yuantn/MI-AOD

Extend it to use other mmdetection models

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Thanks for the amazing work, I wanted to ask if we can extend the proposed model to use with mmdetection models e.g. faster-rcnns etc. Will simply replacing and managing the config files work? or the method is specifically designed to work with refineNet and SSD?

Thanks for your attention to our work.
This model can be extended to more mmdetection models. Extending to the anchor-based models would be easier, but just replacing the configuration files is not enough.

You can regard this repository as a basic version for RetinaNet and an improved version for SSD, and check which files are specially modified for SSD refer to the section Code Structure (such as configs/_base_/ssd300.py, configs/MIAOD_SSD.py, mmdet/models/dense_heads/__init__.py, mmdet/models/dense_heads/ssd_head.py, etc.). Then you can add and modify the corresponding code of the model you want to extend.

Of course, if the model you want to extend is a two-stage detection model like faster-RCNN, you also need to pay attention to the modification of the files like mmdet/models/detectors/two_stage.py, which are only applicable to two-stage models.


感谢您对本工作的关注。

该模型可以扩展至更多的 mmdetection 模型。扩展到基于锚框的方法会较为容易一些,但仅仅替换配置文件是不够的。

你可以将本代码库看作一个适用于 RetinaNet 的基本版和适用于 SSD 的改进版,并参考在 代码结构 部分对比有哪些文件针对 SSD 特意进行了改动(如 configs/_base_/ssd300.pyconfigs/MIAOD_SSD.pymmdet/models/dense_heads/__init__.pymmdet/models/dense_heads/ssd_head.py等等),并将你想要扩展到的模型进行对应部分代码的添加与修改即可。

当然如果你要扩展到的模型是类似于 faster-RCNN 的双阶段检测网络的话,你也需要注意一下对 mmdet/models/detectors/two_stage.py 类似仅适用于双阶段网络文件的修改。