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Nexdata/10034_People_Re_ID_Data_in_Surveillance_Scenes

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Hugging Face2024-04-11 更新2024-06-12 收录
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https://hf-mirror.com/datasets/Nexdata/10034_People_Re_ID_Data_in_Surveillance_Scenes
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--- license: cc-by-nc-nd-4.0 --- ## Description 10,034 People - Re-ID Data in Surveillance Scenes. The data includes supermarket (inside supermarket and at the gate of the supermarket) scenes. The data includes males and females and the age distribution is from children to the elderly. In this dataset, the rectangular bounding boxes and 15 attributes of human body were annotated.The data can be used for re-id and other tasks. For more details, please refer to the link: https://www.nexdata.ai/dataset/1038?source=Huggingface # Specifications ## Data size 10,034 people ## Population distribution the race distribution is Asian, the gender distribution is male and female, the age distribution is from children to the elderly ## Collecting environment supermarket (inside supermarket and at the gate of the supermarket) ## Data diversity different ages, different time periods, different cameras, different human body orientations and different postures ## Device surveillance cameras, the image resolution is 1,920*1,080 ## Collecting time 8:00-22:00 ## Image parameters the video data is in .mp4 format, the image data is in .jpg format, the annotation file is in .json format ## Annotation content human body rectangular bounding boxes, 15 human body attributes ## Accuracy a rectangular bounding box of human body is qualified when the deviation is not more than 3 # Licensing Information Commercial License
提供机构:
Nexdata
原始信息汇总

数据集概述

基本信息

  • 数据集名称:10,034 People - Re-ID Data in Surveillance Scenes
  • 数据量:10,034人
  • 许可证:cc-by-nc-nd-4.0

数据内容

  • 场景:超市内部及超市门口
  • 人群分布
    • 种族:亚洲人
    • 性别:男性和女性
    • 年龄:从儿童到老年人
  • 数据多样性
    • 不同年龄段
    • 不同时间段
    • 不同摄像头
    • 不同人体朝向和姿势

收集环境与设备

  • 收集环境:超市
  • 设备:监控摄像头,图像分辨率为1,920*1,080
  • 收集时间:8:00-22:00

数据格式与标注

  • 视频格式:.mp4
  • 图像格式:.jpg
  • 标注文件格式:.json
  • 标注内容:人体矩形边界框,15个人体属性
  • 标注精度:人体矩形边界框的偏差不超过3

应用场景

  • 可用于Re-ID及其他相关任务
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