docker run 的时候增加参数 `--storage-opt size=30G`




```
docker run -it --gpus all --storage-opt size=30G kevinchina/deeplearning:cuda10.1pytorch1.7.1baseenv0.1 bash
```

> 设置容器磁盘大小 在 docker 启动时候 加载参数 --storage-opt dm.basesize=100G 用来调整默认容器的

> rootfs大小； 在创建容器的时候使用参数--storage-opt size=30G来设置改容器的 rootfs 大小。

> 

> 作者：momo1023 链接：https://www.jianshu.com/p/d984723d9b31 来源：简书

> 著作权归作者所有。商业转载请联系作者获得授权，非商业转载请注明出处。

docker 容器 磁盘 10G 限制 大小

# cpu





miniconda3的一个基础镜像，其中安装fastapi和opencv。

kevinchina/deeplearning:miniconda3base0.2
```shell
FROM kevinchina/deeplearning:wrfbaseenv
COPY deps /deps
RUN rm -rf /etc/yum.repos.d/* && \
    cp /deps/CentOS-Base.repo /etc/yum.repos.d/ && \
    yum clean all
RUN yum install wget opencv -y
RUN wget http://mirrors.tuna.tsinghua.edu.cn/anaconda/miniconda/Miniconda3-latest-Linux-x86_64.sh -O /tmp/conda.sh && \
    /bin/bash /tmp/conda.sh -b && \
    cp -f /deps/.condarc ~/ && rm /tmp/conda.sh
ENV PATH ~/miniconda3/bin:$PATH
RUN ~/miniconda3/bin/conda init bash && \
    . ~/.bashrc && \
    conda create -n py38 python=3.8.12 -y
RUN . ~/.bashrc && \
    conda activate py38 && \
    pip install -i https://pypi.tuna.tsinghua.edu.cn/simple pip -U && \
    pip config set global.index-url https://pypi.tuna.tsinghua.edu.cn/simple && \
    pip install fastapi uvicorn python-multipart requests opencv-python numpy
RUN cp /usr/share/zoneinfo/Asia/Shanghai /etc/localtime && echo 'Asia/Shanghai' >/etc/timezone
```

在上一个基础上，安装pytorch cpu版本 1.8

kevinchina/deeplearning:miniconda3base0.3
```shell
FROM kevinchina/deeplearning:miniconda3base0.2
RUN . ~/.bashrc && conda activate py38 && conda install pytorch==1.8.0 torchvision==0.9.0 torchaudio==0.8.0 cpuonly -c pytorch
```

在上一个基础上，安装 yolo需求的包， 创建app文件夹。

成为 ： kevinchina/deeplearning:miniconda3base0.6
```
FROM kevinchina/deeplearning:miniconda3base0.3
RUN mkdir /app
WORKDIR /app
COPY requirements.txt .
COPY deps/Arial.ttf /root/.config/Ultralytics/Arial.ttf
RUN . ~/.bashrc && conda activate py38 && pip install -i https://pypi.tuna.tsinghua.edu.cn/simple pip -U
RUN . ~/.bashrc && conda activate py38 && pip install -r requirements.txt -i https://pypi.tuna.tsinghua.edu.cn/simple
RUN . ~/.bashrc && conda activate py38 && pip install -r requirements.txt
```

```
matplotlib>=3.2.2
Pillow
PyYAML==5.3.1
scipy>=1.4.1
tqdm>=4.41.0
seaborn>=0.11.0
pandas
Shapely==1.8.0
numpy==1.19.2
tensorboard
```



# selenium

在kevinchina/deeplearning:miniconda3base0.2基础上装selenium

kevinchina/deeplearning:miniconda3base0.5
```shell
FROM kevinchina/deeplearning:miniconda3base0.2
RUN . ~/.bashrc && \
    conda activate py38 && \
    pip config set global.index-url https://pypi.tuna.tsinghua.edu.cn/simple && \
    pip install -i https://pypi.tuna.tsinghua.edu.cn/simple pip -U && \
    pip install  pandas requests selenium
```



# GPU CUDA11.1  pytorch1.8

cuda11.1+pytorch1.8+opencv

kevinchina/deeplearning:cuda11.1pytorch1.8baseenv0.1
```shell
FROM kevinchina/deeplearning:cuda11.1pytorch1.8baseenv
RUN cp /usr/share/zoneinfo/Asia/Shanghai /etc/localtime && echo 'Asia/Shanghai' >/etc/timezone
```

下面是kevinchina/deeplearning:cuda11.1pytorch1.8baseenv0.5：

将目前YOLOv5需要的环境安装了起来。
```
FROM kevinchina/deeplearning:cuda11.1pytorch1.8baseenv0.1
RUN mkdir /app
WORKDIR /app
COPY requirements.txt .
RUN . ~/.bashrc && conda activate py38 && pip install -i https://pypi.tuna.tsinghua.edu.cn/simple pip -U
RUN . ~/.bashrc && conda activate py38 && pip install -r requirements.txt -i https://pypi.tuna.tsinghua.edu.cn/simple
COPY deps/Arial.ttf /root/.config/Ultralytics/Arial.ttf
RUN . ~/.bashrc && conda activate py38 && pip install numpy==1.19.2 wandb  tensorboard -i https://pypi.tuna.tsinghua.edu.cn/simple
```

```
matplotlib>=3.2.2
Pillow
PyYAML==5.3.1
scipy>=1.4.1
tqdm>=4.41.0
seaborn>=0.11.0
pandas
Shapely==1.8.0
numpy==1.19.2
tensorboard
```

# GPU CUDA10.2 pytorch1.8

cuda10.2+pytorch1.8+opencv

kevinchina/deeplearning:cuda10.2pytorch1.8baseenv0.1
```shell
FROM nvidia/cuda:10.2-cudnn7-devel-centos7
COPY deps /deps
RUN rm -rf /etc/yum.repos.d/* && cp /deps/CentOS-Base.repo /etc/yum.repos.d/ && yum clean all
RUN yum install wget opencv vim -y
RUN wget http://mirrors.tuna.tsinghua.edu.cn/anaconda/miniconda/Miniconda3-latest-Linux-x86_64.sh -O /tmp/conda.sh && \
    bash /tmp/conda.sh -b && rm /tmp/conda.sh && \
    cp -f /deps/.condarc /root/
RUN ~/miniconda3/bin/conda init bash && . ~/.bashrc && conda create -n py38 python=3.8.12 -y
RUN . ~/.bashrc && conda activate py38 && pip install -i https://pypi.tuna.tsinghua.edu.cn/simple pip -U && pip config set global.index-url https://pypi.tuna.tsinghua.edu.cn/simple && pip install fastapi uvicorn python-multipart requests opencv-python numpy
RUN . ~/.bashrc && conda activate py38 && conda install pytorch==1.8.0 torchvision==0.9.0 torchaudio==0.8.0 cudatoolkit=10.2 -c pytorch -y
RUN cp /usr/share/zoneinfo/Asia/Shanghai /etc/localtime && echo 'Asia/Shanghai' >/etc/timezone
```

# GPU CUDA10.2   pytorch1.6.0

```shell
FROM nvidia/cuda:10.2-cudnn7-devel-centos7
COPY deps /deps
RUN rm -rf /etc/yum.repos.d/* && cp /deps/CentOS-Base.repo /etc/yum.repos.d/ && yum clean all
RUN yum install wget opencv vim -y
RUN wget http://mirrors.tuna.tsinghua.edu.cn/anaconda/miniconda/Miniconda3-latest-Linux-x86_64.sh -O /tmp/conda.sh && \
    bash /tmp/conda.sh -b && rm /tmp/conda.sh && \
    cp -f /deps/.condarc /root/
RUN ~/miniconda3/bin/conda init bash && . ~/.bashrc && conda create -n py38 python=3.8.12 -y
RUN . ~/.bashrc && conda activate py38 && pip install -i https://pypi.tuna.tsinghua.edu.cn/simple pip -U && pip config set global.index-url https://pypi.tuna.tsinghua.edu.cn/simple && pip install fastapi uvicorn python-multipart requests opencv-python numpy
RUN . ~/.bashrc && conda activate py38 && conda install pytorch==1.6.0 torchvision==0.7.0 cudatoolkit=10.2 -c pytorch
RUN cp /usr/share/zoneinfo/Asia/Shanghai /etc/localtime && echo 'Asia/Shanghai' >/etc/timezone
```


# GPU CUDA10.1 pytorch1.7.1

cuda10.1+pytorch1.7.1+opencv

kevinchina/deeplearning:cuda10.1pytorch1.7.1baseenv0.1

```shell
FROM nvidia/cuda:10.1-cudnn7-devel-centos7
COPY deps /deps
RUN rm -rf /etc/yum.repos.d/* && cp /deps/CentOS-Base.repo /etc/yum.repos.d/ && yum clean all
RUN yum install wget opencv vim -y
RUN wget http://mirrors.tuna.tsinghua.edu.cn/anaconda/miniconda/Miniconda3-latest-Linux-x86_64.sh -O /tmp/conda.sh && \
    bash /tmp/conda.sh -b && rm /tmp/conda.sh && \
    cp -f /deps/.condarc /root/
RUN ~/miniconda3/bin/conda init bash && . ~/.bashrc && conda create -n py38 python=3.8.12 -y
RUN . ~/.bashrc && conda activate py38 && pip install -i https://pypi.tuna.tsinghua.edu.cn/simple pip -U && pip config set global.index-url https://pypi.tuna.tsinghua.edu.cn/simple && pip install fastapi uvicorn python-multipart requests opencv-python numpy
RUN . ~/.bashrc && conda activate py38 && conda install pytorch==1.7.1 torchvision==0.8.2 torchaudio==0.7.2 cudatoolkit=10.1 -c pytorch -y
RUN cp /usr/share/zoneinfo/Asia/Shanghai /etc/localtime && echo 'Asia/Shanghai' >/etc/timezone
```

加一些库，加个VGG16的权重进去用。

kevinchina/deeplearning:cuda10.1pytorch1.7.1baseenv0.2
```
FROM kevinchina/deeplearning:cuda10.1pytorch1.7.1baseenv0.1
RUN . ~/.bashrc && conda activate py38 && pip install pymilvus pandas pillow clickhouse_driver opencv-python pillow requests
COPY vgg16-397923af.pth /root/.cache/torch/hub/checkpoints/
```

# YOLO

装了一些yolo的东西

kevinchina/deeplearning:cuda10.2torch1.8yolov0.1
```python
FROM kevinchina/deeplearning:cuda10.2pytorch1.8baseenv0.1
COPY requirements.txt .
COPY Arial.ttf /root/.config/Ultralytics/
RUN . ~/.bashrc && conda activate py38 && pip install -r requirements.txt
#pip install -r requirements.txt
# Base ----------------------------------------
matplotlib>=3.2.2
numpy>=1.18.5
Pillow
PyYAML==5.3.1
requests>=2.23.0
scipy>=1.4.1
tqdm>=4.41.0
pandas
requests
fastapi
uvicorn
python-multipart
seaborn>=0.11.0
pandas
Shapely==1.8.0
opencv-python
```

# paddle OCR 

docker push kevinchina/deeplearning:paddleocr0.1
```
FROM paddlepaddle/paddle:2.2.1
RUN rm -f /etc/localtime
RUN cp /usr/share/zoneinfo/Asia/Shanghai /etc/localtime && echo 'Asia/Shanghai' >/etc/timezone
RUN pip install -i https://pypi.tuna.tsinghua.edu.cn/simple pip -U
RUN pip config set global.index-url https://pypi.tuna.tsinghua.edu.cn/simple
RUN pip install fastapi uvicorn python-multipart requests opencv-python numpy
RUN unset GREP_OPTIONS
COPY . /PaddleOCRAI
WORKDIR /PaddleOCRAI
RUN pip install -i https://pypi.tuna.tsinghua.edu.cn/simple pip install -r requirements.txt
RUN python setup.py install
#ENTRYPOINT nohup python ocr_fastapi_only_one.py >/ocr.log 2>&1 &
```

dockerfile 常用的环境编写 miniconda3 dockerfile python

dockerfile





COPY hl.tar.gz /wrf_env/

得到

```shell
(base) [root@fce482f7fc63 wrf_env]# ll
total 4
-rw-r--r--. 1 root root 143 Dec  9 03:35 hl.tar.gz
```

ADD hl.tar.gz /wrf_env1/

得到

```shell
(base) [root@fce482f7fc63 wrf_env1]# ll
total 0
drwxr-xr-x. 2 root root 24 Dec  9 03:32 test
(base) [root@fce482f7fc63 wrf_env1]# pwd
/wrf_env1
```

dockerfile ADD 和 COPY

centOS镜像的话，dockerfile 加一句：




```
RUN cp /usr/share/zoneinfo/Asia/Shanghai /etc/localtime && echo 'Asia/Shanghai' >/etc/timezone
```

Docker 容器内时区 时区对不上

[https://ivanzz1001.github.io/records/post/docker/2018/04/20/docker-harbor-architecture](https://ivanzz1001.github.io/records/post/docker/2018/04/20/docker-harbor-architecture)

Harbor整体架构

# 1docker login





去DockerHub官网建立帐号，然后创建仓库deeplearning。

本地使用docker login进行登陆。登陆成功有提示。

![在这里插入图片描述](/static/img/images/00215.png)

# 2 docker tag

更名

docker tag cpu:v1 kevinchina/deeplearning:cpuv1

# 3 docker push

上传

docker push kevinchina/deeplearning:cpuv1

等待即可：

![在这里插入图片描述](/static/img/images/00216.png)

# 阿里的Dockerhub

[https://cr.console.aliyun.com/#/imageList](https://cr.console.aliyun.com/#/imageList)

如何Docker push到DockerHub

参考：[https://blog.csdn.net/wenwenxiong/article/details/78728696](https://blog.csdn.net/wenwenxiong/article/details/78728696)





# 软链接

软链接的方式可以说是最简单最快捷最方便的方法，以后遇到这类问题都可以用这样去解决。

软件就是文件系统，docker的目录是/var/lib/docker，创建软链接让实际的文件存到别的地方，但相关系统变量都可以通过原路径/var/lib/docker访问。
```bash
# 停止docker
systemctl stop docker.socket
systemctl stop docker
# 移动docker所有文件
mv /var/lib/docker /home/docker
# 建立软连接
ln -s /home/docker/docker /var/lib/docker
# 重启docker
systemctl restart docker
```

![在这里插入图片描述](/static/img/images/00217.png)

【运维】Linux 修改Docker存储路径

如图所示，docker run -d -p 8080:8080 tomcat 启动tomcat服务。





然后docker logs 1ba487b1e2ca查看容器启动日志都没问题，但浏览器访问tomcat 8080就是出现404，且我的防火墙已经关闭。

![在这里插入图片描述](/static/img/images/00241.png)

经查验，解决方式需要 删除容器内的webapps空文件夹，然后把webapps.list改名为webapps，指令为：

```bash
docker exec -it 1ba487b1e2ca /bin/bash # 进入容器
rm -rf webapps # 删除
mv webapps.dist webapps # 重命名
```

![在这里插入图片描述](/static/img/images/00242.png)

再访问就OK了：

![在这里插入图片描述](/static/img/images/00243.png)

docker tomcat 容器 访问tomcat主页出现404提示

# 查看Docker存储位置





如此可以查看存储位置：
```csharp
sudo docker info | grep "Docker Root Dir"
```

# 使用软链接方式修改Docker存储位置

docker 的默认存储路径是/var/lib/docker，改成软链接即可。

```shell
# 关闭docker
sudo systemctl stop docker.socket
sudo systemctl stop docker
# 创建一个目录用于存储
mkdir -p /home/work/docker_root
# 移动文件
cp -R /var/lib/docker/* /home/work/docker_root
# 删除文件
rm -rf /var/lib/docker
# 增加软链接
ln -s /home/work/docker_root  /var/lib/docker
# 重启docker
sudo systemctl start docker
```

参考：[https://blog.csdn.net/BigData_Mining/article/details/104921479](https://blog.csdn.net/BigData_Mining/article/details/104921479)

Docker 修改 默认存储位置 存储空间不够

利用--shm-size参数：





```powershell
docker run -it --shm-size="6g" ubuntu
```