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pytorch_segmentation's Introduction

方案说明(“华为・昇腾杯”AI+遥感影像)

运行环境

  1. python3
  2. pytorch
  3. cuda & cudnn
  4. opencv-python
  5. pillow
  6. albumentations
  7. tqdm
  8. tensorboard

方案思路

基于UNet修改的网络结构,使用resnet50作为backbone,loss采用的是cross entropy + dice,梯度优化器使用的是带momentum的SGD,学习率lr设置为0.01,momentum设置为0.9,weight decay设置为1e-4,scheduler是cosinewithrestarts。

测试复现

在代码根目录运行 python inferrence_multimodel.py 命令

参数说明:

-c 配置文件1

-c2 配置文件2

--models 模型文件列表1

--models2 模型文件列表2

-i 输入图片目录

-o 输出标签目录

参考命令: python inference_multimodel.py -c=config.json -c2=config.json --models saved/ResUnet/10-15_12-15/checkpoint-epoch80.pth saved/ResUnet/10-15_12-15/checkpoint-epoch70.pth --models2 saved/ResUnet/10-16_12-49/checkpoint-epoch90.pth saved/ResUnet/10-16_18-26/checkpoint-epoch90.pth saved/ResUnet/10-17_12-23/checkpoint-epoch100.pth saved/ResUnet/10-17_12-23/checkpoint-epoch95.pth -i=../image_B -o=../results

模型下载

将模型下载之后解压到代码根目录下的saved目录中

百度网盘下载地址:

链接:https://pan.baidu.com/s/1gDzTMwOojrbdEOOnRpA7-A 提取码:rtac

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