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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 1 new columns ({'reference'})

This happened while the csv dataset builder was generating data using

hf://datasets/palapapa/iqa-project-dataset/csiq/labels.csv (at revision d3c663b196bad8dcbe6be251aa16f520d058d676)

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 "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 1831, in _prepare_split_single
                  writer.write_table(table)
                File "/usr/local/lib/python3.12/site-packages/datasets/arrow_writer.py", line 714, in write_table
                  pa_table = table_cast(pa_table, self._schema)
                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/table.py", line 2272, in table_cast
                  return cast_table_to_schema(table, schema)
                         ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/table.py", line 2218, in cast_table_to_schema
                  raise CastError(
              datasets.table.CastError: Couldn't cast
              filename: string
              mos: double
              stddev: double
              distortion: string
              scene1: string
              scene2: string
              scene3: string
              reference: string
              set: string
              -- schema metadata --
              pandas: '{"index_columns": [{"kind": "range", "name": null, "start": 0, "' + 1277
              to
              {'filename': Value('string'), 'mos': Value('float64'), 'stddev': Value('float64'), 'distortion': Value('string'), 'scene1': Value('string'), 'scene2': Value('string'), 'scene3': Value('string'), 'set': Value('string')}
              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 1450, 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 993, in stream_convert_to_parquet
                  builder._prepare_split(
                File "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 1702, in _prepare_split
                  for job_id, done, content in self._prepare_split_single(
                                               ^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 1833, 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 1 new columns ({'reference'})
              
              This happened while the csv dataset builder was generating data using
              
              hf://datasets/palapapa/iqa-project-dataset/csiq/labels.csv (at revision d3c663b196bad8dcbe6be251aa16f520d058d676)
              
              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.

filename
string
mos
float64
stddev
float64
distortion
string
scene1
string
scene2
string
scene3
null
set
string
DatabaseImage0001.JPG
4.51664
0.534734
blur
human
null
null
validation
DatabaseImage0003.JPG
1.300189
0.931311
blur
human
landscape
null
training
DatabaseImage0004.JPG
2.359893
0.991261
blur
animal
null
null
testing
DatabaseImage0005.JPG
4.200862
1.021639
contrast
cityscape
still_life
null
validation
DatabaseImage0006.JPG
2.872605
1.008459
contrast
landscape
null
null
training
DatabaseImage0007.JPG
3.721942
0.851709
contrast
landscape
null
null
training
DatabaseImage0008.JPG
3.073059
1.125115
underexposure
human
landscape
null
testing
DatabaseImage0009.JPG
3.705768
1.471081
underexposure
human
landscape
null
training
DatabaseImage0010.JPG
3.292988
0.731183
underexposure
human
landscape
null
validation
DatabaseImage0011.JPG
4.227649
0.634457
underexposure
human
landscape
null
training
DatabaseImage0012.JPG
4.255742
0.648101
underexposure
human
landscape
null
testing
DatabaseImage0013.JPG
3.508192
0.924821
underexposure
human
landscape
null
training
DatabaseImage0014.JPG
4.393557
0.775186
other
landscape
still_life
null
validation
DatabaseImage0015.JPG
1.498045
0.863367
blur
animal
null
null
validation
DatabaseImage0016.JPG
3.806228
0.725724
other
landscape
still_life
null
validation
DatabaseImage0017.JPG
4.0649
0.996841
other
landscape
still_life
null
training
DatabaseImage0018.JPG
4.203347
0.989735
other
landscape
still_life
null
training
DatabaseImage0019.JPG
3.969829
1.041061
other
cityscape
still_life
null
training
DatabaseImage0020.JPG
4.307062
0.662576
other
cityscape
still_life
null
validation
DatabaseImage0021.JPG
1.710015
0.76777
blur
cityscape
still_life
null
training
DatabaseImage0022.JPG
4.233081
0.722963
other
animal
landscape
null
training
DatabaseImage0023.JPG
3.975541
0.76932
blur
animal
landscape
null
validation
DatabaseImage0024.JPG
3.549119
0.656538
blur
landscape
still_life
null
training
DatabaseImage0025.JPG
4.18512
1.159479
other
plant
null
null
training
DatabaseImage0026.JPG
0.205564
0.219934
blur
animal
null
null
training
DatabaseImage0027.JPG
3.968425
0.996972
other
plant
null
null
validation
DatabaseImage0028.JPG
4.583859
0.609021
other
landscape
null
null
training
DatabaseImage0029.JPG
4.001393
0.669829
other
landscape
null
null
training
DatabaseImage0030.JPG
2.966772
1.307177
underexposure
night
plant
null
training
DatabaseImage0031.JPG
3.961538
0.955362
underexposure
night
plant
null
testing
DatabaseImage0032.JPG
3.064033
0.974352
underexposure
night
plant
null
training
DatabaseImage0033.JPG
2.789346
0.855114
blur
human
still_life
null
training
DatabaseImage0034.JPG
4.23348
0.668098
other
animal
human
null
training
DatabaseImage0035.JPG
3.56144
1.264044
blur
human
null
null
training
DatabaseImage0036.JPG
2.520349
1.086017
blur
human
null
null
validation
DatabaseImage0037.JPG
1.812106
0.892469
noise
animal
null
null
training
DatabaseImage0038.JPG
3.918377
0.874113
blur
human
null
null
training
DatabaseImage0039.JPG
3.539071
0.95639
blur
human
null
null
validation
DatabaseImage0040.JPG
3.52999
1.1364
blur
human
null
null
training
DatabaseImage0041.JPG
1.34816
1.006141
blur
human
null
null
training
DatabaseImage0042.JPG
3.938482
0.902959
other
still_life
null
null
training
DatabaseImage0043.JPG
1.504192
0.708377
blur
human
null
null
training
DatabaseImage0044.JPG
3.430586
0.88382
other
still_life
null
null
training
DatabaseImage0045.JPG
2.993695
0.864413
blur
still_life
null
null
validation
DatabaseImage0046.JPG
3.166457
0.708918
blur
still_life
null
null
training
DatabaseImage0047.JPG
3.580623
1.201894
other
cityscape
still_life
null
training
DatabaseImage0048.JPG
2.855774
0.918892
blur
indoor
still_life
null
training
DatabaseImage0049.JPG
3.489959
0.737962
blur
cityscape
still_life
null
training
DatabaseImage0050.JPG
3.040984
1.40199
blur
cityscape
still_life
null
training
DatabaseImage0051.JPG
3.391793
0.853621
other
cityscape
human
null
training
DatabaseImage0052.JPG
3.524768
0.954204
underexposure
landscape
still_life
null
validation
DatabaseImage0053.JPG
1.953342
0.869483
blur
cityscape
landscape
null
training
DatabaseImage0054.JPG
3.331747
1.214937
other
landscape
still_life
null
training
DatabaseImage0055.JPG
3.063648
1.016868
blur
cityscape
landscape
null
training
DatabaseImage0056.JPG
1.676249
0.526508
blur
landscape
still_life
null
training
DatabaseImage0057.JPG
2.50006
1.3714
blur
landscape
still_life
null
testing
DatabaseImage0058.JPG
3.506944
0.729993
blur
landscape
still_life
null
training
DatabaseImage0059.JPG
2.722127
0.696846
blur
animal
null
null
training
DatabaseImage0060.JPG
3.511558
1.144313
other
landscape
null
null
training
DatabaseImage0061.JPG
3.591654
0.830711
other
cityscape
landscape
null
training
DatabaseImage0062.JPG
3.349243
1.327844
other
cityscape
landscape
null
validation
DatabaseImage0063.JPG
4.823466
0.251741
other
animal
null
null
training
DatabaseImage0064.JPG
4.261754
0.615433
other
animal
null
null
training
DatabaseImage0065.JPG
3.298759
1.061522
other
others
null
null
testing
DatabaseImage0066.JPG
3.40016
1.306559
underexposure
night
null
null
training
DatabaseImage0067.JPG
4.00324
0.828161
underexposure
night
null
null
training
DatabaseImage0068.JPG
3.518285
0.985867
underexposure
night
null
null
training
DatabaseImage0069.JPG
3.803909
1.131372
contrast
landscape
still_life
null
training
DatabaseImage0070.JPG
2.636658
0.602579
blur
animal
null
null
training
DatabaseImage0071.JPG
1.809296
1.132168
blur
cityscape
landscape
null
validation
DatabaseImage0072.JPG
4.180408
0.708965
other
landscape
null
null
testing
DatabaseImage0073.JPG
3.804048
1.019302
contrast
cityscape
landscape
null
training
DatabaseImage0074.JPG
3.961583
0.999422
other
landscape
null
null
testing
DatabaseImage0075.JPG
3.563577
1.385424
contrast
landscape
null
null
training
DatabaseImage0076.JPG
2.270623
1.140011
blur
landscape
null
null
training
DatabaseImage0077.JPG
3.900799
0.58456
other
human
landscape
null
training
DatabaseImage0078.JPG
4.358753
0.829307
underexposure
cityscape
human
null
validation
DatabaseImage0079.JPG
4.299708
0.621045
other
human
landscape
null
training
DatabaseImage0080.JPG
2.271763
0.951499
blur
landscape
null
null
validation
DatabaseImage0081.JPG
3.169173
0.949363
noise
animal
null
null
training
DatabaseImage0082.JPG
4.506242
0.629082
other
landscape
null
null
validation
DatabaseImage0083.JPG
4.456427
0.423451
other
landscape
null
null
validation
DatabaseImage0084.JPG
4.73386
0.47867
other
landscape
null
null
testing
DatabaseImage0085.JPG
4.318907
0.751352
other
landscape
null
null
training
DatabaseImage0086.JPG
1.509551
0.98734
blur
others
null
null
validation
DatabaseImage0087.JPG
2.926077
1.372067
blur
plant
null
null
validation
DatabaseImage0088.JPG
3.302223
1.291673
underexposure
landscape
null
null
testing
DatabaseImage0089.JPG
4.327453
0.735821
other
landscape
null
null
validation
DatabaseImage0090.JPG
3.514962
1.00499
other
human
indoor
null
validation
DatabaseImage0091.JPG
0.634339
0.617992
blur
cityscape
human
null
validation
DatabaseImage0092.JPG
2.320849
0.599259
noise
animal
null
null
testing
DatabaseImage0093.JPG
3.400483
1.195876
underexposure
night
null
null
training
DatabaseImage0094.JPG
3.190192
1.1554
underexposure
night
null
null
training
DatabaseImage0095.JPG
3.518641
0.930417
underexposure
night
null
null
validation
DatabaseImage0096.JPG
2.801034
1.541187
underexposure
night
null
null
training
DatabaseImage0097.JPG
3.61899
0.797531
noise
human
night
null
validation
DatabaseImage0098.JPG
1.873681
0.785144
blur
indoor
still_life
null
training
DatabaseImage0099.JPG
3.338588
1.505803
underexposure
night
null
null
training
DatabaseImage0100.JPG
3.656938
1.173575
underexposure
night
null
null
training
DatabaseImage0101.JPG
3.957199
1.100856
blur
indoor
plant
null
training
End of preview.