/Autolabelme

Primary LanguagePythonGNU General Public License v3.0GPL-3.0

#Autolabelme-2017a说明
11/8/2017 7:17:42 AM
DO:
labelme软件自动标注功能的稳定版本：
目前实现功能如下：

  1. 自动保存标记的lif文件。（原来需要命名以及制定位置）
  2. 文件标记过程中的跳转等功能的优化，便于操作。（文件按规定格式命名，+1跳转到下一张）
  3. 文件快捷键的设置，很多改为单键操作。
  4. 文件根据FCN检测结果（缺陷区域）实现自动标记并保存为lif文件。（可以手动修正自动标记结果）

TODO:
后期预计增加或者修改的功能：

  1. 一键生成VOC格式的数据集。
  2. 标记结果的handwrite功能，显示生成的标记在原图中画出来。
  3. 与深度学习算法或者传统算法结合，在label软件中调用模型或者算法处理生成缺陷区域图，与edgepoint.py对接。（优先考虑传统算法，速度快）

Labelme

Labelme is a graphical image annotation tool inspired by http://labelme.csail.mit.edu.

It is written in Python and uses Qt for its graphical interface.

Dependencies

Labelme requires at least Python 2.6 and has been tested with PyQt 4.8.

Usage

After cloning the code you should first run make to generate the resource file (a Python module containing all the icons).

You can then start annotating by running ./labelme.py. For usage instructions you can view the screencast tutorial from the Help menu.

At the moment annotations are saved as a JSON file. The file includes the image itself. In the feature support for XML output or possibly even SVG will be added.

TODO

  • Refactor into a Python package.
  • Add installation script.