Building development environment

There two main approaches to build development environment:

Configure local computer environment
Create a Docker image and container

Building development environment with Docker

Build Docker image.

cd env_scripts
docker build -t buildenv:1.0 .

Run the Docker container and build third party libaries there.

docker run -it buildenv:1.0 bash
cd /development
./install_env.sh
./install_android.sh

Identify active container ID (the following commands can be executed in the separate console session).
```
docker container ls
```
remember the container ID.
Save the container as new a image.
```
docker commit [container id]
```
Identify new image ID.
```
docker image ls
```
remember the image ID.
Give the name for the new image.
```
docker tag [image id] buildenv_libs`
```
Stop the initial container in the original console session.
```
exit
```

Run a new container from the created image, and share code samples folder.

docker run -it -v [host_samples_path]:[container_samples_path] buildenv_libs bash

Samples from chapter 2 require accsess to your graphical environment to show images. You can share you X11 server with a Docker container. The following script shows how to run a container with graphics environment:
```
xhost +local:root
docker run --net=host -e DISPLAY=$DISPLAY -v /tmp/.X11-unix:/tmp/.X11-unix -it -v [host_samples_path]:[container_samples_path] buildenv_libs bash
```
In the started container console session navigate to the container_samples_path\build_scripts folder. You will find there scripts to build samples for each chapter. The following script shows how to build samples for chapter 1:
```
./build_ch1.sh
```

Building local development environment

Install Ubuntu 18.04

Run the following commands to configure the system:

apt-get install -y build-essential
apt-get install -y gdb
apt-get install -y git
apt-get install -y cmake
apt-get install -y cmake-curses-gui
apt-get install -y python
apt-get install -y python-pip
apt-get install -y libblas-dev
apt-get install -y libopenblas-dev
apt-get install -y libatlas-base-dev
apt-get install -y liblapack-dev
apt-get install -y libboost-all-dev
apt-get install -y libopencv-core3.2
apt-get install -y libopencv-imgproc3.2
apt-get install -q -y libopencv-dev
apt-get install -y libopencv-highgui3.2
apt-get install -y libopencv-highgui-dev
apt-get install -y libhdf5-dev
apt-get install -y libjson-c-dev
apt-get install -y libx11-dev
apt-get install -y openjdk-8-jdk
apt-get install -y wget
apt-get install -y ninja-build
apt-get install -y gnuplot
apt-get install -y vim
apt-get install -y python3-venv
pip install pyyaml
RUN pip install typing

Create build environment with the following commands (We assume that the path "/path/to/examples/package/" contains extracted code samples package):

cd ~/
mkdir development
cd ~/development
cp /path/to/examples/package/docker/checkout_lib.sh ~/development
cp /path/to/examples/package/docker/install_lib.sh ~/development
cp /path/to/examples/package/docker/install_env.sh ~/development
cp /path/to/examples/package/docker/install_android.sh ~/development
chmod 777 ~/development/checkout_lib.sh
chmod 777 ~/development/install_lib.sh
chmod 777 ~/development/install_env.sh
chmod 777 ~/development/install_android.sh
./install_env.sh
./android_env.sh

All third party libraries will be installed into the following directory:
```
$HOME/development/libs
```
Navigate to the /path/to/examples/package/build_scripts folder.
Choose the build script for the chapter you want to build, for example build script for the first chapter is build_ch1.sh
Updated the LIBS_DIR varibale in the script with the $HOME/development/libs value, or another one but it should the folder where all third party libraries are installed.
Run the build script to compile samples for the selected chapter.

List of all third-party libraries

Name - commit hash - branch name - repository

Shogun - f7255cf2cc6b5116e50840816d70d21e7cc039bb - master - https://github.com/shogun-toolbox/shogun

SharkML - 221c1f2e8abfffadbf3c5ef7cf324bc6dc9b4315 - master - https://github.com/Shark-ML/Shark

Armadillo - 442d52ba052115b32035a6e7dc6587bb6a462dec- branch 9.500.x - https://gitlab.com/conradsnicta/armadillo-code

DLib - 929c630b381d444bbf5d7aa622e3decc7785ddb2 - v19.15 - https://github.com/davisking/dlib

Eigen - cf794d3b741a6278df169e58461f8529f43bce5d - 3.3.7 - https://github.com/eigenteam/eigen-git-mirror

mlpack - e2f696cfd5b7ccda2d3af1c7c728483ea6591718 - master - https://github.com/mlpack/mlpack

plotcpp - c86bd4f5d9029986f0d5f368450d79f0dd32c7e4 - master - https://github.com/Kolkir/plotcpp

PyTorch - 8554416a199c4cec01c60c7015d8301d2bb39b64 - v1.2.0 - https://github.com/pytorch/pytorch

xtensor - 02d8039a58828db1ffdd2c60fb9b378131c295a2 - master - https://github.com/xtensor-stack/xtensor

xtensor-blas - 89d9df93ff7306c32997e8bb8b1ff02534d7df2e - master - https://github.com/xtensor-stack/xtensor-blas

xtl - 03a6827c9e402736506f3ded754e890b3ea28a98 - master - https://github.com/xtensor-stack/xtl

OpenCV 3 - from the distribution installation package - https://github.com/opencv/opencv_contrib/releases/tag/3.3.0

fast-cpp-csv-parser - 3b439a664090681931c6ace78dcedac6d3a3907e - master - https://github.com/ben-strasser/fast-cpp-csv-parser

RapidJson - 73063f5002612c6bf64fe24f851cd5cc0d83eef9 - master - https://github.com/Tencent/rapidjson