Multimodal-Fatima/VQAv2_testdev_final
收藏Hugging Face2023-05-14 更新2024-03-04 收录
下载链接:
https://hf-mirror.com/datasets/Multimodal-Fatima/VQAv2_testdev_final
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资源简介:
---
dataset_info:
features:
- name: question_type
dtype: string
- name: multiple_choice_answer
dtype: string
- name: answers
sequence: string
- name: answers_original
list:
- name: answer
dtype: string
- name: answer_confidence
dtype: string
- name: answer_id
dtype: int64
- name: id_image
dtype: int64
- name: answer_type
dtype: string
- name: question_id
dtype: int64
- name: question
dtype: string
- name: image
dtype: image
- name: id
dtype: int64
- name: clip_tags_ViT_L_14
sequence: string
- name: blip_caption
dtype: string
- name: LLM_Description_gpt3_downstream_tasks_visual_genome_ViT_L_14
sequence: string
- name: DETA_detections_deta_swin_large_o365_coco_classes
list:
- name: attribute
dtype: string
- name: box
sequence: float32
- name: label
dtype: string
- name: location
dtype: string
- name: ratio
dtype: float32
- name: size
dtype: string
- name: tag
dtype: string
- name: DETA_detections_deta_swin_large_o365_coco_classes_caption_module_random
list:
- name: attribute
dtype: string
- name: box
sequence: float64
- name: captions_module
sequence: string
- name: captions_module_filter
sequence: string
- name: label
dtype: string
- name: location
dtype: string
- name: ratio
dtype: float64
- name: size
dtype: string
- name: tag
dtype: string
- name: Attributes_ViT_L_14_descriptors_text_davinci_003_full
sequence: string
- name: Attributes_LAION_ViT_H_14_2B_descriptors_text_davinci_003_full
sequence: string
- name: clip_tags_ViT_L_14_with_openai
sequence: string
- name: clip_tags_LAION_ViT_H_14_2B_with_openai
sequence: string
splits:
- name: testdev
num_bytes: 22095364841.0
num_examples: 107394
download_size: 11622249771
dataset_size: 22095364841.0
---
# Dataset Card for "VQAv2_testdev_final"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
数据集信息:
特征:
- 字段名:question_type(问题类型),数据类型:字符串型
- 字段名:multiple_choice_answer(选择题答案),数据类型:字符串型
- 字段名:answers(答案集),数据类型:字符串序列型
- 字段名:answers_original(原始答案集),列表型,包含:
- answer(答案):字符串型
- answer_confidence(答案置信度):字符串型
- answer_id(答案ID):64位整型
- 字段名:id_image(图像ID),数据类型:64位整型
- 字段名:answer_type(答案类型),数据类型:字符串型
- 字段名:question_id(问题ID),数据类型:64位整型
- 字段名:question(问题文本),数据类型:字符串型
- 字段名:image(图像数据),数据类型:图像型
- 字段名:id(样本ID),数据类型:64位整型
- 字段名:clip_tags_ViT_L_14(ViT-L_14模型CLIP标签),数据类型:字符串序列型(CLIP:对比语言-图像预训练模型)
- 字段名:blip_caption(BLIP字幕),数据类型:字符串型(BLIP:自举语言-图像预训练模型)
- 字段名:LLM_Description_gpt3_downstream_tasks_visual_genome_ViT_L_14(基于GPT3、视觉基因组与ViT-L_14的大语言模型下游任务描述),数据类型:字符串序列型(大语言模型:Large Language Model,LLM)
- 字段名:DETA_detections_deta_swin_large_o365_coco_classes(DETA Swin Large模型O365 COCO类别集检测结果),列表型,包含:
- attribute(属性):字符串型
- box(边界框):32位浮点型序列
- label(标签):字符串型
- location(位置):字符串型
- ratio(宽高比):32位浮点型
- size(尺寸):字符串型
- tag(标记):字符串型
- 字段名:DETA_detections_deta_swin_large_o365_coco_classes_caption_module_random(带随机字幕模块的DETA Swin Large模型O365 COCO类别集检测结果),列表型,包含:
- attribute(属性):字符串型
- box(边界框):64位浮点型序列
- captions_module(字幕模块):字符串型序列
- captions_module_filter(字幕模块过滤结果):字符串型序列
- label(标签):字符串型
- location(位置):字符串型
- ratio(宽高比):64位浮点型
- size(尺寸):字符串型
- tag(标记):字符串型
- 字段名:Attributes_ViT_L_14_descriptors_text_davinci_003_full(ViT-L_14与text-davinci-003全量属性描述符),数据类型:字符串序列型
- 字段名:Attributes_LAION_ViT_H_14_2B_descriptors_text_davinci_003_full(LAION ViT-H_14_2B与text-davinci-003全量属性描述符),数据类型:字符串序列型
- 字段名:clip_tags_ViT_L_14_with_openai(带OpenAI标注的ViT-L_14模型CLIP标签),数据类型:字符串序列型
- 字段名:clip_tags_LAION_ViT_H_14_2B_with_openai(带OpenAI标注的LAION ViT-H_14_2B模型CLIP标签),数据类型:字符串序列型
数据集划分:
- 划分名称:testdev,字节数:22095364841.0,样本数:107394
下载大小:11622249771
数据集总大小:22095364841.0
---
# 数据集卡片:"VQAv2_testdev_final"
[需补充更多信息](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
提供机构:
Multimodal-Fatima
原始信息汇总
数据集概述
数据集名称
VQAv2_testdev_final
数据集特征
- question_type (string)
- multiple_choice_answer (string)
- answers (sequence: string)
- answers_original (list)
- answer (string)
- answer_confidence (string)
- answer_id (int64)
- id_image (int64)
- answer_type (string)
- question_id (int64)
- question (string)
- image (image)
- id (int64)
- clip_tags_ViT_L_14 (sequence: string)
- blip_caption (string)
- LLM_Description_gpt3_downstream_tasks_visual_genome_ViT_L_14 (sequence: string)
- DETA_detections_deta_swin_large_o365_coco_classes (list)
- attribute (string)
- box (sequence: float32)
- label (string)
- location (string)
- ratio (float32)
- size (string)
- tag (string)
- DETA_detections_deta_swin_large_o365_coco_classes_caption_module_random (list)
- attribute (string)
- box (sequence: float64)
- captions_module (sequence: string)
- captions_module_filter (sequence: string)
- label (string)
- location (string)
- ratio (float64)
- size (string)
- tag (string)
- Attributes_ViT_L_14_descriptors_text_davinci_003_full (sequence: string)
- Attributes_LAION_ViT_H_14_2B_descriptors_text_davinci_003_full (sequence: string)
- clip_tags_ViT_L_14_with_openai (sequence: string)
- clip_tags_LAION_ViT_H_14_2B_with_openai (sequence: string)
数据集分割
- testdev
- num_bytes: 22095364841.0
- num_examples: 107394
数据集大小
- download_size: 11622249771
- dataset_size: 22095364841.0



