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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 9 new columns ({'obj_question', 'supercategory', 'super_question', 'div', 'point', 'bbox', 'ans', 'general_question', 'obj_type'}) and 3 missing columns ({'points', 'all_objs', 'question'}). This happened while the json dataset builder was generating data using hf://datasets/SY-Xuan/Pink_sft/LookTwiceQA/train_split.json (at revision cf299a68cca1801ff350b5134bf1ee21d3efe158) 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 obj_question: string supercategory: string super_question: string id: int64 div: string point: struct<ans: string, x: int64, y: int64> child 0, ans: string child 1, x: int64 child 2, y: int64 bbox: struct<h: int64, merged_object_ids: list<item: int64>, names: list<item: string>, object_id: int64, synsets: list<item: string>, w: int64, x: int64, y: int64> child 0, h: int64 child 1, merged_object_ids: list<item: int64> child 0, item: int64 child 2, names: list<item: string> child 0, item: string child 3, object_id: int64 child 4, synsets: list<item: string> child 0, item: string child 5, w: int64 child 6, x: int64 child 7, y: int64 ans: string general_question: string obj_type: string to {'question': Value(dtype='string', id=None), 'points': {'ans': Value(dtype='string', id=None), 'x': Value(dtype='int64', id=None), 'y': Value(dtype='int64', id=None)}, 'all_objs': {'attributes': Sequence(feature=Value(dtype='string', id=None), length=-1, id=None), 'h': Value(dtype='int64', id=None), 'names': Sequence(feature=Value(dtype='string', id=None), length=-1, id=None), 'object_id': Value(dtype='int64', id=None), 'synsets': Sequence(feature=Value(dtype='string', id=None), length=-1, id=None), 'w': Value(dtype='int64', id=None), 'x': Value(dtype='int64', id=None), 'y': Value(dtype='int64', id=None)}, 'id': Value(dtype='int64', 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 9 new columns ({'obj_question', 'supercategory', 'super_question', 'div', 'point', 'bbox', 'ans', 'general_question', 'obj_type'}) and 3 missing columns ({'points', 'all_objs', 'question'}). This happened while the json dataset builder was generating data using hf://datasets/SY-Xuan/Pink_sft/LookTwiceQA/train_split.json (at revision cf299a68cca1801ff350b5134bf1ee21d3efe158) 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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all_objs
dict | points
dict | question
string | id
int64 |
---|---|---|---|
{
"attributes": [
"green"
],
"h": 37,
"names": [
"hay"
],
"object_id": 761385,
"synsets": [
"hay.n.01"
],
"w": 78,
"x": 317,
"y": 105
} | {
"ans": "green",
"x": 356,
"y": 123
} | What color is this hay? | 2,363,870 |
{
"attributes": [
"brown"
],
"h": 71,
"names": [
"hay"
],
"object_id": 761386,
"synsets": [
"hay.n.01"
],
"w": 51,
"x": 443,
"y": 65
} | {
"ans": "brown",
"x": 468,
"y": 100
} | What color is this hay? | 2,363,870 |
{
"attributes": [
"blue"
],
"h": 57,
"names": [
"light"
],
"object_id": 445878,
"synsets": [
"light.n.01"
],
"w": 487,
"x": 12,
"y": 157
} | {
"ans": "blue",
"x": 255,
"y": 185
} | What color is this light? | 2,396,299 |
{
"attributes": [
"green"
],
"h": 9,
"names": [
"light"
],
"object_id": 445893,
"synsets": [
"light.n.01"
],
"w": 10,
"x": 198,
"y": 190
} | {
"ans": "green",
"x": 203,
"y": 194
} | What color is this light? | 2,396,299 |
{
"attributes": [
"brown"
],
"h": 29,
"names": [
"leaves"
],
"object_id": 606138,
"synsets": [
"leaf.n.01"
],
"w": 20,
"x": 467,
"y": 94
} | {
"ans": "brown",
"x": 477,
"y": 108
} | What color is this leaves? | 2,370,140 |
{
"attributes": [
"green"
],
"h": 67,
"names": [
"leaves"
],
"object_id": 606135,
"synsets": [
"leaf.n.01"
],
"w": 57,
"x": 299,
"y": 8
} | {
"ans": "green",
"x": 327,
"y": 41
} | What color is this leaves? | 2,370,140 |
{
"attributes": [
"red"
],
"h": 60,
"names": [
"pants"
],
"object_id": 290732,
"synsets": [
"trouser.n.01"
],
"w": 25,
"x": 183,
"y": 254
} | {
"ans": "red",
"x": 195,
"y": 284
} | What color is this pants? | 2,406,750 |
{
"attributes": [
"black"
],
"h": 43,
"names": [
"pants"
],
"object_id": 290743,
"synsets": [
"trouser.n.01"
],
"w": 27,
"x": 109,
"y": 270
} | {
"ans": "black",
"x": 122,
"y": 291
} | What color is this pants? | 2,406,750 |
{
"attributes": [
"white"
],
"h": 11,
"names": [
"letter"
],
"object_id": 319677,
"synsets": [
"letter.n.01"
],
"w": 14,
"x": 204,
"y": 219
} | {
"ans": "white",
"x": 211,
"y": 224
} | What color is this letter? | 2,410,850 |
{
"attributes": [
"white"
],
"h": 13,
"names": [
"letter"
],
"object_id": 319676,
"synsets": [
"letter.n.01"
],
"w": 11,
"x": 321,
"y": 215
} | {
"ans": "white",
"x": 326,
"y": 221
} | What color is this letter? | 2,410,850 |
{
"attributes": [
"black"
],
"h": 8,
"names": [
"letter"
],
"object_id": 319680,
"synsets": [
"letter.n.01"
],
"w": 8,
"x": 49,
"y": 204
} | {
"ans": "black",
"x": 53,
"y": 208
} | What color is this letter? | 2,410,850 |
{
"attributes": [
"black"
],
"h": 8,
"names": [
"letter"
],
"object_id": 319679,
"synsets": [
"letter.n.01"
],
"w": 6,
"x": 38,
"y": 203
} | {
"ans": "black",
"x": 41,
"y": 207
} | What color is this letter? | 2,410,850 |
{
"attributes": [
"white",
"huge",
"long",
"low"
],
"h": 73,
"names": [
"building"
],
"object_id": 319674,
"synsets": [
"building.n.01"
],
"w": 496,
"x": 1,
"y": 58
} | {
"ans": "white",
"x": 249,
"y": 94
} | What color is this building? | 2,410,850 |
{
"attributes": [
"brown"
],
"h": 34,
"names": [
"building"
],
"object_id": 319683,
"synsets": [
"building.n.01"
],
"w": 110,
"x": 232,
"y": 39
} | {
"ans": "brown",
"x": 287,
"y": 56
} | What color is this building? | 2,410,850 |
{
"attributes": [
"black"
],
"h": 187,
"names": [
"ram"
],
"object_id": 2957754,
"synsets": [
"random-access_memory.n.01"
],
"w": 82,
"x": 224,
"y": 28
} | {
"ans": "black",
"x": 265,
"y": 121
} | What color is this ram? | 2,322,459 |
{
"attributes": [
"brown"
],
"h": 238,
"names": [
"ram"
],
"object_id": 3476994,
"synsets": [
"random-access_memory.n.01"
],
"w": 212,
"x": 161,
"y": 130
} | {
"ans": "brown",
"x": 267,
"y": 249
} | What color is this ram? | 2,322,459 |
{
"attributes": [
"white"
],
"h": 117,
"names": [
"marking"
],
"object_id": 2957755,
"synsets": [
"marker.n.02"
],
"w": 28,
"x": 244,
"y": 30
} | {
"ans": "white",
"x": 258,
"y": 88
} | What color is this marking? | 2,322,459 |
{
"attributes": [
"black"
],
"h": 76,
"names": [
"marking"
],
"object_id": 3554784,
"synsets": [
"marker.n.02"
],
"w": 43,
"x": 250,
"y": 219
} | {
"ans": "black",
"x": 271,
"y": 257
} | What color is this marking? | 2,322,459 |
{
"attributes": [
"white"
],
"h": 31,
"names": [
"helmet"
],
"object_id": 312223,
"synsets": [
"helmet.n.02"
],
"w": 39,
"x": 125,
"y": 131
} | {
"ans": "white",
"x": 144,
"y": 146
} | What color is this helmet? | 2,411,415 |
{
"attributes": [
"black"
],
"h": 27,
"names": [
"helmet"
],
"object_id": 312238,
"synsets": [
"helmet.n.02"
],
"w": 39,
"x": 73,
"y": 106
} | {
"ans": "black",
"x": 92,
"y": 119
} | What color is this helmet? | 2,411,415 |
{
"attributes": [
"red"
],
"h": 71,
"names": [
"shirt"
],
"object_id": 1033252,
"synsets": [
"shirt.n.01"
],
"w": 37,
"x": 486,
"y": 285
} | {
"ans": "red",
"x": 504,
"y": 320
} | What color is this shirt? | 1,769 |
{
"attributes": [
"white"
],
"h": 44,
"names": [
"shirt"
],
"object_id": 1033262,
"synsets": [
"shirt.n.01"
],
"w": 31,
"x": 570,
"y": 293
} | {
"ans": "white",
"x": 585,
"y": 315
} | What color is this shirt? | 1,769 |
{
"attributes": [
"orange"
],
"h": 72,
"names": [
"shirt"
],
"object_id": 1033255,
"synsets": [
"shirt.n.01"
],
"w": 50,
"x": 626,
"y": 276
} | {
"ans": "orange",
"x": 651,
"y": 312
} | What color is this shirt? | 1,769 |
{
"attributes": [
"large",
"white"
],
"h": 105,
"names": [
"apple"
],
"object_id": 3490028,
"synsets": [
"apple.n.01"
],
"w": 105,
"x": 392,
"y": 177
} | {
"ans": "white",
"x": 444,
"y": 229
} | What color is this apple? | 2,416,562 |
{
"attributes": [
"white"
],
"h": 81,
"names": [
"apple"
],
"object_id": 2818958,
"synsets": [
"apple.n.01"
],
"w": 84,
"x": 202,
"y": 82
} | {
"ans": "white",
"x": 244,
"y": 122
} | What color is this apple? | 2,416,562 |
{
"attributes": [
"green"
],
"h": 74,
"names": [
"apple"
],
"object_id": 2801822,
"synsets": [
"apple.n.01"
],
"w": 75,
"x": 266,
"y": 0
} | {
"ans": "green",
"x": 303,
"y": 37
} | What color is this apple? | 2,416,562 |
{
"attributes": [
"white"
],
"h": 60,
"names": [
"apple"
],
"object_id": 2818957,
"synsets": [
"apple.n.01"
],
"w": 72,
"x": 206,
"y": 24
} | {
"ans": "white",
"x": 242,
"y": 54
} | What color is this apple? | 2,416,562 |
{
"attributes": [
"white"
],
"h": 24,
"names": [
"pipe"
],
"object_id": 4294331,
"synsets": [],
"w": 72,
"x": 370,
"y": 84
} | {
"ans": "white",
"x": 406,
"y": 96
} | What color is this pipe? | 2,400,079 |
{
"attributes": [
"yellow"
],
"h": 20,
"names": [
"pipe"
],
"object_id": 4294383,
"synsets": [],
"w": 114,
"x": 4,
"y": 118
} | {
"ans": "yellow",
"x": 61,
"y": 128
} | What color is this pipe? | 2,400,079 |
{
"attributes": [
"blue"
],
"h": 47,
"names": [
"sign"
],
"object_id": 4294388,
"synsets": [],
"w": 34,
"x": 464,
"y": 325
} | {
"ans": "blue",
"x": 481,
"y": 348
} | What color is this sign? | 2,400,079 |
{
"attributes": [
"black"
],
"h": 44,
"names": [
"sign"
],
"object_id": 4067948,
"synsets": [],
"w": 200,
"x": 153,
"y": 280
} | {
"ans": "black",
"x": 253,
"y": 302
} | What color is this sign? | 2,400,079 |
{
"attributes": [
"white"
],
"h": 16,
"names": [
"circle"
],
"object_id": 4294382,
"synsets": [],
"w": 16,
"x": 355,
"y": 338
} | {
"ans": "white",
"x": 363,
"y": 346
} | What color is this circle? | 2,400,079 |
{
"attributes": [
"blue"
],
"h": 14,
"names": [
"circle"
],
"object_id": 4294380,
"synsets": [],
"w": 12,
"x": 368,
"y": 340
} | {
"ans": "blue",
"x": 374,
"y": 347
} | What color is this circle? | 2,400,079 |
{
"attributes": [
"purple"
],
"h": 30,
"names": [
"feather"
],
"object_id": 457825,
"synsets": [
"feather.n.01"
],
"w": 13,
"x": 249,
"y": 217
} | {
"ans": "purple",
"x": 255,
"y": 232
} | What color is this feather? | 2,395,105 |
{
"attributes": [
"light green",
"black"
],
"h": 26,
"names": [
"feather"
],
"object_id": 457824,
"synsets": [
"feather.n.01"
],
"w": 17,
"x": 202,
"y": 203
} | {
"ans": "black",
"x": 210,
"y": 216
} | What color is this feather? | 2,395,105 |
{
"attributes": [
"green",
"rectangular"
],
"h": 125,
"names": [
"sign"
],
"object_id": 2101109,
"synsets": [
"sign.n.02"
],
"w": 178,
"x": 216,
"y": 38
} | {
"ans": "green",
"x": 305,
"y": 100
} | What color is this sign? | 2,358,930 |
{
"attributes": [
"yellow"
],
"h": 36,
"names": [
"sign"
],
"object_id": 1788987,
"synsets": [
"sign.n.02"
],
"w": 17,
"x": 81,
"y": 301
} | {
"ans": "yellow",
"x": 89,
"y": 319
} | What color is this sign? | 2,358,930 |
{
"attributes": [
"purple",
"violet"
],
"h": 71,
"names": [
"flowers",
"hyssops"
],
"object_id": 856917,
"synsets": [
"flower.n.01"
],
"w": 53,
"x": 348,
"y": 178
} | {
"ans": "purple",
"x": 374,
"y": 213
} | What color is this flowers? | 2,351,976 |
{
"attributes": [
"fuchsia",
"red"
],
"h": 104,
"names": [
"flowers",
"roses"
],
"object_id": 856915,
"synsets": [
"flower.n.01"
],
"w": 69,
"x": 2,
"y": 225
} | {
"ans": "red",
"x": 36,
"y": 277
} | What color is this flowers? | 2,351,976 |
{
"attributes": [
"blue"
],
"h": 65,
"names": [
"pillow"
],
"object_id": 4456190,
"synsets": [],
"w": 141,
"x": 258,
"y": 496
} | {
"ans": "blue",
"x": 328,
"y": 528
} | What color is this pillow? | 1,592,933 |
{
"attributes": [
"orange"
],
"h": 81,
"names": [
"pillow"
],
"object_id": 4456192,
"synsets": [],
"w": 161,
"x": 29,
"y": 459
} | {
"ans": "orange",
"x": 109,
"y": 499
} | What color is this pillow? | 1,592,933 |
{
"attributes": [
"gray"
],
"h": 140,
"names": [
"shirts"
],
"object_id": 1557129,
"synsets": [
"shirt.n.01"
],
"w": 10,
"x": 164,
"y": 211
} | {
"ans": "gray",
"x": 169,
"y": 281
} | What color is this shirts? | 4,171 |
{
"attributes": [
"gray"
],
"h": 133,
"names": [
"shirts"
],
"object_id": 1557126,
"synsets": [
"shirt.n.01"
],
"w": 26,
"x": 237,
"y": 203
} | {
"ans": "gray",
"x": 250,
"y": 269
} | What color is this shirts? | 4,171 |
{
"attributes": [
"gray"
],
"h": 142,
"names": [
"shirts"
],
"object_id": 1557128,
"synsets": [
"shirt.n.01"
],
"w": 25,
"x": 178,
"y": 206
} | {
"ans": "gray",
"x": 190,
"y": 277
} | What color is this shirts? | 4,171 |
{
"attributes": [
"black"
],
"h": 144,
"names": [
"shirts"
],
"object_id": 1557134,
"synsets": [
"shirt.n.01"
],
"w": 18,
"x": 42,
"y": 194
} | {
"ans": "black",
"x": 51,
"y": 266
} | What color is this shirts? | 4,171 |
{
"attributes": [
"gray"
],
"h": 139,
"names": [
"shirts"
],
"object_id": 1557127,
"synsets": [
"shirt.n.01"
],
"w": 25,
"x": 217,
"y": 205
} | {
"ans": "gray",
"x": 229,
"y": 274
} | What color is this shirts? | 4,171 |
{
"attributes": [
"yellow"
],
"h": 139,
"names": [
"shirts"
],
"object_id": 1557140,
"synsets": [
"shirt.n.01"
],
"w": 6,
"x": 97,
"y": 201
} | {
"ans": "yellow",
"x": 100,
"y": 270
} | What color is this shirts? | 4,171 |
{
"attributes": [
"paper",
"green"
],
"h": 69,
"names": [
"lantern"
],
"object_id": 2132103,
"synsets": [
"lantern.n.01"
],
"w": 170,
"x": 262,
"y": 3
} | {
"ans": "green",
"x": 347,
"y": 37
} | What color is this lantern? | 2,360,974 |
{
"attributes": [
"paper",
"white"
],
"h": 12,
"names": [
"lantern"
],
"object_id": 2112250,
"synsets": [
"lantern.n.01"
],
"w": 16,
"x": 326,
"y": 83
} | {
"ans": "white",
"x": 334,
"y": 89
} | What color is this lantern? | 2,360,974 |
{
"attributes": [
"white"
],
"h": 17,
"names": [
"spots"
],
"object_id": 1908066,
"synsets": [
"topographic_point.n.01"
],
"w": 13,
"x": 186,
"y": 192
} | {
"ans": "white",
"x": 192,
"y": 200
} | What color is this spots? | 2,373,686 |
{
"attributes": [
"brown"
],
"h": 27,
"names": [
"spots"
],
"object_id": 1908067,
"synsets": [
"topographic_point.n.01"
],
"w": 13,
"x": 145,
"y": 228
} | {
"ans": "brown",
"x": 151,
"y": 241
} | What color is this spots? | 2,373,686 |
{
"attributes": [
"green",
"parked"
],
"h": 71,
"names": [
"car"
],
"object_id": 1155976,
"synsets": [
"car.n.01"
],
"w": 211,
"x": 99,
"y": 185
} | {
"ans": "green",
"x": 204,
"y": 220
} | What color is this car? | 2,400,683 |
{
"attributes": [
"red"
],
"h": 39,
"names": [
"car"
],
"object_id": 1155998,
"synsets": [
"car.n.01"
],
"w": 134,
"x": 178,
"y": 170
} | {
"ans": "red",
"x": 245,
"y": 189
} | What color is this car? | 2,400,683 |
{
"attributes": [
"white"
],
"h": 132,
"names": [
"collar"
],
"object_id": 3224799,
"synsets": [
"collar.n.01"
],
"w": 233,
"x": 20,
"y": 235
} | {
"ans": "white",
"x": 136,
"y": 301
} | What color is this collar? | 2,334,375 |
{
"attributes": [
"brown"
],
"h": 64,
"names": [
"collar"
],
"object_id": 3411986,
"synsets": [
"collar.n.01"
],
"w": 91,
"x": 65,
"y": 257
} | {
"ans": "brown",
"x": 110,
"y": 289
} | What color is this collar? | 2,334,375 |
{
"attributes": [
"large",
"yellow"
],
"h": 259,
"names": [
"tree"
],
"object_id": 823167,
"synsets": [
"tree.n.01"
],
"w": 465,
"x": 3,
"y": 4
} | {
"ans": "yellow",
"x": 235,
"y": 133
} | What color is this tree? | 2,356,133 |
{
"attributes": [
"red"
],
"h": 19,
"names": [
"tree"
],
"object_id": 823178,
"synsets": [
"tree.n.01"
],
"w": 19,
"x": 364,
"y": 203
} | {
"ans": "red",
"x": 373,
"y": 212
} | What color is this tree? | 2,356,133 |
{
"attributes": [
"yellow"
],
"h": 24,
"names": [
"tree"
],
"object_id": 823171,
"synsets": [
"tree.n.01"
],
"w": 36,
"x": 287,
"y": 176
} | {
"ans": "yellow",
"x": 305,
"y": 188
} | What color is this tree? | 2,356,133 |
{
"attributes": [
"small",
"red",
"motorized"
],
"h": 65,
"names": [
"bike"
],
"object_id": 4205720,
"synsets": [],
"w": 50,
"x": 341,
"y": 146
} | {
"ans": "red",
"x": 366,
"y": 178
} | What color is this bike? | 2,321,296 |
{
"attributes": [
"blue"
],
"h": 127,
"names": [
"bike"
],
"object_id": 4205708,
"synsets": [],
"w": 207,
"x": 155,
"y": 149
} | {
"ans": "blue",
"x": 258,
"y": 212
} | What color is this bike? | 2,321,296 |
{
"attributes": [
"black"
],
"h": 5,
"names": [
"roof"
],
"object_id": 3763178,
"synsets": [
"roof.n.01"
],
"w": 30,
"x": 463,
"y": 127
} | {
"ans": "black",
"x": 478,
"y": 129
} | What color is this roof? | 2,359,999 |
{
"attributes": [
"red"
],
"h": 10,
"names": [
"roof"
],
"object_id": 3763176,
"synsets": [
"roof.n.01"
],
"w": 29,
"x": 279,
"y": 103
} | {
"ans": "red",
"x": 293,
"y": 108
} | What color is this roof? | 2,359,999 |
{
"attributes": [
"white"
],
"h": 35,
"names": [
"pants"
],
"object_id": 1354100,
"synsets": [
"trouser.n.01"
],
"w": 25,
"x": 217,
"y": 153
} | {
"ans": "white",
"x": 229,
"y": 170
} | What color is this pants? | 2,379,808 |
{
"attributes": [
"brown"
],
"h": 26,
"names": [
"pants"
],
"object_id": 1354093,
"synsets": [
"trouser.n.01"
],
"w": 14,
"x": 301,
"y": 106
} | {
"ans": "brown",
"x": 308,
"y": 119
} | What color is this pants? | 2,379,808 |
{
"attributes": [
"black"
],
"h": 10,
"names": [
"helmet"
],
"object_id": 1354098,
"synsets": [
"helmet.n.02"
],
"w": 15,
"x": 217,
"y": 112
} | {
"ans": "black",
"x": 224,
"y": 117
} | What color is this helmet? | 2,379,808 |
{
"attributes": [
"red"
],
"h": 9,
"names": [
"helmet"
],
"object_id": 1354094,
"synsets": [
"helmet.n.02"
],
"w": 9,
"x": 336,
"y": 99
} | {
"ans": "red",
"x": 340,
"y": 103
} | What color is this helmet? | 2,379,808 |
{
"attributes": [
"black"
],
"h": 51,
"names": [
"shirt"
],
"object_id": 913321,
"synsets": [
"shirt.n.01"
],
"w": 55,
"x": 220,
"y": 200
} | {
"ans": "black",
"x": 247,
"y": 225
} | What color is this shirt? | 2,344,758 |
{
"attributes": [
"white"
],
"h": 58,
"names": [
"shirt"
],
"object_id": 913320,
"synsets": [
"shirt.n.01"
],
"w": 55,
"x": 343,
"y": 200
} | {
"ans": "white",
"x": 370,
"y": 229
} | What color is this shirt? | 2,344,758 |
{
"attributes": [
"18",
"white"
],
"h": 28,
"names": [
"number",
"18"
],
"object_id": 913325,
"synsets": [
"numeral.n.01"
],
"w": 23,
"x": 231,
"y": 212
} | {
"ans": "white",
"x": 242,
"y": 226
} | What color is this number? | 2,344,758 |
{
"attributes": [
"11",
"red"
],
"h": 24,
"names": [
"number",
"11"
],
"object_id": 913326,
"synsets": [
"numeral.n.01"
],
"w": 25,
"x": 354,
"y": 207
} | {
"ans": "red",
"x": 366,
"y": 219
} | What color is this number? | 2,344,758 |
{
"attributes": [
"white"
],
"h": 17,
"names": [
"circles"
],
"object_id": 2200505,
"synsets": [
"circle.n.01"
],
"w": 12,
"x": 227,
"y": 217
} | {
"ans": "white",
"x": 233,
"y": 225
} | What color is this circles? | 2,342,295 |
{
"attributes": [
"green"
],
"h": 55,
"names": [
"circles"
],
"object_id": 3493668,
"synsets": [
"circle.n.01"
],
"w": 67,
"x": 139,
"y": 241
} | {
"ans": "green",
"x": 172,
"y": 268
} | What color is this circles? | 2,342,295 |
{
"attributes": [
"purple"
],
"h": 62,
"names": [
"kite"
],
"object_id": 2375180,
"synsets": [
"kite.n.03"
],
"w": 96,
"x": 173,
"y": 232
} | {
"ans": "purple",
"x": 221,
"y": 263
} | What color is this kite? | 2,359,605 |
{
"attributes": [
"blue"
],
"h": 23,
"names": [
"kite"
],
"object_id": 1902597,
"synsets": [
"kite.n.03"
],
"w": 51,
"x": 177,
"y": 227
} | {
"ans": "blue",
"x": 202,
"y": 238
} | What color is this kite? | 2,359,605 |
{
"attributes": [
"red"
],
"h": 22,
"names": [
"kite"
],
"object_id": 2096781,
"synsets": [
"kite.n.03"
],
"w": 46,
"x": 203,
"y": 249
} | {
"ans": "red",
"x": 226,
"y": 260
} | What color is this kite? | 2,359,605 |
{
"attributes": [
"white"
],
"h": 86,
"names": [
"shirt"
],
"object_id": 4029262,
"synsets": [],
"w": 82,
"x": 37,
"y": 131
} | {
"ans": "white",
"x": 78,
"y": 174
} | What color is this shirt? | 2,324,695 |
{
"attributes": [
"white"
],
"h": 129,
"names": [
"shirt"
],
"object_id": 4029300,
"synsets": [],
"w": 143,
"x": 345,
"y": 14
} | {
"ans": "white",
"x": 416,
"y": 78
} | What color is this shirt? | 2,324,695 |
{
"attributes": [
"black"
],
"h": 193,
"names": [
"shirt"
],
"object_id": 4029299,
"synsets": [],
"w": 212,
"x": 170,
"y": 116
} | {
"ans": "black",
"x": 276,
"y": 212
} | What color is this shirt? | 2,324,695 |
{
"attributes": [
"red"
],
"h": 331,
"names": [
"shirt"
],
"object_id": 4409302,
"synsets": [],
"w": 376,
"x": 645,
"y": 188
} | {
"ans": "red",
"x": 833,
"y": 353
} | What color is this shirt? | 285,929 |
{
"attributes": [
"blue"
],
"h": 305,
"names": [
"shirt"
],
"object_id": 3982130,
"synsets": [],
"w": 338,
"x": 64,
"y": 258
} | {
"ans": "blue",
"x": 233,
"y": 410
} | What color is this shirt? | 285,929 |
{
"attributes": [
"pink"
],
"h": 139,
"names": [
"wall"
],
"object_id": 4110881,
"synsets": [],
"w": 73,
"x": 376,
"y": 65
} | {
"ans": "pink",
"x": 412,
"y": 134
} | What color is this wall? | 2,335,139 |
{
"attributes": [
"white"
],
"h": 161,
"names": [
"wall"
],
"object_id": 4628598,
"synsets": [],
"w": 199,
"x": 119,
"y": 54
} | {
"ans": "white",
"x": 218,
"y": 134
} | What color is this wall? | 2,335,139 |
{
"attributes": [
"fuchsia",
"pink"
],
"h": 120,
"names": [
"couch"
],
"object_id": 4635434,
"synsets": [],
"w": 194,
"x": 304,
"y": 206
} | {
"ans": "pink",
"x": 401,
"y": 266
} | What color is this couch? | 2,335,139 |
{
"attributes": [
"gray"
],
"h": 59,
"names": [
"couch"
],
"object_id": 4635470,
"synsets": [],
"w": 93,
"x": 185,
"y": 172
} | {
"ans": "gray",
"x": 231,
"y": 201
} | What color is this couch? | 2,335,139 |
{
"attributes": [
"gray"
],
"h": 39,
"names": [
"couch"
],
"object_id": 4635472,
"synsets": [],
"w": 43,
"x": 279,
"y": 185
} | {
"ans": "gray",
"x": 300,
"y": 204
} | What color is this couch? | 2,335,139 |
{
"attributes": [
"yellow"
],
"h": 63,
"names": [
"sign"
],
"object_id": 1034660,
"synsets": [
"sign.n.02"
],
"w": 85,
"x": 18,
"y": 262
} | {
"ans": "yellow",
"x": 60,
"y": 293
} | What color is this sign? | 2,752 |
{
"attributes": [
"white"
],
"h": 34,
"names": [
"sign"
],
"object_id": 1034658,
"synsets": [
"sign.n.02"
],
"w": 34,
"x": 591,
"y": 267
} | {
"ans": "white",
"x": 608,
"y": 284
} | What color is this sign? | 2,752 |
{
"attributes": [
"black",
"leather"
],
"h": 199,
"names": [
"chair"
],
"object_id": 4457266,
"synsets": [],
"w": 180,
"x": 627,
"y": 179
} | {
"ans": "black",
"x": 717,
"y": 278
} | What color is this chair? | 1,592,983 |
{
"attributes": [
"brown"
],
"h": 327,
"names": [
"chair"
],
"object_id": 4457280,
"synsets": [],
"w": 225,
"x": 723,
"y": 338
} | {
"ans": "brown",
"x": 835,
"y": 501
} | What color is this chair? | 1,592,983 |
{
"attributes": [
"yellow"
],
"h": 65,
"names": [
"pillow"
],
"object_id": 4457254,
"synsets": [],
"w": 96,
"x": 260,
"y": 140
} | {
"ans": "yellow",
"x": 308,
"y": 172
} | What color is this pillow? | 1,592,983 |
{
"attributes": [
"white"
],
"h": 46,
"names": [
"pillow"
],
"object_id": 4457260,
"synsets": [],
"w": 119,
"x": 433,
"y": 282
} | {
"ans": "white",
"x": 492,
"y": 305
} | What color is this pillow? | 1,592,983 |
{
"attributes": [
"black"
],
"h": 17,
"names": [
"letter"
],
"object_id": 4685638,
"synsets": [],
"w": 46,
"x": 208,
"y": 106
} | {
"ans": "black",
"x": 231,
"y": 114
} | What color is this letter? | 2,340,332 |
{
"attributes": [
"black"
],
"h": 24,
"names": [
"letter"
],
"object_id": 4685636,
"synsets": [],
"w": 26,
"x": 181,
"y": 69
} | {
"ans": "black",
"x": 194,
"y": 81
} | What color is this letter? | 2,340,332 |
{
"attributes": [
"black"
],
"h": 13,
"names": [
"letter"
],
"object_id": 4685639,
"synsets": [],
"w": 33,
"x": 183,
"y": 66
} | {
"ans": "black",
"x": 199,
"y": 72
} | What color is this letter? | 2,340,332 |
{
"attributes": [
"red"
],
"h": 65,
"names": [
"letter"
],
"object_id": 4685640,
"synsets": [],
"w": 43,
"x": 274,
"y": 65
} | {
"ans": "red",
"x": 295,
"y": 97
} | What color is this letter? | 2,340,332 |
{
"attributes": [
"black"
],
"h": 20,
"names": [
"letter"
],
"object_id": 4685634,
"synsets": [],
"w": 19,
"x": 217,
"y": 103
} | {
"ans": "black",
"x": 226,
"y": 113
} | What color is this letter? | 2,340,332 |
{
"attributes": [
"blue"
],
"h": 65,
"names": [
"shirt"
],
"object_id": 4685623,
"synsets": [],
"w": 57,
"x": 46,
"y": 128
} | {
"ans": "blue",
"x": 74,
"y": 160
} | What color is this shirt? | 2,340,332 |
{
"attributes": [
"white"
],
"h": 19,
"names": [
"shirt"
],
"object_id": 4685661,
"synsets": [],
"w": 36,
"x": 448,
"y": 101
} | {
"ans": "white",
"x": 466,
"y": 110
} | What color is this shirt? | 2,340,332 |
{
"attributes": [
"white"
],
"h": 60,
"names": [
"shirt"
],
"object_id": 1183218,
"synsets": [
"shirt.n.01"
],
"w": 72,
"x": 125,
"y": 125
} | {
"ans": "white",
"x": 161,
"y": 155
} | What color is this shirt? | 2,398,066 |
{
"attributes": [
"black"
],
"h": 61,
"names": [
"shirt"
],
"object_id": 1183234,
"synsets": [
"shirt.n.01"
],
"w": 64,
"x": 388,
"y": 132
} | {
"ans": "black",
"x": 420,
"y": 162
} | What color is this shirt? | 2,398,066 |
End of preview.