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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 4 new columns ({'median_relative_size_after_cropping', 'spacings', 'foreground_intensity_properties_per_channel', 'shapes_after_crop'}) and 12 missing columns ({'labels', 'reference', 'training', 'channel_names', 'name', 'numTraining', 'description', 'release', 'numTest', 'tensorImageSize', 'licence', 'file_ending'}).
This happened while the json dataset builder was generating data using
hf://datasets/KagglingFace/nnUNetPlans_3d_lowres_KiTS19/dataset_fingerprint.json (at revision 4b105883db2738f6c7b2fef349d2918c3a7e1610)
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 2011, in _prepare_split_single
writer.write_table(table)
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/arrow_writer.py", line 585, 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 2302, in table_cast
return cast_table_to_schema(table, schema)
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/table.py", line 2256, in cast_table_to_schema
raise CastError(
datasets.table.CastError: Couldn't cast
foreground_intensity_properties_per_channel: struct<0: struct<max: double, mean: double, median: double, min: double, percentile_00_5: double, percentile_99_5: double, std: double>>
child 0, 0: struct<max: double, mean: double, median: double, min: double, percentile_00_5: double, percentile_99_5: double, std: double>
child 0, max: double
child 1, mean: double
child 2, median: double
child 3, min: double
child 4, percentile_00_5: double
child 5, percentile_99_5: double
child 6, std: double
median_relative_size_after_cropping: double
shapes_after_crop: list<item: list<item: int64>>
child 0, item: list<item: int64>
child 0, item: int64
spacings: list<item: list<item: double>>
child 0, item: list<item: double>
child 0, item: double
to
{'channel_names': {'0': Value(dtype='string', id=None)}, 'description': Value(dtype='string', id=None), 'file_ending': Value(dtype='string', id=None), 'labels': {'Kidney': Value(dtype='string', id=None), 'Tumor': Value(dtype='string', id=None), 'background': Value(dtype='string', id=None)}, 'licence': Value(dtype='string', id=None), 'name': Value(dtype='string', id=None), 'numTest': Value(dtype='int64', id=None), 'numTraining': Value(dtype='int64', id=None), 'reference': Value(dtype='string', id=None), 'release': Value(dtype='string', id=None), 'tensorImageSize': Value(dtype='string', id=None), 'training': [{'image': Value(dtype='string', id=None), 'label': 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 1321, in compute_config_parquet_and_info_response
parquet_operations = convert_to_parquet(builder)
File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 935, in convert_to_parquet
builder.download_and_prepare(
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 1027, in download_and_prepare
self._download_and_prepare(
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 1122, in _download_and_prepare
self._prepare_split(split_generator, **prepare_split_kwargs)
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 1882, 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 2013, 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 4 new columns ({'median_relative_size_after_cropping', 'spacings', 'foreground_intensity_properties_per_channel', 'shapes_after_crop'}) and 12 missing columns ({'labels', 'reference', 'training', 'channel_names', 'name', 'numTraining', 'description', 'release', 'numTest', 'tensorImageSize', 'licence', 'file_ending'}).
This happened while the json dataset builder was generating data using
hf://datasets/KagglingFace/nnUNetPlans_3d_lowres_KiTS19/dataset_fingerprint.json (at revision 4b105883db2738f6c7b2fef349d2918c3a7e1610)
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.
channel_names
dict | description
string | file_ending
string | labels
dict | licence
string | name
string | numTest
int64 | numTraining
int64 | reference
string | release
string | tensorImageSize
string | training
list | foreground_intensity_properties_per_channel
dict | median_relative_size_after_cropping
float64 | shapes_after_crop
sequence | spacings
sequence | dataset_name
string | plans_name
string | original_median_spacing_after_transp
sequence | original_median_shape_after_transp
sequence | image_reader_writer
string | transpose_forward
sequence | transpose_backward
sequence | configurations
dict | experiment_planner_used
string | label_manager
string |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
{
"0": "CT"
} | kidney and kidney tumor segmentation | .nii.gz | {
"Kidney": "1",
"Tumor": "2",
"background": "0"
} | KiTS | 0 | 210 | KiTS data for nnunet | 0.0 | 4D | [
{
"image": "./imagesTr/case_00000.nii.gz",
"label": "./labelsTr/case_00000.nii.gz"
},
{
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"label": "./labelsTr/case_00001.nii.gz"
},
{
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"label": "./labelsTr/case_00002.nii.gz"
},
{
"image": "./imagesTr/case_00003.nii.gz",
"label": "./labelsTr/case_00003.nii.gz"
},
{
"image": "./imagesTr/case_00004.nii.gz",
"label": "./labelsTr/case_00004.nii.gz"
},
{
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"label": "./labelsTr/case_00005.nii.gz"
},
{
"image": "./imagesTr/case_00006.nii.gz",
"label": "./labelsTr/case_00006.nii.gz"
},
{
"image": "./imagesTr/case_00007.nii.gz",
"label": "./labelsTr/case_00007.nii.gz"
},
{
"image": "./imagesTr/case_00008.nii.gz",
"label": "./labelsTr/case_00008.nii.gz"
},
{
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"label": "./labelsTr/case_00009.nii.gz"
},
{
"image": "./imagesTr/case_00010.nii.gz",
"label": "./labelsTr/case_00010.nii.gz"
},
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"label": "./labelsTr/case_00011.nii.gz"
},
{
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"label": "./labelsTr/case_00012.nii.gz"
},
{
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"label": "./labelsTr/case_00013.nii.gz"
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"label": "./labelsTr/case_00014.nii.gz"
},
{
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"label": "./labelsTr/case_00015.nii.gz"
},
{
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"label": "./labelsTr/case_00016.nii.gz"
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},
{
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"label": "./labelsTr/case_00018.nii.gz"
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{
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"label": "./labelsTr/case_00019.nii.gz"
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{
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"label": "./labelsTr/case_00020.nii.gz"
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{
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{
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{
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{
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{
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} | ExperimentPlanner | LabelManager |
Please cite the following paper when using nnU-Net: Isensee, F., Jaeger, P. F., Kohl, S. A., Petersen, J., & Maier-Hein, K. H. (2021). nnU-Net: a self-configuring method for deep learning-based biomedical image segmentation. Nature methods, 18(2), 203-211.
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