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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 ({'images'}) and 2 missing columns ({'video', 'id'}).

This happened while the json dataset builder was generating data using

hf://datasets/3dllm/ScanQA/LLaVA_v2_ScanQA_v1.0_train.json (at revision 0876a9b78db49dc405615d7e4907781196f8abcc)

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
              conversations: list<item: struct<from: string, value: string>>
                child 0, item: struct<from: string, value: string>
                    child 0, from: string
                    child 1, value: string
              images: list<item: string>
                child 0, item: string
              -- schema metadata --
              pandas: '{"index_columns": [], "column_indexes": [], "columns": [{"name":' + 324
              to
              {'id': Value(dtype='int64', id=None), 'video': Value(dtype='string', id=None), 'conversations': [{'from': Value(dtype='string', id=None), 'value': 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 1417, 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 1049, in convert_to_parquet
                  builder.download_and_prepare(
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 924, in download_and_prepare
                  self._download_and_prepare(
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 1000, 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 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 1 new columns ({'images'}) and 2 missing columns ({'video', 'id'}).
              
              This happened while the json dataset builder was generating data using
              
              hf://datasets/3dllm/ScanQA/LLaVA_v2_ScanQA_v1.0_train.json (at revision 0876a9b78db49dc405615d7e4907781196f8abcc)
              
              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)

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id
int64
video
string
conversations
list
8
scannet/scene0000_00
[ { "from": "human", "value": "<video>\nWhat is in the right corner of room by curtains?" }, { "from": "gpt", "value": "Brown cabinet with tv sitting in it." } ]
7
scannet/scene0000_00
[ { "from": "human", "value": "<video>\nWhat color table is on the left side of the cabinet?" }, { "from": "gpt", "value": "Light brown." } ]
57
scannet/scene0000_00
[ { "from": "human", "value": "<video>\nWhat is on the left of the tv?" }, { "from": "gpt", "value": "Bicycle on floor." } ]
39
scannet/scene0000_00
[ { "from": "human", "value": "<video>\nWhere is the beige wooden working table placed?" }, { "from": "gpt", "value": "Right of tall cabinet." } ]
4
scannet/scene0000_00
[ { "from": "human", "value": "<video>\nWhat is in the corner of the bath?" }, { "from": "gpt", "value": "Shower." } ]
54
scannet/scene0000_00
[ { "from": "human", "value": "<video>\nWhat is placed next to the fridge?" }, { "from": "gpt", "value": "Door." } ]
3
scannet/scene0000_00
[ { "from": "human", "value": "<video>\nWhere is the silver bread toaster placed?" }, { "from": "gpt", "value": "Countertop." } ]
62
scannet/scene0000_00
[ { "from": "human", "value": "<video>\nWhat color is the plastic clothes handler?" }, { "from": "gpt", "value": "Blue." } ]
42
scannet/scene0000_00
[ { "from": "human", "value": "<video>\nOn what part of the cabinet is the beige cabinet placed?" }, { "from": "gpt", "value": "Right kitchen wall." } ]
8
scannet/scene0000_00
[ { "from": "human", "value": "<video>\nThe beige wooden bookshelf is placed next to what else?" }, { "from": "gpt", "value": "Brown wooden cabinet and television." } ]
12
scannet/scene0000_00
[ { "from": "human", "value": "<video>\nHow many trash cans can be seen on your right when you enter?" }, { "from": "gpt", "value": "2 small white trash cans." } ]
8
scannet/scene0000_00
[ { "from": "human", "value": "<video>\nWhere is the large wooden bookshelf placed?" }, { "from": "gpt", "value": "To right of brown wooden cabinet and television up against wall near windows." } ]
54
scannet/scene0000_00
[ { "from": "human", "value": "<video>\nWhat is the white wooden door?" }, { "from": "gpt", "value": "Kitchen door." } ]
43
scannet/scene0000_00
[ { "from": "human", "value": "<video>\nWhere is the brown wooden cabinet located?" }, { "from": "gpt", "value": "Above kitchen counter tops." } ]
52
scannet/scene0000_00
[ { "from": "human", "value": "<video>\nWhat is placed next to the fridge on the upper side of the cabinets?" }, { "from": "gpt", "value": "Microwave oven." } ]
43
scannet/scene0000_00
[ { "from": "human", "value": "<video>\nOn what side of the cabinets is the microwave located?" }, { "from": "gpt", "value": "Right side." } ]
34
scannet/scene0000_00
[ { "from": "human", "value": "<video>\nWhat color is the coffee table in front of a couch?" }, { "from": "gpt", "value": "Gray." } ]
32
scannet/scene0000_00
[ { "from": "human", "value": "<video>\nWhat is the coffee table in front of?" }, { "from": "gpt", "value": "Couch." } ]
6
scannet/scene0001_00
[ { "from": "human", "value": "<video>\nHow many coffee tables does the brown armchair face?" }, { "from": "gpt", "value": "2." } ]
3
scannet/scene0001_00
[ { "from": "human", "value": "<video>\nWhat kind of table is in the house?" }, { "from": "gpt", "value": "Wooden." } ]
19
scannet/scene0001_00
[ { "from": "human", "value": "<video>\nWhat is to the right of the picture?" }, { "from": "gpt", "value": "Doorframe." } ]
1
scannet/scene0001_00
[ { "from": "human", "value": "<video>\nWhat color is the couch?" }, { "from": "gpt", "value": "Brown couch." } ]
10
scannet/scene0001_00
[ { "from": "human", "value": "<video>\nHow many brown chairs are on the right and left of the brown couch?" }, { "from": "gpt", "value": "2 couches." } ]
7
scannet/scene0001_00
[ { "from": "human", "value": "<video>\nWhat type of wood is the coffee table?" }, { "from": "gpt", "value": "Brown coffee table." } ]
6
scannet/scene0001_00
[ { "from": "human", "value": "<video>\nWhere does the coffee table sit in the sitting area?" }, { "from": "gpt", "value": "Next to other coffee table surrounded by 2 couches and 2 armchairs." } ]
6
scannet/scene0001_00
[ { "from": "human", "value": "<video>\nThe coffee table on the right is closest to what?" }, { "from": "gpt", "value": "Brown couch." } ]
0
scannet/scene0001_00
[ { "from": "human", "value": "<video>\nWhat color leather sofa is in the room?" }, { "from": "gpt", "value": "Brown." } ]
6
scannet/scene0001_00
[ { "from": "human", "value": "<video>\nWhat type of coffee table is in the room?" }, { "from": "gpt", "value": "Square wood coffee table." } ]
6
scannet/scene0001_00
[ { "from": "human", "value": "<video>\nWhat kind of wooden coffee table is on the right of the coffee table?" }, { "from": "gpt", "value": "Square wood coffee table." } ]
6
scannet/scene0001_00
[ { "from": "human", "value": "<video>\nWhere is the coffee table kept?" }, { "from": "gpt", "value": "In middle of seating area." } ]
6
scannet/scene0001_00
[ { "from": "human", "value": "<video>\nWhere is the coffee table lying?" }, { "from": "gpt", "value": "To right of picture." } ]
5
scannet/scene0001_00
[ { "from": "human", "value": "<video>\nThe brown couch is right next to what?" }, { "from": "gpt", "value": "Tables." } ]
5
scannet/scene0001_00
[ { "from": "human", "value": "<video>\nThe couch is on the right of what?" }, { "from": "gpt", "value": "Tables." } ]
6
scannet/scene0001_00
[ { "from": "human", "value": "<video>\nHow many tables is the brown armchair facing?" }, { "from": "gpt", "value": "2." } ]
10
scannet/scene0001_00
[ { "from": "human", "value": "<video>\nWhat color is the couch by the two sets of chairs?" }, { "from": "gpt", "value": "Reddish grey." } ]
19
scannet/scene0001_00
[ { "from": "human", "value": "<video>\nWhat's behind the couch to the left of the two coffee tables?" }, { "from": "gpt", "value": "Door." } ]
6
scannet/scene0001_00
[ { "from": "human", "value": "<video>\nWhat's the color of the coffee tables in the room?" }, { "from": "gpt", "value": "Brown." } ]
10
scannet/scene0001_00
[ { "from": "human", "value": "<video>\nHow many arm chairs are there?" }, { "from": "gpt", "value": "4." } ]
10
scannet/scene0001_00
[ { "from": "human", "value": "<video>\nWhere is the brown arm chair located?" }, { "from": "gpt", "value": "In middle of room." } ]
7
scannet/scene0001_00
[ { "from": "human", "value": "<video>\nWhat is to the left of the small wooden table?" }, { "from": "gpt", "value": "Couch." } ]
8
scannet/scene0001_00
[ { "from": "human", "value": "<video>\nWhat type of couch is placed next to the light wood tea table?" }, { "from": "gpt", "value": "Loveseat." } ]
0
scannet/scene0001_00
[ { "from": "human", "value": "<video>\nWhat is the couch nearest the window placed in front of?" }, { "from": "gpt", "value": "Table." } ]
6
scannet/scene0001_00
[ { "from": "human", "value": "<video>\nHow many identical coffee tables are in a center of the room?" }, { "from": "gpt", "value": "2." } ]
8
scannet/scene0001_00
[ { "from": "human", "value": "<video>\nThe window is furthest away from which couch?" }, { "from": "gpt", "value": "If facing window 1 on left." } ]
12
scannet/scene0002_00
[ { "from": "human", "value": "<video>\nWhere is the white cabinet located?" }, { "from": "gpt", "value": "Right of door." } ]
31
scannet/scene0002_00
[ { "from": "human", "value": "<video>\nWhat does the chair's back face?" }, { "from": "gpt", "value": "Small cabinet." } ]
14
scannet/scene0002_00
[ { "from": "human", "value": "<video>\nWhat is the front of the chair resting on?" }, { "from": "gpt", "value": "Door." } ]
47
scannet/scene0002_00
[ { "from": "human", "value": "<video>\nWhat is attached to the wall of the house?" }, { "from": "gpt", "value": "Radiator." } ]
18
scannet/scene0002_00
[ { "from": "human", "value": "<video>\nWhat color is the chair in front of the radiator?" }, { "from": "gpt", "value": "Brown and black." } ]
46
scannet/scene0002_00
[ { "from": "human", "value": "<video>\nWhat color is the ottoman?" }, { "from": "gpt", "value": "Dark green." } ]
49
scannet/scene0002_00
[ { "from": "human", "value": "<video>\nWhat is in front of the radiator?" }, { "from": "gpt", "value": "Small table." } ]
49
scannet/scene0002_00
[ { "from": "human", "value": "<video>\nWhat is next to the chair?" }, { "from": "gpt", "value": "Small table." } ]
54
scannet/scene0002_00
[ { "from": "human", "value": "<video>\nWhat color storage bin is next to the orange one?" }, { "from": "gpt", "value": "Teal." } ]
53
scannet/scene0002_00
[ { "from": "human", "value": "<video>\nWhat is on the left of the brown storage bin?" }, { "from": "gpt", "value": "Teal storage bin." } ]
48
scannet/scene0002_00
[ { "from": "human", "value": "<video>\nWhere is the triangular shape table located?" }, { "from": "gpt", "value": "In front of radiator." } ]
33
scannet/scene0002_00
[ { "from": "human", "value": "<video>\nWhere is the brown door located?" }, { "from": "gpt", "value": "Between 2 tall cabinets." } ]
17
scannet/scene0002_00
[ { "from": "human", "value": "<video>\nWhat does the rectangular window with brown molding sit behind?" }, { "from": "gpt", "value": "Tv stand." } ]
37
scannet/scene0002_00
[ { "from": "human", "value": "<video>\nWhere do the bottoms of the windows sit?" }, { "from": "gpt", "value": "Floor level." } ]
38
scannet/scene0002_00
[ { "from": "human", "value": "<video>\nThe tv stand is sitting to the right of what?" }, { "from": "gpt", "value": "Window." } ]
37
scannet/scene0002_00
[ { "from": "human", "value": "<video>\nWhere is the tv stand sitting?" }, { "from": "gpt", "value": "Under 2 windows." } ]
49
scannet/scene0002_00
[ { "from": "human", "value": "<video>\nWhat sits in front of the radiator on the right?" }, { "from": "gpt", "value": "Small table." } ]
55
scannet/scene0002_00
[ { "from": "human", "value": "<video>\nWhat is the black microwave on top of?" }, { "from": "gpt", "value": "Mini fridge." } ]
27
scannet/scene0002_00
[ { "from": "human", "value": "<video>\nWhat is kept on the chair left of the windows?" }, { "from": "gpt", "value": "Pillow." } ]
31
scannet/scene0002_00
[ { "from": "human", "value": "<video>\nHow many drawers are in the storage cabinet?" }, { "from": "gpt", "value": "3." } ]
31
scannet/scene0002_00
[ { "from": "human", "value": "<video>\nWhat is the height of the storage cabinet?" }, { "from": "gpt", "value": "Short." } ]
33
scannet/scene0002_00
[ { "from": "human", "value": "<video>\nWhat is found in one corner of the room?" }, { "from": "gpt", "value": "Cabinet." } ]
33
scannet/scene0002_00
[ { "from": "human", "value": "<video>\nWhat can be seen near the refrigerator?" }, { "from": "gpt", "value": "Cabinet." } ]
56
scannet/scene0002_00
[ { "from": "human", "value": "<video>\nWhat color is the couch?" }, { "from": "gpt", "value": "Dark gray." } ]
28
scannet/scene0002_00
[ { "from": "human", "value": "<video>\nWhat does the dark grey upholstered couch have in its middle?" }, { "from": "gpt", "value": "Blue pillow." } ]
56
scannet/scene0002_00
[ { "from": "human", "value": "<video>\nWhat is under the couch's front feet?" }, { "from": "gpt", "value": "Orange rug." } ]
53
scannet/scene0002_00
[ { "from": "human", "value": "<video>\nWhat color storage bin is on top of a white cabinet?" }, { "from": "gpt", "value": "Orange." } ]
33
scannet/scene0002_00
[ { "from": "human", "value": "<video>\nWhat is the orange storage bin on top of?" }, { "from": "gpt", "value": "White cabinet." } ]
17
scannet/scene0002_00
[ { "from": "human", "value": "<video>\nWhat is in front of a window?" }, { "from": "gpt", "value": "White tv stand." } ]
37
scannet/scene0002_00
[ { "from": "human", "value": "<video>\nWhat is the tv stand in front of?" }, { "from": "gpt", "value": "2 windows." } ]
28
scannet/scene0002_00
[ { "from": "human", "value": "<video>\nWhat color is the throw pillow?" }, { "from": "gpt", "value": "Blue." } ]
56
scannet/scene0002_00
[ { "from": "human", "value": "<video>\nWhat color couch is the pillow sitting on?" }, { "from": "gpt", "value": "Grey." } ]
23
scannet/scene0002_00
[ { "from": "human", "value": "<video>\nWhat color is the trash can?" }, { "from": "gpt", "value": "Blue." } ]
32
scannet/scene0002_00
[ { "from": "human", "value": "<video>\nWhere is the trash can located?" }, { "from": "gpt", "value": "Under white shelf." } ]
56
scannet/scene0002_00
[ { "from": "human", "value": "<video>\nWhat is in front of the door in the room?" }, { "from": "gpt", "value": "Couch." } ]
46
scannet/scene0002_00
[ { "from": "human", "value": "<video>\nHow many controllers are on top of the green ottoman?" }, { "from": "gpt", "value": "3." } ]
12
scannet/scene0002_00
[ { "from": "human", "value": "<video>\nWhere does the tall white cabinet sit?" }, { "from": "gpt", "value": "Left of door." } ]
35
scannet/scene0002_00
[ { "from": "human", "value": "<video>\nWhat color is the cabinet?" }, { "from": "gpt", "value": "White." } ]
55
scannet/scene0002_00
[ { "from": "human", "value": "<video>\nWhat color is the mini fridge and microwave combo?" }, { "from": "gpt", "value": "Black." } ]
25
scannet/scene0002_00
[ { "from": "human", "value": "<video>\nHow many pillows are on the couch?" }, { "from": "gpt", "value": "2." } ]
25
scannet/scene0002_00
[ { "from": "human", "value": "<video>\nTo what direction is the other pillow on the couch?" }, { "from": "gpt", "value": "Left." } ]
46
scannet/scene0002_00
[ { "from": "human", "value": "<video>\nWhat color is the coffee table in the center of the room?" }, { "from": "gpt", "value": "Teal." } ]
55
scannet/scene0002_00
[ { "from": "human", "value": "<video>\nWhat is to the right of the white cabinet?" }, { "from": "gpt", "value": "Refrigerator." } ]
25
scannet/scene0002_00
[ { "from": "human", "value": "<video>\nWhat sits on the grey couch?" }, { "from": "gpt", "value": "Pillows." } ]
33
scannet/scene0002_00
[ { "from": "human", "value": "<video>\nWhat is next to the printer?" }, { "from": "gpt", "value": "White cabinet." } ]
17
scannet/scene0002_00
[ { "from": "human", "value": "<video>\nWhat is the window behind?" }, { "from": "gpt", "value": "Tv stand." } ]
28
scannet/scene0002_00
[ { "from": "human", "value": "<video>\nWhat color is the pillow?" }, { "from": "gpt", "value": "Blue." } ]
26
scannet/scene0002_00
[ { "from": "human", "value": "<video>\nWhere is the pillow located?" }, { "from": "gpt", "value": "On wooden chair." } ]
53
scannet/scene0002_00
[ { "from": "human", "value": "<video>\nHow many bins are located on top of the cabinet?" }, { "from": "gpt", "value": "2." } ]
53
scannet/scene0002_00
[ { "from": "human", "value": "<video>\nHow many large bins are located on top of cabinet?" }, { "from": "gpt", "value": "2." } ]
55
scannet/scene0002_00
[ { "from": "human", "value": "<video>\nWhat color is the fridge under the microwave?" }, { "from": "gpt", "value": "Black." } ]
19
scannet/scene0002_00
[ { "from": "human", "value": "<video>\nWhat is next to the gray couch?" }, { "from": "gpt", "value": "Wooden chair with grey cushions." } ]
37
scannet/scene0002_00
[ { "from": "human", "value": "<video>\nWhere is the tv stand located?" }, { "from": "gpt", "value": "Under 2 windows." } ]
48
scannet/scene0002_00
[ { "from": "human", "value": "<video>\nWhat is next to the tv stand?" }, { "from": "gpt", "value": "Radiator." } ]
24
scannet/scene0002_00
[ { "from": "human", "value": "<video>\nWhat is next to the trash can?" }, { "from": "gpt", "value": "Trashcan." } ]
12
scannet/scene0002_00
[ { "from": "human", "value": "<video>\nWhere is the cabinet located?" }, { "from": "gpt", "value": "Between 2 doors." } ]
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