# pneumoconiosis_analysis

**Repository Path**: numerical_aggregation_research/pneumoconiosis

## Basic Information

- **Project Name**: pneumoconiosis_analysis
- **Description**: chenfeibing
- **Primary Language**: Unknown
- **License**: Apache-2.0
- **Default Branch**: master
- **Homepage**: None
- **GVP Project**: No

## Statistics

- **Stars**: 0
- **Forks**: 0
- **Created**: 2023-09-14
- **Last Updated**: 2023-10-31

## Categories & Tags

**Categories**: Uncategorized

**Tags**: None

## README

# 准备
1、安装anaconda
设置源
https://mirror.tuna.tsinghua.edu.cn/help/anaconda/

```shell
Windows 用户无法直接创建名为 .condarc 的文件，可先执行 conda config --set show_channel_urls yes 生成该文件之后再修改。

# 阿里
channels:
  - defaults
show_channel_urls: true
default_channels:
  - http://mirrors.aliyun.com/anaconda/pkgs/main
  - http://mirrors.aliyun.com/anaconda/pkgs/r
  - http://mirrors.aliyun.com/anaconda/pkgs/msys2
custom_channels:
  conda-forge: http://mirrors.aliyun.com/anaconda/cloud
  msys2: http://mirrors.aliyun.com/anaconda/cloud
  bioconda: http://mirrors.aliyun.com/anaconda/cloud
  menpo: http://mirrors.aliyun.com/anaconda/cloud
  pytorch: http://mirrors.aliyun.com/anaconda/cloud
  simpleitk: http://mirrors.aliyun.com/anaconda/cloud

# 清华
channels:
  - defaults
show_channel_urls: true
default_channels:
  - https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
  - https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/r
  - https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/msys2
custom_channels:
  conda-forge: https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud
  msys2: https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud
  bioconda: https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud
  menpo: https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud
  pytorch: https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud
  pytorch-lts: https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud
  simpleitk: https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud
  deepmodeling: https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/
```

运行 conda clean -i 清除索引缓存，保证用的是镜像站提供的索引。

2、确保显卡可用，驱动已安装，查看cuda版本
命令nvidia-smi

# 配置环境

pytorch官网：https://pytorch.org/get-started/locally/
autogluon官网：https://auto.gluon.ai/stable/install.html

```shell
# 1虚拟环境
conda create -n env_autogluon0.82pip python=3.9
conda activate env_autogluon0.82pip
pip install -U setuptools wheel pip -i https://pypi.tuna.tsinghua.edu.cn/simple

# 2安装pytorch，1.13.1版本，cuda这里安装的是pytorch-cuda=11.7，根据本地cuda版本安装
conda install pytorch==1.13.1 torchvision==0.14.1 torchaudio==0.13.1 pytorch-cuda=11.7 -c pytorch -c nvidia

## conda装不上推荐用pip装
pip --default-timeout=1000 install torch==1.13.1+cu117 torchvision==0.14.1+cu117 --extra-index-url https://download.pytorch.org/whl/cu117

## 3如果gpu版本推理不成功，安装cpu版本
pip install torch==1.13.1+cpu torchvision==0.14.1+cpu -f https://download.pytorch.org/whl/cpu/torch_stable.html

# 4安装autogloun
pip install autogluon -i https://pypi.tuna.tsinghua.edu.cn/simple

# 5安装其他包
pip install jupyter yapf opencv-python simpleitk openpyxl imutils -i https://pypi.tuna.tsinghua.edu.cn/simple
pip install jupyter yapf -i https://pypi.tuna.tsinghua.edu.cn/simple

```
# 预测
src目录下predict.py为预测文件，文件下包括两个函数，支持单个文件预测和多文件预测

```shell
#测试命令行
python main.py --dicom_file_path E:\pycharmworkspace\pneumoconiosis\datasets\482778.dcm
python main.py --dir_path E:\pycharmworkspace\pneumoconiosis\datasets\dicom
```

# 打包
pip install pyinstaller -i https://pypi.tuna.tsinghua.edu.cn/simple

1.把生成的exe文件存放在指定目录：pyinstaller (-F) xxx.py --distpath DIR
2.把生成的spec文件存放在指定目录：pyinstaller (-F) xxx.py --specpath DIR
3.把生成的build文件夹存放在指定目录：pyinstaller (-F) xxx.py --workpath DIR

```shell
pyi-makespec -F -w -i C:\Users\Administrator\Desktop\lung.ico main.py 
pyinstaller main.spec

pyinstaller -F -w -i C:\Users\Administrator\Desktop\lung.ico main.py 

# 调用
./main.exe --dicom_file_path E:\pycharmworkspace\pneumoconiosis\datasets\482778.dcm
```
# 服务
```shell
conda activate env_autogluon0.82pip2

python C:\Users\Administrator\Desktop\pneumoconiosis_v2\pneumoconiosis\app.py                
```