: double>
child 0, item: double
classes: struct<0: string, 1: string>
child 0, 0: string
child 1, 1: string
ignore_index: int64
attributes: struct<image: struct<dtype: string, bands: list<item: string>>, label: struct<dtype: string>>
child 0, image: struct<dtype: string, bands: list<item: string>>
child 0, dtype: string
child 1, bands: list<item: string>
child 0, item: string
child 1, label: struct<dtype: string>
child 0, dtype: string
to
{'chunks': [{'chunk_bytes': Value(dtype='int64', id=None), 'chunk_size': Value(dtype='int64', id=None), 'dim': Value(dtype='null', id=None), 'filename': Value(dtype='string', id=None)}], 'config': {'chunk_bytes': Value(dtype='int64', id=None), 'chunk_size': Value(dtype='null', id=None), 'compression': Value(dtype='null', id=None), 'data_format': Sequence(feature=Value(dtype='string', id=None), length=-1, id=None), 'data_spec': Value(dtype='string', id=None), 'encryption': Value(dtype='null', id=None), 'item_loader': Value(dtype='string', id=None)}, 'updated_at': Value(dtype='string', id=None)}
because column names don't match
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 1412, 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 988, in stream_convert_to_parquet
builder._prepare_split(
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 1741, 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 1872, in _prepare_split_single
raise DatasetGenerationCastError.from_cast_error(
datasets.exceptions.DatasetGenerationCastError: An error occurred while generating the dataset
All the data files must have the same columns, but at some point there are 8 new columns ({'ignore_index', 'num_samples', 'split', 'attributes', 'Dataset', 'std', 'mean', 'classes'}) and 3 missing columns ({'config', 'chunks', 'updated_at'}).
This happened while the json dataset builder was generating data using
hf://datasets/JessicaYuan/EarthNets_MMFlood/optimized_mmflood_sar_train/metadata.json (at revision 1728b0f1e552b60c0c0cbbd954b92617d9e1cbfa)
Please either edit the data files to have matching columns, or separate them into different configurations (see docs at https://hf.co/docs/hub/datasets-manual-configuration#multiple-configurations)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.
chunks
list | config
dict | updated_at
string | Dataset
string | split
string | num_samples
int64 | mean
sequence | std
sequence | classes
dict | ignore_index
int64 | attributes
dict |
|---|---|---|---|---|---|---|---|---|---|---|
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] | {
"chunk_bytes": 256000000,
"chunk_size": null,
"compression": null,
"data_format": [
"numpy",
"numpy"
],
"data_spec": "[1, {\"type\": \"builtins.dict\", \"context\": \"[\\\"image\\\", \\\"label\\\"]\", \"children_spec\": [{\"type\": null, \"context\": null, \"children_spec\": []}, {\"type\": null, \"context\": null, \"children_spec\": []}]}]",
"encryption": null,
"item_loader": "PyTreeLoader"
} | 1733781944.399247 | null | null | null | null | null | null | null | null |
null | null | null | MMFlood_SAR | train | 6,181 | [
0.049329374,
0.011776519,
142.41237
] | [
0.0391287043,
0.0103687926,
81.1010422
] | {
"0": "background",
"1": "flood"
} | 255 | {
"image": {
"dtype": "float16",
"bands": [
"vv",
"vh",
"dem"
]
},
"label": {
"dtype": "uint8"
}
} |
How to use it
Install Dataset4EO
git clone --branch streaming https://github.com/EarthNets/Dataset4EO.git
pip install -e .
Then download the dataset from this Huggingface repo.
import dataset4eo as eodata
import time
train_dataset = eodata.StreamingDataset(input_dir="optimized_mmflood_sar_train", num_channels=3, shuffle=True, drop_last=True)
sample = dataset[101]
print(sample.keys())
print(sample["image"])
print(sample["simage"].shape)
print(sample["label"])
We acknowledge and give full credit to the original authors of SpectralEarth for their effort in creating this dataset. The dataset is re-hosted in compliance with its original license to facilitate further research. Please cite the following paper for the creation of the dataset:
@article{montello2022mmflood,
title={Mmflood: A multimodal dataset for flood delineation from satellite imagery},
author={Montello, Fabio and Arnaudo, Edoardo and Rossi, Claudio},
journal={IEEE Access},
volume={10},
pages={96774--96787},
year={2022},
publisher={IEEE}
}
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