# watersegmentation
#### 介绍
模式识别与机器学习课程的小组结课项目,也是极市开发者平台的打榜项目。采用开源模型DeepLabV3+作为项目主干,通过对水体和水体上的漂浮物进行像素级别的分割,并按照面积阈值判断并输出报警消息。
#### 使用说明
1.参考github上开源模型实现:https://github.com/VainF/DeepLabV3Plus-Pytorch?tab=readme-ov-file。
2.数据集由极市开发者平台打榜项目《水务漂浮物识别》提供。
3.由于平台需要由bash启动训练,所以我们将main.py中的常用调试参数都提取出来,写了一个基本的bash启动器。
4.平台上测试需在ev_sdk路径下使用ji.py作为测试接口。
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基于开源模型DeepLabV3+的模式识别与机器学习课程的小组结课项目(课程设计)
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模式识别与机器学习课程的小组结课项目,也是极市开发者平台的打榜项目。采用开源模型DeepLabV3+作为项目主干,通过对水体和水体上的漂浮物进行像素级别的分割,并按照面积阈值判断并输出报警消息。模式识别与机器学习课程的小组结课项目,也是极市开发者平台的打榜项目。采用开源模型DeepLabV3+作为项目主干,通过对水体和水体上的漂浮物进行像素级别的分割,并按照面积阈值判断并输出报警消息。模式识别与机器学习课程的小组结课项目,也是极市开发者平台的打榜项目。采用开源模型DeepLabV3+作为项目主干,通过对水体和水体上的漂浮物进行像素级别的分割,并按照面积阈值判断并输出报警消息。模式识别与机器学习课程的小组结课项目,也是极市开发者平台的打榜项目。采用开源模型DeepLabV3+作为项目主干,通过对水体和水体上的漂浮物进行像素级别的分割,并按照面积阈值判断并输出报警消息。模式识别与机器学习课程的小组结课项目,也是极市开发者平台的打榜项目。采用开源模型DeepLabV3+作为项目主干,通过对水体和水体上的漂浮物进行像素级别的分割,并按照面积阈值判断并输出报警消息。
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基于开源模型DeepLabV3+的模式识别与机器学习课程的小组结课项目(课程设计) (258个子文件)
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