Datasets:
Tasks:
Visual Question Answering
Sub-tasks:
visual-question-answering
Languages:
English
Multilinguality:
monolingual
Size Categories:
100K<n<1M
Language Creators:
found
Annotations Creators:
machine-generated
Source Datasets:
extended|other-guesswhat
License:
unknown
id
int32
2.45k
224k
| target_id
int32
144
2.23M
| timestamp
string
| status
string
| image
dict
| qas
sequence
| objects
sequence
|
|---|---|---|---|---|---|---|
2,447 | 1,641,241 | "2016-07-08 15:10:17" | "success" | {
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"height": 400,
"width": 500,
"visual_genome": {
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"height": 400,
"url": "https://cs.stanford.edu/people/rak248/VG_100K/2318324.jpg",
"coco_id": 157190,
"flickr_id": "2171007168",
"image_id": "2318324"
}
} | {
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"is it on the back coutertop?",
"is it on the island?",
"is it on the walls?",
"is it in the cabinets?",
"is it a human?",
"is it on the windowsill?",
"is it an appliance?",
"does it cook things?"
],
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} |
2,451 | 657,159 | "2016-07-08 15:10:32" | "success" | {
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} |
2,463 | 2,108,588 | "2016-07-08 15:11:26" | "success" | {
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}
} | {
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],
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} | {
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306.17,
373.49,
312.23
]
]
]
} |
2,802 | 1,169,010 | "2016-07-08 15:40:04" | "success" | {
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"flickr_url": "http://farm5.staticflickr.com/4073/5442407465_f8b46bb466_z.jpg",
"coco_url": "http://mscoco.org/images/127702",
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"width": 640,
"visual_genome": {
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"height": 375,
"url": "https://cs.stanford.edu/people/rak248/VG_100K/2340381.jpg",
"coco_id": 127702,
"flickr_id": "5442407465",
"image_id": "2340381"
}
} | {
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"Is it a backpack?"
],
"answer": [
"Yes",
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"id": [
6419,
6427,
6437
]
} | {
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263.17,
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261.35,
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261.51,
257.2,
259.52,
257.37
]
]
]
} |
2,831 | 1,457,122 | "2016-07-08 15:42:28" | "success" | {
"id": 248953,
"file_name": "COCO_val2014_000000248953.jpg",
"flickr_url": "http://farm5.staticflickr.com/4045/4204628838_58b04494e7_z.jpg",
"coco_url": "http://mscoco.org/images/248953",
"height": 375,
"width": 500,
"visual_genome": {
"width": 500,
"height": 375,
"url": "https://cs.stanford.edu/people/rak248/VG_100K_2/2401674.jpg",
"coco_id": 248953,
"flickr_id": "4204628838",
"image_id": "2401674"
}
} | {
"question": [
"Is it a person?",
"Is it white?",
"Is it an object?"
],
"answer": [
"No",
"Yes",
"Yes"
],
"id": [
6505,
6521,
6528
]
} | {
"id": [
524942,
526226,
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277.03,
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238.36,
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],
"category": [
"person",
"person",
"person",
"snowboard"
],
"area": [
380.49599999999975,
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1,
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} |
Dataset Card for "compguesswhat"
Dataset Summary
CompGuessWhat?! is an instance of a multi-task framework for evaluating the quality of learned neural representations,
in particular concerning attribute grounding. Use this dataset if you want to use the set of games whose reference
scene is an image in VisualGenome. Visit the website for more details: https://compguesswhat.github.io
Supported Tasks and Leaderboards
Languages
Dataset Structure
Data Instances
compguesswhat-original
- Size of downloaded dataset files: 107.21 MB
- Size of the generated dataset: 174.37 MB
- Total amount of disk used: 281.57 MB
An example of 'validation' looks as follows.
This example was too long and was cropped:
{
"id": 2424,
"image": "{\"coco_url\": \"http://mscoco.org/images/270512\", \"file_name\": \"COCO_train2014_000000270512.jpg\", \"flickr_url\": \"http://farm6.stat...",
"objects": "{\"area\": [1723.5133056640625, 4838.5361328125, 287.44476318359375, 44918.7109375, 3688.09375, 522.1935424804688], \"bbox\": [[5.61...",
"qas": {
"answer": ["Yes", "No", "No", "Yes"],
"id": [4983, 4996, 5006, 5017],
"question": ["Is it in the foreground?", "Does it have wings?", "Is it a person?", "Is it a vehicle?"]
},
"status": "success",
"target_id": 1197044,
"timestamp": "2016-07-08 15:07:38"
}
compguesswhat-zero_shot
- Size of downloaded dataset files: 4.84 MB
- Size of the generated dataset: 96.74 MB
- Total amount of disk used: 101.59 MB
An example of 'nd_valid' looks as follows.
This example was too long and was cropped:
{
"id": 0,
"image": {
"coco_url": "https://s3.amazonaws.com/nocaps/val/004e21eb2e686f40.jpg",
"date_captured": "2018-11-06 11:04:33",
"file_name": "004e21eb2e686f40.jpg",
"height": 1024,
"id": 6,
"license": 0,
"open_images_id": "004e21eb2e686f40",
"width": 768
},
"objects": "{\"IsOccluded\": [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], \"IsTruncated\": [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], \"area\": [3...",
"status": "incomplete",
"target_id": "004e21eb2e686f40_30"
}
Data Fields
The data fields are the same among all splits.
compguesswhat-original
id: aint32feature.target_id: aint32feature.timestamp: astringfeature.status: astringfeature.id: aint32feature.file_name: astringfeature.flickr_url: astringfeature.coco_url: astringfeature.height: aint32feature.width: aint32feature.width: aint32feature.height: aint32feature.url: astringfeature.coco_id: aint32feature.flickr_id: astringfeature.image_id: astringfeature.qas: a dictionary feature containing:question: astringfeature.answer: astringfeature.id: aint32feature.
objects: a dictionary feature containing:id: aint32feature.bbox: alistoffloat32features.category: astringfeature.area: afloat32feature.category_id: aint32feature.segment: a dictionary feature containing:feature: afloat32feature.
compguesswhat-zero_shot
id: aint32feature.target_id: astringfeature.status: astringfeature.id: aint32feature.file_name: astringfeature.coco_url: astringfeature.height: aint32feature.width: aint32feature.license: aint32feature.open_images_id: astringfeature.date_captured: astringfeature.objects: a dictionary feature containing:id: astringfeature.bbox: alistoffloat32features.category: astringfeature.area: afloat32feature.category_id: aint32feature.IsOccluded: aint32feature.IsTruncated: aint32feature.segment: a dictionary feature containing:MaskPath: astringfeature.LabelName: astringfeature.BoxID: astringfeature.BoxXMin: astringfeature.BoxXMax: astringfeature.BoxYMin: astringfeature.BoxYMax: astringfeature.PredictedIoU: astringfeature.Clicks: astringfeature.
Data Splits
compguesswhat-original
| train | validation | test | |
|---|---|---|---|
| compguesswhat-original | 46341 | 9738 | 9621 |
compguesswhat-zero_shot
| nd_valid | od_valid | nd_test | od_test | |
|---|---|---|---|---|
| compguesswhat-zero_shot | 5343 | 5372 | 13836 | 13300 |
Dataset Creation
Curation Rationale
Source Data
Initial Data Collection and Normalization
Who are the source language producers?
Annotations
Annotation process
Who are the annotators?
Personal and Sensitive Information
Considerations for Using the Data
Social Impact of Dataset
Discussion of Biases
Other Known Limitations
Additional Information
Dataset Curators
Licensing Information
Citation Information
@inproceedings{suglia2020compguesswhat,
title={CompGuessWhat?!: a Multi-task Evaluation Framework for Grounded Language Learning},
author={Suglia, Alessandro, Konstas, Ioannis, Vanzo, Andrea, Bastianelli, Emanuele, Desmond Elliott, Stella Frank and Oliver Lemon},
booktitle={Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics},
year={2020}
}
Contributions
Thanks to @thomwolf, @aleSuglia, @lhoestq for adding this dataset.
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