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The dataset generation failed
Error code: DatasetGenerationError
Exception: CastError
Message: 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
image: string
sample_id: string
sample_b: struct<ann_id: int64, bbox_xywh: list<item: double>, bbox_xyxy: list<item: double>, caption_quality: (... 270 chars omitted)
child 0, ann_id: int64
child 1, bbox_xywh: list<item: double>
child 0, item: double
child 2, bbox_xyxy: list<item: double>
child 0, item: double
child 3, caption_quality: null
child 4, category_id: int64
child 5, category_name: string
child 6, expression_en: string
child 7, expression_vi: null
child 8, file_name: string
child 9, image_height: int64
child 10, image_id: int64
child 11, image_path: string
child 12, image_width: int64
child 13, sample_id: string
child 14, source_dataset: string
child 15, source_split: string
child 16, split: string
category_name: string
category_id: int64
sample_id_b: string
semantic_similarity: double
discriminative_groups: list<item: string>
child 0, item: string
hard_score: double
sample_a: struct<ann_id: int64, bbox_xywh: list<item: double>, bbox_xyxy: list<item: double>, caption_quality: (... 270 chars omitted)
child 0, ann_id: int64
child 1, bbox_xywh: list<item: double>
child 0, item: double
child 2, bbox_xyxy: list<item: double>
child 0, item: double
child 3, caption_quality: null
child 4, category_id: int64
child 5, category_name: string
child 6, expression_en: string
child 7, expression_vi: null
child 8, file_name: string
child 9, image_height: int64
child 10, image_id: int64
child 11, image_path: string
child 12, image_width: int64
child 13, sample_id: string
child 14, source_dataset: string
child 15, source_split: string
child 16, split: string
sample_id_a: string
visual_distractor_score: double
image_id: int64
ann_id_b: int64
pair_id: string
ann_id_a: int64
to
{'ann_id_a': Value('int64'), 'ann_id_b': Value('int64'), 'category_id': Value('int64'), 'category_name': Value('string'), 'discriminative_groups': List(Value('string')), 'hard_score': Value('float64'), 'image_id': Value('int64'), 'pair_id': Value('string'), 'sample_a': {'ann_id': Value('int64'), 'bbox_xywh': List(Value('float64')), 'bbox_xyxy': List(Value('float64')), 'caption_quality': Value('null'), 'category_id': Value('int64'), 'category_name': Value('string'), 'expression_en': Value('string'), 'expression_vi': Value('null'), 'file_name': Value('string'), 'image_height': Value('int64'), 'image_id': Value('int64'), 'image_path': Value('string'), 'image_width': Value('int64'), 'sample_id': Value('string'), 'source_dataset': Value('string'), 'source_split': Value('string'), 'split': Value('string')}, 'sample_b': {'ann_id': Value('int64'), 'bbox_xywh': List(Value('float64')), 'bbox_xyxy': List(Value('float64')), 'caption_quality': Value('null'), 'category_id': Value('int64'), 'category_name': Value('string'), 'expression_en': Value('string'), 'expression_vi': Value('null'), 'file_name': Value('string'), 'image_height': Value('int64'), 'image_id': Value('int64'), 'image_path': Value('string'), 'image_width': Value('int64'), 'sample_id': Value('string'), 'source_dataset': Value('string'), 'source_split': Value('string'), 'split': Value('string')}, 'sample_id_a': Value('string'), 'sample_id_b': Value('string'), 'semantic_similarity': Value('float64'), 'visual_distractor_score': Value('float64')}
because column names don't match
Traceback: Traceback (most recent call last):
File "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 1816, in _prepare_split_single
for key, table in generator:
^^^^^^^^^
File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 611, in wrapped
for item in generator(*args, **kwargs):
^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/packaged_modules/json/json.py", line 310, in _generate_tables
self._cast_table(pa_table, json_field_paths=json_field_paths),
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/packaged_modules/json/json.py", line 130, in _cast_table
pa_table = table_cast(pa_table, self.info.features.arrow_schema)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/table.py", line 2369, in table_cast
return cast_table_to_schema(table, schema)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/table.py", line 2297, 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
image: string
sample_id: string
sample_b: struct<ann_id: int64, bbox_xywh: list<item: double>, bbox_xyxy: list<item: double>, caption_quality: (... 270 chars omitted)
child 0, ann_id: int64
child 1, bbox_xywh: list<item: double>
child 0, item: double
child 2, bbox_xyxy: list<item: double>
child 0, item: double
child 3, caption_quality: null
child 4, category_id: int64
child 5, category_name: string
child 6, expression_en: string
child 7, expression_vi: null
child 8, file_name: string
child 9, image_height: int64
child 10, image_id: int64
child 11, image_path: string
child 12, image_width: int64
child 13, sample_id: string
child 14, source_dataset: string
child 15, source_split: string
child 16, split: string
category_name: string
category_id: int64
sample_id_b: string
semantic_similarity: double
discriminative_groups: list<item: string>
child 0, item: string
hard_score: double
sample_a: struct<ann_id: int64, bbox_xywh: list<item: double>, bbox_xyxy: list<item: double>, caption_quality: (... 270 chars omitted)
child 0, ann_id: int64
child 1, bbox_xywh: list<item: double>
child 0, item: double
child 2, bbox_xyxy: list<item: double>
child 0, item: double
child 3, caption_quality: null
child 4, category_id: int64
child 5, category_name: string
child 6, expression_en: string
child 7, expression_vi: null
child 8, file_name: string
child 9, image_height: int64
child 10, image_id: int64
child 11, image_path: string
child 12, image_width: int64
child 13, sample_id: string
child 14, source_dataset: string
child 15, source_split: string
child 16, split: string
sample_id_a: string
visual_distractor_score: double
image_id: int64
ann_id_b: int64
pair_id: string
ann_id_a: int64
to
{'ann_id_a': Value('int64'), 'ann_id_b': Value('int64'), 'category_id': Value('int64'), 'category_name': Value('string'), 'discriminative_groups': List(Value('string')), 'hard_score': Value('float64'), 'image_id': Value('int64'), 'pair_id': Value('string'), 'sample_a': {'ann_id': Value('int64'), 'bbox_xywh': List(Value('float64')), 'bbox_xyxy': List(Value('float64')), 'caption_quality': Value('null'), 'category_id': Value('int64'), 'category_name': Value('string'), 'expression_en': Value('string'), 'expression_vi': Value('null'), 'file_name': Value('string'), 'image_height': Value('int64'), 'image_id': Value('int64'), 'image_path': Value('string'), 'image_width': Value('int64'), 'sample_id': Value('string'), 'source_dataset': Value('string'), 'source_split': Value('string'), 'split': Value('string')}, 'sample_b': {'ann_id': Value('int64'), 'bbox_xywh': List(Value('float64')), 'bbox_xyxy': List(Value('float64')), 'caption_quality': Value('null'), 'category_id': Value('int64'), 'category_name': Value('string'), 'expression_en': Value('string'), 'expression_vi': Value('null'), 'file_name': Value('string'), 'image_height': Value('int64'), 'image_id': Value('int64'), 'image_path': Value('string'), 'image_width': Value('int64'), 'sample_id': Value('string'), 'source_dataset': Value('string'), 'source_split': Value('string'), 'split': Value('string')}, 'sample_id_a': Value('string'), 'sample_id_b': Value('string'), 'semantic_similarity': Value('float64'), 'visual_distractor_score': Value('float64')}
because column names don't match
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 1361, 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 940, in stream_convert_to_parquet
builder._prepare_split(split_generator=splits_generators[split], file_format="parquet")
File "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 1683, 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 1869, in _prepare_split_single
raise DatasetGenerationError("An error occurred while generating the dataset") from e
datasets.exceptions.DatasetGenerationError: An error occurred while generating the datasetNeed help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.
ann_id_a int64 | ann_id_b int64 | category_id int64 | category_name string | discriminative_groups list | hard_score float64 | image_id int64 | pair_id string | sample_a dict | sample_b dict | sample_id_a string | sample_id_b string | semantic_similarity float64 | visual_distractor_score float64 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
1,471 | 1,447 | 58 | 58 | [
"spatial",
"ordinal"
] | 0.948623 | 569,667 | 569667_58_jxu_refcoco_train_1105_1471_3145_jxu_refcoco_train_1106_1447_3146 | {
"ann_id": 1471,
"bbox_xywh": [
110.89,
121.05,
229.17,
173.73
],
"bbox_xyxy": [
110.89,
121.05,
340.06,
294.78
],
"caption_quality": null,
"category_id": 58,
"category_name": "58",
"expression_en": "second hot dog from left",
"expression_vi": null,
"file_name": "C... | {
"ann_id": 1447,
"bbox_xywh": [
245.52,
133.98,
207.96,
191.47
],
"bbox_xyxy": [
245.52,
133.98,
453.48,
325.45
],
"caption_quality": null,
"category_id": 58,
"category_name": "58",
"expression_en": "second hot dog from right third from left",
"expression_vi": null,
... | jxu_refcoco_train_1105_1471_3145 | jxu_refcoco_train_1106_1447_3146 | 0.936387 | 0.918048 |
1,380,286 | 2,172,270 | 9 | 9 | [
"spatial",
"ordinal"
] | 0.933907 | 506,832 | 506832_9_jxu_refcoco_train_6525_1380286_18580_jxu_refcoco_train_6527_2172270_18585 | {
"ann_id": 1380286,
"bbox_xywh": [
411.64,
78.5,
188.59,
118.7
],
"bbox_xyxy": [
411.64,
78.5,
600.23,
197.2
],
"caption_quality": null,
"category_id": 9,
"category_name": "9",
"expression_en": "second row from top second boat from right",
"expression_vi": null,
"f... | {
"ann_id": 2172270,
"bbox_xywh": [
290.02,
69.6,
219,
117.54
],
"bbox_xyxy": [
290.02,
69.6,
509.02,
187.14
],
"caption_quality": null,
"category_id": 9,
"category_name": "9",
"expression_en": "second row down third boat from right",
"expression_vi": null,
"file_na... | jxu_refcoco_train_6525_1380286_18580 | jxu_refcoco_train_6527_2172270_18585 | 0.928798 | 0.865339 |
1,574,361 | 1,575,899 | 60 | 60 | [
"spatial",
"ordinal"
] | 0.933328 | 323,964 | 323964_60_jxu_refcoco_train_22373_1574361_63630_jxu_refcoco_train_22376_1575899_63637 | {
"ann_id": 1574361,
"bbox_xywh": [
169.08,
323.81,
188.55,
99.4
],
"bbox_xyxy": [
169.08,
323.81,
357.63,
423.21000000000004
],
"caption_quality": null,
"category_id": 60,
"category_name": "60",
"expression_en": "third donut from left second donut up",
"expression_vi... | {
"ann_id": 1575899,
"bbox_xywh": [
279.75,
253.11,
179.32,
94.27
],
"bbox_xyxy": [
279.75,
253.11,
459.07,
347.38
],
"caption_quality": null,
"category_id": 60,
"category_name": "60",
"expression_en": "third donut from top right",
"expression_vi": null,
"file_name"... | jxu_refcoco_train_22373_1574361_63630 | jxu_refcoco_train_22376_1575899_63637 | 0.926426 | 0.868967 |
1,576,075 | 1,574,449 | 60 | 60 | [
"spatial",
"ordinal"
] | 0.92695 | 434,771 | 434771_60_jxu_refcoco_train_12809_1576075_36450_jxu_refcoco_train_12812_1574449_36457 | {
"ann_id": 1576075,
"bbox_xywh": [
50.29,
147.64,
147.71,
91.26
],
"bbox_xyxy": [
50.29,
147.64,
198,
238.89999999999998
],
"caption_quality": null,
"category_id": 60,
"category_name": "60",
"expression_en": "first row on left middle donut in the row",
"expression_vi... | {
"ann_id": 1574449,
"bbox_xywh": [
192.17,
156.7,
147.28,
88.98
],
"bbox_xyxy": [
192.17,
156.7,
339.45,
245.68
],
"caption_quality": null,
"category_id": 60,
"category_name": "60",
"expression_en": "second row from left third donut from front",
"expression_vi": null... | jxu_refcoco_train_12809_1576075_36450 | jxu_refcoco_train_12812_1574449_36457 | 0.904488 | 0.89741 |
584,859 | 583,927 | 22 | 22 | [
"spatial",
"size"
] | 0.924423 | 334,216 | 334216_22_jxu_refcoco_train_21332_584859_60675_jxu_refcoco_train_21333_583927_60677 | {
"ann_id": 584859,
"bbox_xywh": [
332.7,
171.03,
110.47,
209.84
],
"bbox_xyxy": [
332.7,
171.03,
443.16999999999996,
380.87
],
"caption_quality": null,
"category_id": 22,
"category_name": "22",
"expression_en": "small elephant on right",
"expression_vi": null,
"fil... | {
"ann_id": 583927,
"bbox_xywh": [
109.14,
189.57,
140.74,
188.6
],
"bbox_xyxy": [
109.14,
189.57,
249.88,
378.16999999999996
],
"caption_quality": null,
"category_id": 22,
"category_name": "22",
"expression_en": "little elephant on left",
"expression_vi": null,
"fi... | jxu_refcoco_train_21332_584859_60675 | jxu_refcoco_train_21333_583927_60677 | 0.93491 | 0.80111 |
1,654,038 | 1,652,728 | 84 | 84 | [
"spatial",
"ordinal"
] | 0.921693 | 9,398 | 9398_84_jxu_refcoco_train_49238_1654038_140032_jxu_refcoco_train_49239_1652728_140034 | {
"ann_id": 1654038,
"bbox_xywh": [
264.27,
120.81,
168.27,
353.8
],
"bbox_xyxy": [
264.27,
120.81,
432.53999999999996,
474.61
],
"caption_quality": null,
"category_id": 84,
"category_name": "84",
"expression_en": "standing book second to left",
"expression_vi": null,... | {
"ann_id": 1652728,
"bbox_xywh": [
378.18,
150.79,
190.3,
323.63
],
"bbox_xyxy": [
378.18,
150.79,
568.48,
474.41999999999996
],
"caption_quality": null,
"category_id": 84,
"category_name": "84",
"expression_en": "right standing book",
"expression_vi": null,
"file_... | jxu_refcoco_train_49238_1654038_140032 | jxu_refcoco_train_49239_1652728_140034 | 0.892276 | 0.904702 |
1,544,822 | 1,541,841 | 52 | 52 | [
"spatial",
"ordinal"
] | 0.921076 | 153,618 | 153618_52_jxu_refcoco_train_36784_1544822_104619_jxu_refcoco_train_36786_1541841_104624 | {
"ann_id": 1544822,
"bbox_xywh": [
7.19,
268.94,
133.75,
215.73
],
"bbox_xyxy": [
7.19,
268.94,
140.94,
484.66999999999996
],
"caption_quality": null,
"category_id": 52,
"category_name": "52",
"expression_en": "bunch of bananas far left front",
"expression_vi": null,... | {
"ann_id": 1541841,
"bbox_xywh": [
116.49,
227,
119.38,
266.06
],
"bbox_xyxy": [
116.49,
227,
235.87,
493.06
],
"caption_quality": null,
"category_id": 52,
"category_name": "52",
"expression_en": "bunch of bananas second from left",
"expression_vi": null,
"file_nam... | jxu_refcoco_train_36784_1544822_104619 | jxu_refcoco_train_36786_1541841_104624 | 0.896669 | 0.889539 |
653,359 | 650,801 | 42 | 42 | [
"spatial",
"ordinal"
] | 0.918607 | 246,184 | 246184_42_jxu_refcoco_train_29122_653359_82822_jxu_refcoco_train_29123_650801_82823 | {
"ann_id": 653359,
"bbox_xywh": [
131.8,
0.96,
198.65,
419.26
],
"bbox_xyxy": [
131.8,
0.96,
330.45000000000005,
420.21999999999997
],
"caption_quality": null,
"category_id": 42,
"category_name": "42",
"expression_en": "middle yellow board",
"expression_vi": null,
... | {
"ann_id": 650801,
"bbox_xywh": [
29.61,
0.96,
198.65,
418.31
],
"bbox_xyxy": [
29.61,
0.96,
228.26,
419.27
],
"caption_quality": null,
"category_id": 42,
"category_name": "42",
"expression_en": "yellow board third from left",
"expression_vi": null,
"file_name": "C... | jxu_refcoco_train_29122_653359_82822 | jxu_refcoco_train_29123_650801_82823 | 0.876609 | 0.932359 |
1,497,237 | 665,092 | 46 | 46 | [
"spatial",
"ordinal"
] | 0.917882 | 153,814 | 153814_46_jxu_refcoco_train_36770_1497237_104582_jxu_refcoco_train_36772_665092_104586 | {
"ann_id": 1497237,
"bbox_xywh": [
410.4,
1.44,
161.28,
300.96
],
"bbox_xyxy": [
410.4,
1.44,
571.68,
302.4
],
"caption_quality": null,
"category_id": 46,
"category_name": "46",
"expression_en": "wine glass second from right",
"expression_vi": null,
"file_name": "C... | {
"ann_id": 665092,
"bbox_xywh": [
459.31,
33.87,
152.69,
313.96
],
"bbox_xyxy": [
459.31,
33.87,
612,
347.83
],
"caption_quality": null,
"category_id": 46,
"category_name": "46",
"expression_en": "rightmost wine glass",
"expression_vi": null,
"file_name": "COCO_tra... | jxu_refcoco_train_36770_1497237_104582 | jxu_refcoco_train_36772_665092_104586 | 0.865382 | 0.95961 |
27,833 | 25,942 | 64 | 64 | [
"spatial",
"ordinal"
] | 0.916708 | 167,042 | 167042_64_jxu_refcoco_train_35725_27833_101621_jxu_refcoco_train_35726_25942_101622 | {
"ann_id": 27833,
"bbox_xywh": [
434.07,
0,
152.81,
248.03
],
"bbox_xyxy": [
434.07,
0,
586.88,
248.03
],
"caption_quality": null,
"category_id": 64,
"category_name": "64",
"expression_en": "second pot from right",
"expression_vi": null,
"file_name": "COCO_train201... | {
"ann_id": 25942,
"bbox_xywh": [
228.48,
86.76,
154.25,
264.15
],
"bbox_xyxy": [
228.48,
86.76,
382.73,
350.90999999999997
],
"caption_quality": null,
"category_id": 64,
"category_name": "64",
"expression_en": "third pot from left",
"expression_vi": null,
"file_nam... | jxu_refcoco_train_35725_27833_101621 | jxu_refcoco_train_35726_25942_101622 | 0.914521 | 0.818605 |
1,083,228 | 1,081,832 | 60 | 60 | [
"spatial",
"color"
] | 0.913702 | 21,254 | 21254_60_jxu_refcoco_train_48207_1083228_137111_jxu_refcoco_train_48208_1081832_137113 | {
"ann_id": 1083228,
"bbox_xywh": [
161.47,
513.3,
150.26,
87.4
],
"bbox_xyxy": [
161.47,
513.3,
311.73,
600.6999999999999
],
"caption_quality": null,
"category_id": 60,
"category_name": "60",
"expression_en": "second white donut from the left bottom row",
"expression... | {
"ann_id": 1081832,
"bbox_xywh": [
310.14,
508.62,
135.08,
95.11
],
"bbox_xyxy": [
310.14,
508.62,
445.22,
603.73
],
"caption_quality": null,
"category_id": 60,
"category_name": "60",
"expression_en": "second donut from the right on the bottom row",
"expression_vi": ... | jxu_refcoco_train_48207_1083228_137111 | jxu_refcoco_train_48208_1081832_137113 | 0.876682 | 0.907636 |
1,574,449 | 1,574,224 | 60 | 60 | [
"spatial",
"ordinal"
] | 0.913694 | 434,771 | 434771_60_jxu_refcoco_train_12812_1574449_36456_jxu_refcoco_train_12813_1574224_36458 | {
"ann_id": 1574449,
"bbox_xywh": [
192.17,
156.7,
147.28,
88.98
],
"bbox_xyxy": [
192.17,
156.7,
339.45,
245.68
],
"caption_quality": null,
"category_id": 60,
"category_name": "60",
"expression_en": "second row from left third one down",
"expression_vi": null,
"fil... | {
"ann_id": 1574224,
"bbox_xywh": [
208.18,
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68,417 | 62,830 | 20 | 20 | [
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593,624 | 592,495 | 24 | 24 | [
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1,559,207 | 1,557,529 | 55 | 55 | [
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"file_name... | jxu_refcoco_train_500_1559207_1425 | jxu_refcoco_train_501_1557529_1428 | 0.830146 | 0.904903 |
1,576,134 | 1,576,081 | 60 | 60 | [
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"color"
] | 0.887021 | 286,910 | 286910_60_jxu_refcoco_train_25638_1576134_72884_jxu_refcoco_train_25639_1576081_72887 | {
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1,070,053 | 1,068,351 | 58 | 58 | [
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"file_name"... | jxu_refcoco_train_18239_1070053_51879 | jxu_refcoco_train_18240_1068351_51883 | 0.874981 | 0.777969 |
599,213 | 596,841 | 25 | 25 | [
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"expression_en": "giraffe on left little one",
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1,185,850 | 1,185,745 | 33 | 33 | [
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"color"
] | 0.886655 | 394,151 | 394151_33_jxu_refcoco_train_16291_1185850_46356_jxu_refcoco_train_16292_1185745_46358 | {
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1,161,433 | 1,159,657 | 88 | 88 | [
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1,330,395 | 2,152,680 | 1 | 1 | [
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End of preview.
ViGround-Contrast Data
Prepared data artifacts for ViGround-Contrast: hard-pair fine-tuning and fast base-model evaluation for Vietnamese referring expression grounding.
Repo: thanhhoangnvbg/viground-contrast-data
Contents
data/benchmark/standard.jsonl: fast benchmark standard rows, EN + VI.data/benchmark/hard_pairs.jsonl: fast benchmark hard-pair rows.data/train_random/train_samples.jsonl: 4,000 selected Random-FT samples.data/train_hardpair/train_samples.jsonl: 4,000 selected HardPair-FT samples.data/train_random/locateanything_train.jsonl: Random-FT LocateAnything conversation format.data/train_hardpair/locateanything_train.jsonl: HardPair-FT LocateAnything conversation format.data/processed/*: manifests, reports, lineage, and integrity output.data/translations/*: selected train and benchmark translations plus incremental cache.configs/*: data, benchmark, and training configs used to build these artifacts.
Counts
- Random-FT train samples:
4,000 - HardPair-FT train samples:
4,000 - Selected train translations:
8,000 - Fast benchmark standard rows:
2,000 - Fast benchmark hard pairs:
500 - Fast benchmark inference rows per model:
3,000 - Fast benchmark inference rows for three models:
9,000
Image Source
This dataset does not upload COCO images. All rows reference MS COCO 2014
train2014 filenames under:
data/raw/coco/train2014/
Download images from the official COCO source:
http://images.cocodataset.org/zips/train2014.zip
image_path values in uploaded JSONL are relative paths of the form
data/raw/coco/train2014/COCO_train2014_*.jpg.
Lineage
- Train annotations:
jxu124/refcoco, records withsplit=train. - Benchmark annotations:
JierunChen/Ref-L4reviewed RefCOCO val/testA/testB, filtered withcaption_quality != 0. - Vietnamese text: automatic translation from English referring expressions.
- Bounding boxes: original annotations, no manual relabeling.
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