If you have docker, you may check https://hub.docker.com/r/liamjones/paintschainer-docker/ (not supported officially but thanks for volunteering)

If not specified, follow instruction from their official website.

• Chainer/ Linux gcc: See https://docs.chainer.org/en/stable/install.html
• Microsoft Visual C++ Build Tools 2015 (Windows): See https://landinghub.visualstudio.com/visual-cpp-build-tools
• Python: See https://www.python.org/downloads/
• Numpy: pip install numpy. Check installed version after that.
• openCV (Windows): See https://www.solarianprogrammer.com/2016/09/17/install-opencv-3-with-python-3-on-windows/ (Pre-built libraries)
• openCV (Linux): See https://stackoverflow.com/questions/20953273/install-opencv-for-python-3-3 (Build from source)
• openCV (Anaconda): conda install -c menpo opencv3 (Pre-built libraries)

• Step1: Install "Microsoft Visual C++ Build Tools". Uninstall "Visual Studio 2015" if you have it. (You can install VS2015 after this step)
• Step2: Install "Nvidia CUDA"
• Step3: Register and download "NVIDIA CUDA Deep Neural Network library (cuDNN)" (See https://developer.nvidia.com/cudnn)
• Step4: Extract, copy and paste the files in to installed CUDA folder (e.g. C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v8.0\)
• Step5: pip install chainer --no-cache-dir -vvvv (<- Do this AT LAST!)

If you failed to perform the following steps, you will see this message. Uninstall chainer and install it again.

 Running command python setup.py egg_info
    Options: {'profile': False, 'annotate': False, 'linetrace': False, 'no_cuda': False}
    Include directories: ['C:\\Program Files\\NVIDIA GPU Computing Toolkit\\CUDA\\v8.0\\include']
    Library directories: ['C:\\Program Files\\NVIDIA GPU Computing Toolkit\\CUDA\\v8.0\\bin', 'C:\\Program Files\\NVIDIA GPU Computing Toolkit\\CUDA\\v8.0\\lib\\x64']
    Microsoft Visual C++ 14.0 is required. Get it with "Microsoft Visual C++ Build Tools": https://landinghub.visualstudio.com/visual-cpp-build-tools

• Step1: Install "Visual Studio 2015"
• Step2: Install "Anaconda 3" and run conda update anaconda
• Step3: Install "Nvidia CUDA"
• Step4: Register and download "NVIDIA CUDA Deep Neural Network library (cuDNN)" (See https://developer.nvidia.com/cudnn)`
• Step5: Unzip cudnn-*-windows*-x64-v**.zip to any folder
• Step6: Add a new bat file run.bat in cudnn\cuda folder, and edit it
• Step7: Start run.bat
• Step8: pip install chainer --no-cache-dir -vvvv (<- Do this AT LAST!)

Next time when you want to start web host, you can start run.bat.

• run.bat

@echo off
REM You maybe need to edit following two line
SET PaintsChainer_PATH=K:\proj\PaintsChainer
SET Anaconda3_PATH=E:\Anaconda3
SET path=%~dp0;%~dp0bin;%path%
call "C:\Program Files (x86)\Microsoft Visual Studio 14.0\VC\vcvarsall.bat" amd64
SET LIB=%~dp0lib;%~dp0lib\x64;%LIB%
SET INCLUDE=%~dp0include;%INCLUDE%
SET LIBPATH=%~dp0lib;%~dp0lib\x64;%LIBPATH%
cd /d %PaintsChainer_PATH%
start %Anaconda3_PATH%\Scripts\activate.bat