Dataset Preview
Duplicate
The full dataset viewer is not available (click to read why). Only showing a preview of the rows.
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 ({'foreground_intensity_properties_per_channel', 'median_relative_size_after_cropping', 'shapes_after_crop', 'spacings'}) and 12 missing columns ({'numTraining', 'labels', 'release', 'training', 'name', 'licence', 'channel_names', 'reference', 'numTest', 'file_ending', 'description', 'tensorImageSize'}).

This happened while the json dataset builder was generating data using

hf://datasets/KagglingFace/FYP-KiTS-A-Preprocessed/dataset_fingerprint.json (at revision f91ee51ce513c0051bdc9bbcd7adec46d1099e0f)

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': {'Cortex': Value(dtype='string', id=None), 'Medulla': 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 1316, in compute_config_parquet_and_info_response
                  parquet_operations, partial = stream_convert_to_parquet(
                File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 909, in stream_convert_to_parquet
                  builder._prepare_split(
                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 ({'foreground_intensity_properties_per_channel', 'median_relative_size_after_cropping', 'shapes_after_crop', 'spacings'}) and 12 missing columns ({'numTraining', 'labels', 'release', 'training', 'name', 'licence', 'channel_names', 'reference', 'numTest', 'file_ending', 'description', 'tensorImageSize'}).
              
              This happened while the json dataset builder was generating data using
              
              hf://datasets/KagglingFace/FYP-KiTS-A-Preprocessed/dataset_fingerprint.json (at revision f91ee51ce513c0051bdc9bbcd7adec46d1099e0f)
              
              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
val
sequence
train
sequence
{ "0": "CT" }
kidney and kidney tumor segmentation
.nii.gz
{ "Cortex": "3", "Medulla": "2", "Tumor": "1", "background": "0" }
FYP-KiTS
0
40
Final year project KiTS data for nnunet v2
0.0
4D
[ { "image": "./imagesTr/case_00000.nii.gz", "label": "./labelsTr/case_00000.nii.gz" }, { "image": "./imagesTr/case_00001.nii.gz", "label": "./labelsTr/case_00001.nii.gz" }, { "image": "./imagesTr/case_00002.nii.gz", "label": "./labelsTr/case_00002.nii.gz" }, { "image": "./imag...
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
{ "0": { "max": 669, "mean": 122.23634338378906, "median": 126, "min": -161, "percentile_00_5": -118, "percentile_99_5": 302, "std": 73.87754821777344 } }
1
[ [ 122, 512, 512 ], [ 97, 512, 512 ], [ 80, 512, 512 ], [ 106, 512, 512 ], [ 34, 512, 512 ], [ 151, 512, 512 ], [ 87, 512, 512 ], [ 31, 512, 512 ], [ 100, 512, 512 ], [ ...
[ [ 1, 0.748046875, 0.748046875 ], [ 1, 0.626953125, 0.626953125 ], [ 1.25, 0.7402340173721313, 0.7402340173721313 ], [ 1.25, 0.7402340173721313, 0.7402340173721313 ], [ 1.25, 0.7402340173721313, 0.7402340173721313 ], [ 0.625, 0.8...
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
{ "0": { "max": 669, "mean": 122.23634338378906, "median": 126, "min": -161, "percentile_00_5": -118, "percentile_99_5": 302, "std": 73.87754821777344 } }
null
null
null
Dataset996_KiTS
nnUNetPlans
[ 1.25, 0.7402340173721313, 0.7402340173721313 ]
[ 98, 512, 512 ]
SimpleITKIO
[ 0, 1, 2 ]
[ 0, 1, 2 ]
{ "2d": { "data_identifier": "nnUNetPlans_2d", "preprocessor_name": "DefaultPreprocessor", "batch_size": 12, "patch_size": [ 512, 512 ], "median_image_size_in_voxels": [ 512, 512 ], "spacing": [ 0.7402340173721313, 0.7402340173721313 ], "norm...
ExperimentPlanner
LabelManager
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
[ "case_00002", "case_00003", "case_00005", "case_00019", "case_00021", "case_00025", "case_00028", "case_00032" ]
[ "case_00000", "case_00001", "case_00004", "case_00006", "case_00007", "case_00008", "case_00009", "case_00010", "case_00011", "case_00012", "case_00013", "case_00014", "case_00015", "case_00016", "case_00017", "case_00018", "case_00020", "case_00022", "case_00023", "case_00024"...
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
[ "case_00000", "case_00004", "case_00008", "case_00012", "case_00015", "case_00030", "case_00033", "case_00035" ]
[ "case_00001", "case_00002", "case_00003", "case_00005", "case_00006", "case_00007", "case_00009", "case_00010", "case_00011", "case_00013", "case_00014", "case_00016", "case_00017", "case_00018", "case_00019", "case_00020", "case_00021", "case_00022", "case_00023", "case_00024"...
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
[ "case_00006", "case_00007", "case_00010", "case_00013", "case_00017", "case_00020", "case_00024", "case_00026" ]
[ "case_00000", "case_00001", "case_00002", "case_00003", "case_00004", "case_00005", "case_00008", "case_00009", "case_00011", "case_00012", "case_00014", "case_00015", "case_00016", "case_00018", "case_00019", "case_00021", "case_00022", "case_00023", "case_00025", "case_00027"...
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
[ "case_00009", "case_00011", "case_00016", "case_00018", "case_00022", "case_00023", "case_00027", "case_00031" ]
[ "case_00000", "case_00001", "case_00002", "case_00003", "case_00004", "case_00005", "case_00006", "case_00007", "case_00008", "case_00010", "case_00012", "case_00013", "case_00014", "case_00015", "case_00017", "case_00019", "case_00020", "case_00021", "case_00024", "case_00025"...
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
[ "case_00001", "case_00014", "case_00029", "case_00034", "case_00036", "case_00037", "case_00038", "case_00039" ]
[ "case_00000", "case_00002", "case_00003", "case_00004", "case_00005", "case_00006", "case_00007", "case_00008", "case_00009", "case_00010", "case_00011", "case_00012", "case_00013", "case_00015", "case_00016", "case_00017", "case_00018", "case_00019", "case_00020", "case_00021"...
README.md exists but content is empty.
Downloads last month
2