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README
Apache-2.0

image-annotation

用于制作darknet数据集制作,并提供转换为Voc数据集的能力

MainWindows.py

在工具根目录下使用下面的命令

python3 MianWindow.py

快捷键

操作 快捷键
撤回上一次的标注 Control+Z或者Command+Z
切换图片 上下键
快速保存当前标注并切换到下一张图片 S或者空格或者回车

应用功能说明

区域划分

  1. 区域1:工具栏
  2. 区域2:图片显示预览
  3. 区域3:标注图片画板
  4. 区域4:标注类型选择区域
  5. 区域4:标注记录显示区

使用效果

启动程序后,只有==打开图集==功能可以使用,其他功能必须在打开一个图集(一个全是图片的文件夹)后才可以使用。

配置文件

在打开所在图集文件夹下会生成一个默认的配置文件

SelectWindow操作文档

启动程序的命令

python SelectImageWindow.py

应用说明

该程序用于把MainWindow.py分好类的文件中挑选训练集测试集,并生成标准VOC数据集。

  1. 在开始该程序前,必须检查分类文件夹下是否有empty文件夹,如果有必须将该文件夹移走,该文件夹内的图片都是没有特征类型的图片,仅用于校验和检查用。不可参与后面的数据集。
  2. 点击==打开图片集==,选择分好类的文件夹。
  3. 点击为选择的图可以挑选图片,将图片移入到训练集或测试集,
  4. 每次挑选完成后必须点击==保存本次分类==
  5. 所有的分类文件都挑选完成后即可点击==生成VOC数据集==。选择生成的目录后程序就开始执行(生成的图片会统一转换为jpeg的格式,所以比较耗时),该执行耗时比较久大概十几分钟,完成时会有弹框。

环境搭建

所需python模块

  • pillow
  • lxml
  • tkinter

详细查看ducument中的文档

mac环境搭建

ubuntu环境搭建

Win10环境搭建

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用于标注特征图片,生成yolo数据集 展开 收起
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Apache-2.0
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