python 在Docker容器中安装OpenCV

p3rjfoxz 于 2023-03-28 发布在 Python

关注(0)|答案(9)|浏览(211)

我正在尝试Dockerise一个Python应用程序，它依赖于OpenCV。我已经尝试了几种不同的方法，但是当我尝试运行应用程序时，我总是得到... ImportError: No module named cv2。
这是我目前的Dockerfile。

FROM python:2.7

MAINTAINER Ewan Valentine <ewan@theladbible.com>

RUN mkdir -p /usr/src/app 
WORKDIR /usr/src/app 

# Various Python and C/build deps
RUN apt-get update && apt-get install -y \ 
    wget \
    build-essential \ 
    cmake \ 
    git \
    pkg-config \
    python-dev \ 
    python-opencv \ 
    libopencv-dev \ 
    libav-tools  \ 
    libjpeg-dev \ 
    libpng-dev \ 
    libtiff-dev \ 
    libjasper-dev \ 
    libgtk2.0-dev \ 
    python-numpy \ 
    python-pycurl \ 
    libatlas-base-dev \
    gfortran \
    webp \ 
    python-opencv 

# Install Open CV - Warning, this takes absolutely forever
RUN cd ~ && git clone https://github.com/Itseez/opencv.git && \ 
    cd opencv && \
    git checkout 3.0.0 && \
    cd ~ && git clone https://github.com/Itseez/opencv_contrib.git && \
    cd opencv_contrib && \
    git checkout 3.0.0 && \
    cd ~/opencv && mkdir -p build && cd build && \
    cmake -D CMAKE_BUILD_TYPE=RELEASE \
    -D CMAKE_INSTALL_PREFIX=/usr/local \ 
    -D INSTALL_C_EXAMPLES=ON \ 
    -D INSTALL_PYTHON_EXAMPLES=ON \ 
    -D OPENCV_EXTRA_MODULES_PATH=~/opencv_contrib/modules \ 
    -D BUILD_EXAMPLES=OFF .. && \
    make -j4 && \
    make install && \ 
    ldconfig

COPY requirements.txt /usr/src/app/
RUN pip install --no-cache-dir -r requirements.txt

COPY . /usr/src/app

我的requirements.txt文件

Flask==0.8
gunicorn==0.14.2
requests==0.11.1
bs4==0.0.1
nltk==3.2.1
pymysql==0.7.2
xlsxwriter==0.8.5
numpy==1.11
Pillow==3.2.0
cv2==1.0
pytesseract==0.1

python

来源：https://stackoverflow.com/questions/36862589/install-opencv-in-a-docker-container

9条答案

按热度按时间

63lcw9qa1#

用稍微不同的设置修复

FROM python:2.7

MAINTAINER Ewan Valentine <ewan@theladbible.com>

RUN mkdir -p /usr/src/app 
WORKDIR /usr/src/app 

# Various Python and C/build deps
RUN apt-get update && apt-get install -y \ 
    wget \
    build-essential \ 
    cmake \ 
    git \
    unzip \ 
    pkg-config \
    python-dev \ 
    python-opencv \ 
    libopencv-dev \ 
    libav-tools  \ 
    libjpeg-dev \ 
    libpng-dev \ 
    libtiff-dev \ 
    libjasper-dev \ 
    libgtk2.0-dev \ 
    python-numpy \ 
    python-pycurl \ 
    libatlas-base-dev \
    gfortran \
    webp \ 
    python-opencv \ 
    qt5-default \
    libvtk6-dev \ 
    zlib1g-dev 

# Install Open CV - Warning, this takes absolutely forever
RUN mkdir -p ~/opencv cd ~/opencv && \
    wget https://github.com/opencv/opencv/archive/3.0.0.zip && \
    unzip 3.0.0.zip && \
    rm 3.0.0.zip && \
    mv opencv-3.0.0 OpenCV && \
    cd OpenCV && \
    mkdir build && \ 
    cd build && \
    cmake \
    -DWITH_QT=ON \ 
    -DWITH_OPENGL=ON \ 
    -DFORCE_VTK=ON \
    -DWITH_TBB=ON \
    -DWITH_GDAL=ON \
    -DWITH_XINE=ON \
    -DBUILD_EXAMPLES=ON .. && \
    make -j4 && \
    make install && \ 
    ldconfig

COPY requirements.txt /usr/src/app/
RUN pip install --no-cache-dir -r requirements.txt

COPY . /usr/src/app

赞(0）回复(0）举报 2023-03-28

iugsix8n2#

感谢您发布这篇文章。我遇到了同样的问题，并尝试了您的解决方案，尽管它似乎安装了OpenCV，但它给我留下了Python 6库版本冲突的问题，所以我采取了不同的路线。我认为一个更简单的方法是在您的容器中安装Anaconda，然后添加OpenCV。我使用Python 2，所以我的整个Dockerfile安装OpenCvv只是：

FROM continuumio/anaconda
EXPOSE 5000

ADD . /code-directory
WORKDIR code-directory
RUN conda install opencv

CMD ["python", "run-code.py"]

这将从continuumio/anaconda Dockerfile安装Anaconda，然后它将使用Anaconda安装opencv。如果你需要，还有一个单独的continuumio Dockerfile用于Python 3。

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2admgd593#

下面是一个image，它是在Ubuntu 16.04上用Python2 + Python3 + OpenCV构建的。
下面是Dockerfile（在上面提到的同一个dockerhub repo中提供），它将在Ubuntu 16.04上为python2和python3安装opencv，并设置相应的raw1394链接。

FROM ubuntu:16.04
MAINTAINER Chenna Varri

RUN apt-get update
RUN apt-get install -y build-essential apt-utils

RUN apt-get install -y cmake git libgtk2.0-dev pkg-config libavcodec-dev \
  libavformat-dev libswscale-dev
RUN  apt-get update && apt-get install -y python-dev python-numpy \
  python3 python3-pip python3-dev libtbb2 libtbb-dev \
  libjpeg-dev libjasper-dev libdc1394-22-dev \
  python-opencv libopencv-dev libav-tools python-pycurl \
  libatlas-base-dev gfortran webp qt5-default libvtk6-dev zlib1g-dev

RUN pip3 install numpy

RUN apt-get install -y python-pip
RUN pip install --upgrade pip

RUN cd ~/ &&\
    git clone https://github.com/Itseez/opencv.git &&\
    git clone https://github.com/Itseez/opencv_contrib.git &&\
    cd opencv && mkdir build && cd build && cmake  -DWITH_QT=ON -DWITH_OPENGL=ON -DFORCE_VTK=ON -DWITH_TBB=ON -DWITH_GDAL=ON -DWITH_XINE=ON -DBUILD_EXAMPLES=ON .. && \
    make -j4 && make install && ldconfig

# Set the appropriate link
RUN ln /dev/null /dev/raw1394

RUN cd ~/opencv

对于刚开始使用Docker的人的一些额外说明：

在存放此Dockerfile的目录中，将docker镜像构建为docker build -t ubuntu_cv .
构建映像后，可以执行docker images检查

REPOSITORY   TAG       IMAGE ID      CREATED             SIZE

ubuntu_cv  latest    6210ddd6346b   24 minutes ago      2.192 GB

您可以将Docker容器启动为docker run -t -i ubuntu_cv:latest

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fruv7luv4#

要在docker中安装OpenCV（latest）...步骤与Linux版本类似，只是符号链接路径不同：

apt install -y libtiff5-dev libjpeg8-dev libpng-dev cmake make
apt install -y libavcodec-dev libavformat-dev libswscale-dev libdc1394-22-dev
apt install -y libxine2-dev libv4l-dev
apt install -y libgstreamer1.0-dev libgstreamer-plugins-base1.0-dev
apt install -y qt5-default
apt install -y libatlas-base-dev
apt install -y libfaac-dev libmp3lame-dev libtheora-dev
apt install -y libvorbis-dev libxvidcore-dev
apt install -y libopencore-amrnb-dev libopencore-amrwb-dev
apt install -y x264 x265 v4l-utils
apt install -y libprotobuf-dev protobuf-compiler
apt install -y libeigen3-dev

wget --output-document cv.zip https://github.com/opencv/opencv/archive/4.0.1.zip
wget --output-document contrib.zip 
https://github.com/opencv/opencv_contrib/archive/4.0.1.zip
unzip cv.zip
unzip contrib.zip
cd opencv-4.0.1
mkdir build
cd build
cmake -D CMAKE_BUILD_TYPE=RELEASE \
  -D CMAKE_INSTALL_PREFIX=/usr/local \
  -D WITH_TBB=ON \
  -D WITH_V4L=ON \
  -D WITH_QT=ON \
  -D WITH_OPENGL=ON \
  -D WITH_CUDA=ON \
  -D WITH_NVCUVID=OFF \
  -D OPENCV_EXTRA_MODULES_PATH=../../opencv_contrib-4.0.1/modules \
  -D OPENCV_ENABLE_NONFREE=ON \
  ..

make -j 'number of gpu'
make install 
ldconfig
ln -s /usr/local/lib/python3.6/dist-packages/cv2/python-3.6/cv2.cpython-36m-x86_64-linux-gnu.so /usr/local/lib/python3.6/dist-packages/cv2/python-3.6/cv2.so

这对我很有效！

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chhqkbe15#

对于一些应用程序（比如我的例子），你可以使用python包opencv-python-headless。如果你所做的只是基于CPU的opencv活动，这将直接在docker镜像中工作。

WORKDIR /usr/src/app

COPY requirements.txt ./
RUN pip install --no-cache-dir -r requirements.txt

COPY . .

CMD [ "python", "./camera_controller.py" ]

通过requirements.txt中的此行

opencv-python-headless==<your version>

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3zwtqj6y6#

from    ubuntu:12.10

# Ubuntu sides with libav, I side with ffmpeg.
run echo "deb http://ppa.launchpad.net/jon-severinsson/ffmpeg/ubuntu quantal main" >> /etc/apt/sources.list
run apt-key adv --keyserver keyserver.ubuntu.com --recv-keys 1DB8ADC1CFCA9579

run apt-get update
run apt-get install -y -q wget curl
run apt-get install -y -q build-essential
run apt-get install -y -q cmake
run apt-get install -y -q python2.7 python2.7-dev
run wget 'https://pypi.python.org/packages/2.7/s/setuptools/setuptools-0.6c11-py2.7.egg' && /bin/sh setuptools-0.6c11-py2.7.egg && rm -f setuptools-0.6c11-py2.7.egg
run curl 'https://raw.github.com/pypa/pip/master/contrib/get-pip.py' | python2.7
run pip install numpy
run apt-get install -y -q libavformat-dev libavcodec-dev libavfilter-dev libswscale-dev
run apt-get install -y -q libjpeg-dev libpng-dev libtiff-dev libjasper-dev zlib1g-dev libopenexr-dev libxine-dev libeigen3-dev libtbb-dev
add build_opencv.sh /build_opencv.sh
run /bin/sh /build_opencv.sh
run rm -rf /build_opencv.sh

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wyyhbhjk7#

我使用这个Dockerfile，它工作起来很有魅力

FROM python:3.9

LABEL mantainer="Baher Elnaggar <eng.baher77@gmail.com>"

WORKDIR /opt/build

ENV OPENCV_VERSION="4.5.1"

RUN apt-get -qq update \
    && apt-get -qq install -y --no-install-recommends \
        build-essential \
        cmake \
        git \
        wget \
        unzip \
        yasm \
        pkg-config \
        libswscale-dev \
        libtbb2 \
        libtbb-dev \
        libjpeg-dev \
        libpng-dev \
        libtiff-dev \
        libopenjp2-7-dev \
        libavformat-dev \
        libpq-dev \
    && pip install numpy \
    && wget -q https://github.com/opencv/opencv/archive/${OPENCV_VERSION}.zip -O opencv.zip \




    && unzip -qq opencv.zip -d /opt \
    && rm -rf opencv.zip \
    && cmake \
        -D BUILD_TIFF=ON \
        -D BUILD_opencv_java=OFF \
        -D WITH_CUDA=OFF \
        -D WITH_OPENGL=ON \
        -D WITH_OPENCL=ON \
        -D WITH_IPP=ON \
        -D WITH_TBB=ON \
        -D WITH_EIGEN=ON \
        -D WITH_V4L=ON \
        -D BUILD_TESTS=OFF \
        -D BUILD_PERF_TESTS=OFF \
        -D CMAKE_BUILD_TYPE=RELEASE \
        -D CMAKE_INSTALL_PREFIX=$(python3.9 -c "import sys; print(sys.prefix)") \
        -D PYTHON_EXECUTABLE=$(which python3.9) \
        -D PYTHON_INCLUDE_DIR=$(python3.9 -c "from distutils.sysconfig import get_python_inc; print(get_python_inc())") \
        -D PYTHON_PACKAGES_PATH=$(python3.9 -c "from distutils.sysconfig import get_python_lib; print(get_python_lib())") \
        /opt/opencv-${OPENCV_VERSION} \
    && make -j$(nproc) \
    && make install \
    && rm -rf /opt/build/* \
    && rm -rf /opt/opencv-${OPENCV_VERSION} \
    && rm -rf /var/lib/apt/lists/* \
    && apt-get -qq autoremove \
    && apt-get -qq clean

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du7egjpx8#

如果你想在CUDA中使用OpenCV dnn，在GPU中使用Torch（可选），我推荐这样做：

FROM nvidia/cuda:10.2-base-ubuntu18.04

WORKDIR /home

ENV DEBIAN_FRONTEND=noninteractive
ENV TZ=Europe/Minsk
RUN ln -snf /usr/share/zoneinfo/$TZ /etc/localtime && echo $TZ > /etc/timezone

RUN apt-get update && apt-get install -y \
    keyboard-configuration \
    nvidia-driver-440\
    curl \
    ca-certificates \
    sudo \
    git \
    bzip2 \
    libx11-6 \
    cmake \
    g++ \
    wget \
    build-essential \ 
    cmake \ 
    git \
    unzip \ 
    pkg-config \
    python-dev \ 
    python-opencv \ 
    libopencv-dev \ 
    libjpeg-dev \ 
    libpng-dev \ 
    libtiff-dev \  
    libgtk2.0-dev \ 
    python-numpy \ 
    python-pycurl \ 
    libatlas-base-dev \
    gfortran \
    webp \ 
    python-opencv \ 
    qt5-default \
    libvtk6-dev \ 
    zlib1g-dev \
    libcudnn7=7.6.5.32-1+cuda10.2 \
    libcudnn7-dev=7.6.5.32-1+cuda10.2 \
    python3-pip \
    python3-venv \
    nano

RUN alias python='/usr/bin/python3'
RUN pip3 install numpy
RUN pip3 install torch

#RUN echo ############ && python --version && ##############

# Install Open CV - Warning, this takes absolutely forever
RUN git clone https://github.com/opencv/opencv_contrib  && \
    cd opencv_contrib  && \
    git fetch --all --tags  && \
    git checkout tags/4.3.0  && \
    cd .. && \
    git clone https://github.com/opencv/opencv.git  && \
    cd opencv  && \
    git checkout tags/4.3.0   

#RUN pip3 freeze && which python3 && python3 --version

################################################################
#################### OPENCV CPU ################################

#RUN pwd &&\
#    cd opencv  && \
#    pwd &&\
#    mkdir build && cd build && \
#    pwd &&\
#    cmake -DCMAKE_BUILD_TYPE=Release  \
#      -DENABLE_CXX14=ON                 \
#      -DBUILD_PERF_TESTS=OFF            \
#      -DOPENCV_GENERATE_PKGCONFIG=ON    \
#      -DWITH_XINE=ON                    \
#      -DBUILD_TESTS=OFF                 \
#      -DENABLE_PRECOMPILED_HEADERS=OFF  \
#      -DCMAKE_SKIP_RPATH=ON             \
#      -DBUILD_WITH_DEBUG_INFO=OFF       \
#      -DOPENCV_EXTRA_MODULES_PATH=../../opencv_contrib/modules  \
#      
#      -Dopencv_dnn_superres=ON /usr/bin/ .. && \
#    make -j$(nproc) && \
#    make install 

################################################################
#################### OPENCV GPU ################################

RUN cd opencv && mkdir build && cd build && \
    cmake -DCMAKE_BUILD_TYPE=Release \
    -D CMAKE_CXX_COMPILER=/usr/bin/g++ \
    -D PYTHON_DEFAULT_EXECUTABLE=$(which python3) \
    -D BUILD_NEW_PYTHON_SUPPORT=ON \
    -D BUILD_opencv_python3=ON \
    -D HAVE_opencv_python3=ON \
    -D INSTALL_PYTHON_EXAMPLES=ON \
    -D CUDA_TOOLKIT_ROOT_DIR=/usr/local/cuda-10.2 \
    -D CUDA_BIN_PATH=/usr/local/cuda-10.2 \
    -D CUDNN_INCLUDE_DIR=/usr/include/cudnn.h \
    -D WITH_CUDNN=ON \
    -D CUDA_ARCH_BIN=6.1 \
    -D OPENCV_DNN_CUDA=ON \
    -D WITH_CUDA=ON \
    -D BUILD_opencv_cudacodec=OFF \
    -D WITH_GTK=ON \
    -D CMAKE_BUILD_TYPE=RELEASE \
    -D CUDA_HOST_COMPILER:FILEPATH=/usr/bin/gcc-7 \
    -D ENABLE_PRECOMPILED_HEADERS=OFF \
    -D WITH_TBB=ON \
    -D WITH_OPENMP=ON \
    -D WITH_IPP=ON \
    -D BUILD_EXAMPLES=OFF \
    -D BUILD_DOCS=OFF \
    -D BUILD_PERF_TESTS=OFF \
    -D BUILD_TESTS=OFF \
    -D WITH_CSTRIPES=ON \
    -D OPENCV_EXTRA_MODULES_PATH=../../opencv_contrib/modules \
    -D CMAKE_INSTALL_PREFIX=/usr/local/ \
    -DBUILD_opencv_python3=ON         \
    -D PYTHON_DEFAULT_EXECUTABLE=$(which python3) \
    -D PYTHON3_EXECUTABLE=$(which python3)  \
    -D PYTHON_INCLUDE_DIR=$(python3 -c "from distutils.sysconfig import get_python_inc; print(get_python_inc())")  \
    -D PYTHON3_INCLUDE_DIR=$(python3 -c "from distutils.sysconfig import get_python_inc; print(get_python_inc())") \
    -D PYTHON3_LIBRARY=$(python3 -c "from distutils.sysconfig import get_config_var;from os.path import dirname,join ; print(join(dirname(get_config_var('LIBPC')),get_config_var('LDLIBRARY')))")  \
    -D PYTHON3_NUMPY_INCLUDE_DIRS=$(python3 -c "import numpy; print(numpy.get_include())")  \
    -D PYTHON3_PACKAGES_PATH=$(python3 -c "from distutils.sysconfig import get_python_lib; print(get_python_lib())")  \
    -D OPENCV_GENERATE_PKGCONFIG=ON .. \
    -Dopencv_dnn_superres=ON /usr/bin/ .. && \ 
    make -j$(nproc) && \
    make install 

RUN pip3 install opencv/build/python_loader

你就可以跑了

import torch
import os

print('availabe:',torch.cuda.is_available() )
print('devices available', torch.cuda.device_count())
print('device id:',torch.cuda.current_device() )
print('device address', torch.cuda.device(0))
print('gpu model',torch.cuda.get_device_name(0))

device = torch.device('cuda' if torch.cuda.is_available() else 'cpu')
print('Using device:', device)

#Additional Info when using cuda
if device.type == 'cuda':
    print(torch.cuda.get_device_name(0))
    print('Memory Usage:')
    print('Allocated:', round(torch.cuda.memory_allocated(0)/1024**3,1), 'GB')
    print('Cached:   ', round(torch.cuda.memory_reserved(0)/1024**3,1), 'GB')

import cv2
print("DNN_BACKEND_CUDA",cv2.dnn.DNN_BACKEND_CUDA)
print("DNN_BACKEND_CUDA",cv2.dnn.DNN_TARGET_CUDA)

你会得到这样的结果：

Using device: cuda
availabe: True
devices available 1
device id: 0
device address <torch.cuda.device object at 0x7f5a0a392550>
gpu model GeForce GTX 1050 Ti
Memory Usage:
Allocated: 0.0 GB
Cached:    0.0 GB
DNN_BACKEND_CUDA 5
DNN_BACKEND_CUDA 6

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a7qyws3x9#

就加上