- Use staged container builds to improve caching and reduce size (#727)

* - Use staged container builds to improve caching and reduce size
- Image size reduced from 8 GB to 1.6ish
- Switched from Make to Ninja for faster builds that do not hog processor
- Removed unneded dependencies
- Added to .dockerignore
- Readme for docker stuff

- Staged Builds
    - Docker's overlay FS means that `rm`ing files does not reduce size
    - Once build artifacts are build, the build dependencies are no longer needed
    - Both of these can be solved by building in a temporary image and copying
    only the needed libraries in
    - Leverages DESTDIR to generate a directory structure that can be just
    copied onto the `/` of the filesystem
    - Similarly, the data files (like models) can be downloaded ahead of time
    into their own image and copied in. This saves on network IO.
    - Anything in a RUN directive that is non-deterministic (e.g. downloading
    a file from a link, the content of that link changes) does not cause a cache
    miss, so if you need to update something RUN uses, either modify the
    dockerfile or build with `--no-cache` to force a rebuild
- Switch to Ninja
    - cmake can generate many types of build systems
    - Ninja builds faster than GNU Make
    - `make -j` has a tendency to lock up my system when building locally
    - Do not need to tell ninja how many jobs to run
- .dockerignore
    - Paths in .dockerignore are basically invisible to dockerd, so when dockerd
    zips up the build context, all of the cruft can be ignored
    - it is beneficial to docker build speed to add any large, unnecssary files
    and directories to .dockerignore.
    - Just remember they cannot be seen by dockerd

* removing cruft and some format fixes

* updated dockerfile to opencv 4.1.0

.dockerignore

@@ -1,8 +1,10 @@
+.git
+docker-compose.yml
 build
 matlab_runners
 matlab_version
 python_scripts
 test-dump
 samples
 model_training
-gui
+gui

.env

@@ -0,0 +1,6 @@
+## This is read by docker-compose. You can overwrite these at runtime, e.g.:
+## DOCKERUSER=bobfoo docker-compose build
+
+DOCKERUSER=openface
+DOCKERTAG=latest
+DATA_MOUNT=/tmp/openface

.gitignore

@@ -1,3 +1,5 @@
+lib/local/LandmarkDetector/model/patch_experts/cen_patches_*.dat
+
 matlab_version/experiments_menpo/out_semifrontal/
 /x64/Release/
 /x64/Debug/
@@ -100,3 +102,6 @@ lib/local/Utilities/Debug/
 lib/3rdParty/CameraEnumerator/Debug/
 lib/local/CppInerop/Debug/
 *.user
+
+# IDE-generated folders
+.idea

CMakeLists.txt

@@ -138,7 +138,7 @@ endforeach()
 if (${CMAKE_CXX_COMPILER_ID} STREQUAL "GNU")
  execute_process(COMMAND ${CMAKE_CXX_COMPILER} -dumpversion OUTPUT_VARIABLE GCC_VERSION)
  if (GCC_VERSION VERSION_LESS 8.0)
- MESSAGE(FATAL_ERROR "Need a 8.0 or newer GCC compiler ${GCC_VERSION}") 
+ MESSAGE(FATAL_ERROR "Need a 8.0 or newer GCC compiler. Current GCC: ${GCC_VERSION}")
  else ()
  set (CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -msse -msse2 -msse3")
  endif ()

docker-compose.yml

@@ -0,0 +1,24 @@
+---
+# Variables can be set from the shell: `DOCKERTAG=foo docker-compose build`
+# or from a .env file. See docker-compose documentation for details
+# Variable DOCKERUSER should be set to your dockerhub user
+# Alternatively, use a docker registry url as the image name
+version: '3.7'
+services:
+ ## Image runtime service
+ ## This can be used to add volume mounts or pass environment variables
+ ## Todo: make a service which can use the container interactively
+ openface:
+ container_name: openface
+ build:
+ context: .
+ dockerfile: docker/Dockerfile
+ image: "${DOCKERUSER}/openface:${DOCKERTAG}"
+ tty: true
+ volumes:
+ - "${DATA_MOUNT}:${DATA_MOUNT}"
+ environment:
+ DATA_MOUNT: "${DATA_MOUNT}"
+ command: ["bash"]
+
+...

docker/Dockerfile

@@ -0,0 +1,110 @@
+# ==================== Building Model Layer ===========================
+# This is a little trick to improve caching and minimize rebuild time
+# and bandwidth. Note that RUN commands only cache-miss if the prior layers
+# miss, or the dockerfile changes prior to this step.
+# To update these patch files, be sure to run build with --no-cache
+FROM alpine as model_data
+RUN apk --no-cache --update-cache add wget
+WORKDIR /data/patch_experts
+
+RUN wget -q https://www.dropbox.com/s/7na5qsjzz8yfoer/cen_patches_0.25_of.dat &&\
+ wget -q https://www.dropbox.com/s/k7bj804cyiu474t/cen_patches_0.35_of.dat &&\
+ wget -q https://www.dropbox.com/s/ixt4vkbmxgab1iu/cen_patches_0.50_of.dat &&\
+ wget -q https://www.dropbox.com/s/2t5t1sdpshzfhpj/cen_patches_1.00_of.dat
+
+## ==================== Install Ubuntu Base libs ===========================
+## This will be our base image for OpenFace, and also the base for the compiler
+## image. We only need packages which are linked
+
+FROM ubuntu:18.04 as ubuntu_base
+
+LABEL maintainer="Michael McDermott <[email protected]>"
+
+ARG DEBIAN_FRONTEND=noninteractive
+
+# todo: minimize this even more
+RUN apt-get update -qq &&\
+ apt-get install -qq curl &&\
+ apt-get install -qq --no-install-recommends \
+ libopenblas-dev liblapack-dev \
+ libavcodec-dev libavformat-dev libswscale-dev \
+ libtbb2 libtbb-dev libjpeg-dev \
+ libpng-dev libtiff-dev &&\
+ rm -rf /var/lib/apt/lists/*
+
+## ==================== Build-time dependency libs ======================
+## This will build and install opencv and dlib into an additional dummy
+## directory, /root/diff, so we can later copy in these artifacts,
+## minimizing docker layer size
+## Protip: ninja is faster than `make -j` and less likely to lock up system
+FROM ubuntu_base as cv_deps
+
+WORKDIR /root/build-dep
+ARG DEBIAN_FRONTEND=noninteractive
+
+RUN apt-get update -qq && apt-get install -qq -y \
+ cmake ninja-build pkg-config build-essential checkinstall\
+ g++-8 &&\
+ rm -rf /var/lib/apt/lists/* &&\
+ update-alternatives --install /usr/bin/gcc gcc /usr/bin/gcc-8 800 --slave /usr/bin/g++ g++ /usr/bin/g++-8
+
+## llvm clang-3.7 libc++-dev libc++abi-dev \
+## ==================== Building dlib ===========================
+
+RUN curl http://dlib.net/files/dlib-19.13.tar.bz2 -LO &&\
+ tar xf dlib-19.13.tar.bz2 && \
+ rm dlib-19.13.tar.bz2 &&\
+ mv dlib-19.13 dlib &&\
+ mkdir -p dlib/build &&\
+ cd dlib/build &&\
+ cmake -DCMAKE_BUILD_TYPE=Release -G Ninja .. &&\
+ ninja && \
+ ninja install && \
+ DESTDIR=/root/diff ninja install &&\
+ ldconfig
+
+## ==================== Building OpenCV ======================
+ENV OPENCV_VERSION=4.1.0
+
+RUN curl https:/opencv/opencv/archive/${OPENCV_VERSION}.tar.gz -LO &&\
+ tar xf ${OPENCV_VERSION}.tar.gz && \
+ rm ${OPENCV_VERSION}.tar.gz &&\
+ mv opencv-${OPENCV_VERSION} opencv && \
+ mkdir -p opencv/build && \
+ cd opencv/build && \
+ cmake -D CMAKE_BUILD_TYPE=RELEASE \
+ -D CMAKE_INSTALL_PREFIX=/usr/local \
+ -D WITH_TBB=ON -D WITH_CUDA=OFF \
+ -DWITH_QT=OFF -DWITH_GTK=OFF\
+ -G Ninja .. && \
+ ninja && \
+ ninja install &&\
+ DESTDIR=/root/diff ninja install
+
+## ==================== Building OpenFace ===========================
+FROM cv_deps as openface
+WORKDIR /root/openface
+
+COPY ./ ./
+
+COPY --from=model_data /data/patch_experts/* \
+ /root/openface/lib/local/LandmarkDetector/model/patch_experts/
+
+RUN mkdir -p build && cd build && \
+ cmake -D CMAKE_BUILD_TYPE=RELEASE -G Ninja .. && \
+ ninja &&\
+ DESTDIR=/root/diff ninja install
+
+
+## ==================== Streamline container ===========================
+## Clean up - start fresh and only copy in necessary stuff
+## This shrinks the image from ~8 GB to ~1.6 GB
+FROM ubuntu_base as final
+
+WORKDIR /root
+
+# Copy in only necessary libraries
+COPY --from=openface /root/diff /
+
+# Since we "imported" the build artifacts, we need to reconfigure ld
+RUN ldconfig

docker/README.md

@@ -0,0 +1,57 @@
+# Docker building instructions
+
+This image can be build with just `docker`, but it is highly recommend to use 
+`docker-compose` as this greatly simplifies and improves the process. 
+
+## Quick start
+
+To start with the container hosted by the repo maintainer, run 
+
+`docker run -it --rm --name openface algebr/openface:latest`
+
+This will drop you into a shell with binaries such as FaceLandmarkImg. For example,
+try this code (in the container):
+
+```bash
+curl -o tesla.jpg https://upload.wikimedia.org/wikipedia/commons/thumb/b/b7/Nicola_Tesla_LCCN2014684845.jpg/559px-Nicola_Tesla_LCCN2014684845.jpg 
+FaceLandmarkImg -f tesla.jpg
+```
+
+Then, copy the output to the host system (from host terminal):
+
+```bash
+docker cp openface:/root/processed /tmp/
+cd /tmp/processed
+```
+
+Tip: On Ubuntu and other *nixes with X running, you can open a file directly 
+like this:
+```bash
+xdg-open /tmp/processed/tesla.jpg
+``` 
+
+## Building
+
+In repo root, run `docker-compose build` to automatically build and tag. 
+There are two variables which can be used to modify the tag, `$DOCKERUSER` and
+`$DOCKERTAG`. DC will automatically tag image as 
+`${DOCKERUSER}/openface:${DOCKERTAG}`
+
+## OpenFace service (in progress)
+
+To run OpenFace like a service, you can start the container with bind mounts 
+in order to pass data into and out of the container easily. 
+`$DATA_MOUNT` by default is set to `/tmp/openface`. This can be overridden by 
+modifying `.env` file, setting it in your shell environment, or passing in 
+before `docker-compose` at runtime. Note: output will be `root` owner. 
+
+```bash
+export DATA_MOUNT=/tmp/openface
+mkdir -p $DATA_MOUNT/tesla # this is just to ensure this is writable by user
+docker-compose up -d openface && sync # sync is to wait till service starts
+curl -o $DATA_MOUNT/tesla.jpg \
+ https://upload.wikimedia.org/wikipedia/commons/thumb/b/b7/Nicola_Tesla_LCCN2014684845.jpg/559px-Nicola_Tesla_LCCN2014684845.jpg
+docker exec -it openface FaceLandmarkImg -f $DATA_MOUNT/tesla.jpg -out_dir $DATA_MOUNT/tesla
+docker exec -it openface chown -R $UID:$UID $DATA_MOUNT # chown to current user
+docker-compose down # stop service if you wish
+```