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Dockerfile for building MVIG-SJTU/AlphaPose
# based on [sberryman/Dockerfile.yml](https://gist.github.com/sberryman/82a6d13a44f9c4a3bfaf9263b36c92ed)
# You need the cuda drivers and [nvidia-docker](https://github.com/NVIDIA/nvidia-docker)
#
# build with
# docker build .
#
# run with
# docker run --runtime=nvidia -it --rm -v $(realpath ./data):/root/AlphaPose/data [imagename] ./run.sh --indir=/root/AlphaPose/data/in/ --outdir=data/out
FROM nvidia/cuda:8.0-cudnn5-devel
# Supress warnings about missing front-end. As recommended at:
# http://stackoverflow.com/questions/22466255/is-it-possibe-to-answer-dialog-questions-when-installing-under-docker
ARG DEBIAN_FRONTEND=noninteractive
# Install some dependencies
RUN apt-get update && \
apt-get install -y \
apt-utils \
git \
curl \
unzip \
openssh-client \
wget \
build-essential \
cmake \
libboost-all-dev \
libffi-dev \
libfreetype6-dev \
libhdf5-dev \
libjpeg8-dev \
liblcms2-dev \
libopenblas-dev \
liblapack-dev \
libpng12-dev \
libssl-dev \
libtiff5-dev \
libwebp-dev \
libzmq3-dev \
nano \
pkg-config \
libavcodec-dev \
libavformat-dev \
libswscale-dev \
libtheora-dev \
libvorbis-dev \
libxvidcore-dev \
libx264-dev \
yasm \
libopencore-amrnb-dev \
libopencore-amrwb-dev \
libv4l-dev \
libxine2-dev \
libtbb-dev \
libeigen3-dev \
python3.5 \
python3.5-dev \
python3-pip \
python3-tk \
zlib1g-dev \
libprotobuf-dev \
libleveldb-dev \
libsnappy-dev \
libhdf5-serial-dev \
protobuf-compiler \
liblmdb-dev \
libgoogle-glog-dev \
&& \
apt-get clean && \
apt-get autoremove && \
rm -rf /var/lib/apt/lists/*
# python dependencies
RUN apt-get update && \
apt-get install -y python-pip && \
pip install --no-cache-dir --upgrade Cython numpy python-dateutil && \
apt-get clean && \
apt-get autoremove && \
rm -rf /var/lib/apt/lists/*
# alphapose deps
RUN cd /root && \
git clone --depth=1 https://github.com/MVIG-SJTU/AlphaPose.git && \
cd AlphaPose/human-detection/lib/ && \
make clean && \
make && \
cd newnms/ && \
make
# Tensorflow 1.2.1 - GPU
RUN pip install --no-cache-dir --upgrade \
"https://storage.googleapis.com/tensorflow/linux/gpu/tensorflow_gpu-1.2.1-cp27-none-linux_x86_64.whl"
# torch
RUN cd /root && \
git clone https://github.com/torch/distro.git /root/torch --recursive && \
cd /root/torch && \
sed -i 's/sudo\ //' install-deps && \
apt-get update && \
bash install-deps && \
./install.sh -b && \
apt-get install -y python-tk && \
apt-get clean && \
apt-get autoremove && \
rm -rf /var/lib/apt/lists/*
# get the exports (had to manually stop build here and read the below file)
# i'm sure there is a better and more automated way
# file: `cat /root/torch/install/bin/torch-activate`
ENV LUA_PATH='/root/.luarocks/share/lua/5.1/?.lua;/root/.luarocks/share/lua/5.1/?/init.lua;/root/torch/install/share/lua/5.1/?.lua;/root/torch/install/share/lua/5.1/?/init.lua;./?.lua;/root/torch/install/share/luajit-2.1.0-beta1/?.lua;/usr/local/share/lua/5.1/?.lua;/usr/local/share/lua/5.1/?/init.lua' \
LUA_CPATH='/root/.luarocks/lib/lua/5.1/?.so;/root/torch/install/lib/lua/5.1/?.so;./?.so;/usr/local/lib/lua/5.1/?.so;/usr/local/lib/lua/5.1/loadall.so' \
PATH="/root/torch/install/bin:$PATH" \
LD_LIBRARY_PATH="/root/torch/install/lib:$LD_LIBRARY_PATH" \
DYLD_LIBRARY_PATH="/root/torch/install/lib:$DYLD_LIBRARY_PATH" \
LUA_CPATH="/root/torch/install/lib/?.so;$LUA_CPATH"
# finish up alphapose
RUN luarocks install hdf5 && \
cd /root/AlphaPose && \
chmod +x install.sh && \
./install.sh
RUN pip install --upgrade pip
# Common libraries
RUN pip --no-cache-dir install \
Pillow scipy sklearn scikit-image pandas matplotlib requests pika h5py
RUN cd /root/AlphaPose && \
chmod +x fetch_models.sh && \
./fetch_models.sh
WORKDIR "/root/AlphaPose"
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