참고자료:
추측-원본
TFDS에 이 데이터세트를 로드하려면 다음 명령어를 사용하세요.
ds = tfds.load('huggingface:compguesswhat/compguesswhat-original')
- 설명 :
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
- 라이센스 : 알려진 라이센스 없음
- 버전 : 0.2.0
- 분할 :
나뉘다 | 예 |
---|---|
'test' | 9621 |
'train' | 46341 |
'validation' | 9738 |
- 특징 :
{
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"_type": "Value"
},
"target_id": {
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"timestamp": {
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"status": {
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"image": {
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"file_name": {
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"flickr_url": {
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"visual_genome": {
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"url": {
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}
}
},
"qas": {
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"answer": {
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"objects": {
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"bbox": {
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"length": -1,
"id": null,
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}
},
"length": -1,
"id": null,
"_type": "Sequence"
}
}
compguesswhat-zero_shot
TFDS에 이 데이터세트를 로드하려면 다음 명령어를 사용하세요.
ds = tfds.load('huggingface:compguesswhat/compguesswhat-zero_shot')
- 설명 :
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
- 라이센스 : 알려진 라이센스 없음
- 버전 : 0.2.0
- 분할 :
나뉘다 | 예 |
---|---|
'nd_test' | 13836 |
'nd_valid' | 5343 |
'od_test' | 13300 |
'od_valid' | 5372 |
- 특징 :
{
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"id": null,
"_type": "Value"
},
"target_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"status": {
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},
"image": {
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},
"file_name": {
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"id": null,
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"coco_url": {
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"height": {
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"width": {
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},
"license": {
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},
"open_images_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"date_captured": {
"dtype": "string",
"id": null,
"_type": "Value"
}
},
"objects": {
"feature": {
"id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"bbox": {
"feature": {
"dtype": "float32",
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},
"length": 4,
"id": null,
"_type": "Sequence"
},
"category": {
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"area": {
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"id": null,
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},
"category_id": {
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"IsOccluded": {
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"IsTruncated": {
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"segment": {
"feature": {
"MaskPath": {
"dtype": "string",
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"LabelName": {
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"BoxID": {
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"BoxXMin": {
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},
"BoxXMax": {
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},
"BoxYMin": {
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},
"BoxYMax": {
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"id": null,
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},
"PredictedIoU": {
"dtype": "string",
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},
"Clicks": {
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}
},
"length": -1,
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"_type": "Sequence"
}
},
"length": -1,
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}
}