Dockerfile.gpu alongside CPU based Dockerfile

Dockerfile

 # This is a sample Dockerfile you can modify to deploy your own app based on face_recognition
-# In order to run Docker in the GPU you will need to install nvidia-docker: https://github.com/NVIDIA/nvidia-docker
 
-FROM nvidia/cuda:9.0-cudnn7-devel
-
-# Install face recognition dependencies
-
-RUN apt update -y; apt install -y \
-git \
-cmake \
-libsm6 \
-libxext6 \
-libxrender-dev \
-python3 \
-python3-pip
-
-RUN pip3 install scikit-build
-
-# Install compilers
-
-RUN apt install -y software-properties-common
-RUN add-apt-repository ppa:ubuntu-toolchain-r/test
-RUN apt update -y; apt install -y gcc-6 g++-6
-
-RUN update-alternatives --install /usr/bin/gcc gcc /usr/bin/gcc-6 50
-RUN update-alternatives --install /usr/bin/g++ g++ /usr/bin/g++-6 50
-
-#Install dlib 
-
-RUN git clone https://github.com/davisking/dlib.git
-RUN mkdir -p /dlib/build
-
-RUN cmake -H/dlib -B/dlib/build -DDLIB_USE_CUDA=1 -DUSE_AVX_INSTRUCTIONS=1
-RUN cmake --build /dlib/build
-
-RUN cd /dlib; python3 /dlib/setup.py install --yes USE_AVX_INSTRUCTIONS --yes DLIB_USE_CUDA
-
-# Install the face recognition package
-
-RUN pip3 install face_recognition
+FROM python:3.6-slim-stretch
+
+RUN apt-get -y update
+RUN apt-get install -y --fix-missing \
+    build-essential \
+    cmake \
+    gfortran \
+    git \
+    wget \
+    curl \
+    graphicsmagick \
+    libgraphicsmagick1-dev \
+    libatlas-dev \
+    libavcodec-dev \
+    libavformat-dev \
+    libgtk2.0-dev \
+    libjpeg-dev \
+    liblapack-dev \
+    libswscale-dev \
+    pkg-config \
+    python3-dev \
+    python3-numpy \
+    software-properties-common \
+    zip \
+    && apt-get clean && rm -rf /tmp/* /var/tmp/*
+
+RUN cd ~ && \
+    mkdir -p dlib && \
+    git clone -b 'v19.9' --single-branch https://github.com/davisking/dlib.git dlib/ && \
+    cd  dlib/ && \
+    python3 setup.py install --yes USE_AVX_INSTRUCTIONS
+
+
+# The rest of this file just runs an example script.
+
+# If you wanted to use this Dockerfile to run your own app instead, maybe you would do this:
+# COPY . /root/your_app_or_whatever
+# RUN cd /root/your_app_or_whatever && \
+#     pip3 install -r requirements.txt
+# RUN whatever_command_you_run_to_start_your_app
+
+COPY . /root/face_recognition
+RUN cd /root/face_recognition && \
+    pip3 install -r requirements.txt && \
+    python3 setup.py install
+
+CMD cd /root/face_recognition/examples && \
+    python3 recognize_faces_in_pictures.py
\ No newline at end of file

Dockerfile.gpu

+# This is a sample Dockerfile you can modify to deploy your own app based on face_recognition on the GPU
+# In order to run Docker in the GPU you will need to install Nvidia-Docker: https://github.com/NVIDIA/nvidia-docker
+
+FROM nvidia/cuda:9.0-cudnn7-devel
+
+# Install face recognition dependencies
+
+RUN apt update -y; apt install -y \
+git \
+cmake \
+libsm6 \
+libxext6 \
+libxrender-dev \
+python3 \
+python3-pip
+
+RUN pip3 install scikit-build
+
+# Install compilers
+
+RUN apt install -y software-properties-common
+RUN add-apt-repository ppa:ubuntu-toolchain-r/test
+RUN apt update -y; apt install -y gcc-6 g++-6
+
+RUN update-alternatives --install /usr/bin/gcc gcc /usr/bin/gcc-6 50
+RUN update-alternatives --install /usr/bin/g++ g++ /usr/bin/g++-6 50
+
+#Install dlib 
+
+RUN git clone https://github.com/davisking/dlib.git
+RUN mkdir -p /dlib/build
+
+RUN cmake -H/dlib -B/dlib/build -DDLIB_USE_CUDA=1 -DUSE_AVX_INSTRUCTIONS=1
+RUN cmake --build /dlib/build
+
+RUN cd /dlib; python3 /dlib/setup.py install --yes USE_AVX_INSTRUCTIONS --yes DLIB_USE_CUDA
+
+# Install the face recognition package
+
+RUN pip3 install face_recognition

README.md

@@ -371,7 +371,7 @@ to any service that supports Docker images.
 
 You can try the Docker image locally by running: `docker-compose up`
 
-If you don't have nvidia-docker installed or a GPU, remove the last line in the [docker-compose.yml](docker-compose.yml) file (`runtime: nvidia`).
+Linux users with a GPU and [Nvidia-Docker](https://github.com/NVIDIA/nvidia-docker) installed can run the example on the GPU: Open the [docker-compose.yml](docker-compose.yml) file and uncomment the `dockerfile: Dockerfile.gpu` and `runtime: nvidia` lines.
 
 ## Having problems?
 

docker-compose.yml

@@ -7,7 +7,10 @@ services:
     working_dir: /face_recognition/examples
     build:
       context: .
+      #Uncomment this line to run the example on the GPU (requires Nvidia-Docker)
+      # dockerfile: Dockerfile.gpu 
     command: python3 -u find_faces_in_picture_cnn.py
     volumes:
       - ./:/face_recognition
-    runtime: nvidia #Comment this line if you don't have nvidia-docker installed (requires GPU)
\ No newline at end of file
+    #Uncomment this line to run the example on the GPU (requires Nvidia-Docker)
+    # runtime: nvidia
\ No newline at end of file