dockerfile 常用的环境编写 miniconda3 dockerfile python

cpuminiconda3的一个基础镜像，其中安装fastapi和opencv。kevinchina/deeplearning:miniconda3base0.2FROM kevinchina/deeplearning:wrfbaseenvCOPY deps /depsRUN rm -rf /etc/yum.repos.d/* && \cp /deps/CentOS-Base.re

XD742971636

5743人浏览 · 2021-12-16 09:58:45

XD742971636 · 2021-12-16 09:58:45 发布

cpu

miniconda3的一个基础镜像，其中安装fastapi和opencv。

kevinchina/deeplearning:miniconda3base0.2

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

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

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

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

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

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

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


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 &

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