[Information] Requires Python 3.2-3.5 . Maybe 3.5 recommended.

[6DammK9]

If you have Python 2 only, you need to modify the scripts for the HTTP server.
Include it into readme if you want. Cheers!
...
(Copied from my own readme)

Requirement

If not specified, versions are assumed to be recent LTS version.

• A Nvidia graphic card supporting CUDA (6.5, 7.0, 7.5, 8.0)
• Linux: gcc/ g++ 4.8
• Windows: "Microsoft Visual C++ Build Tools 2015" (NOT "Microsoft Visual Studio Community 2015")
• Python 3 (3.5 recommended) (Python 2.7 needs modifying web host (at least) )
• Numpy
• Pillow
• openCV "cv2" (Python 3 support possible, see installation guide)
• Chainer
• CUDA / cuDNN

Installation Guide

Option: Docker user

If you have docker, you may check https://hub.docker.com/r/liamjones/paintschainer-docker/

Option: Fresh install

If not specified, follow instruction from their official website.

• Chainer/ Linux gcc: See http://docs.chainer.org/en/stable/install.html

• Microsoft Visual C++ Build Tools 2015: http://landinghub.visualstudio.com/visual-cpp-build-tools

• Python: https://www.python.org/downloads/

• Numpy: pip install numpy. Check installed version after that.

• Pillow: pip install pillow. 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 http://stackoverflow.com/questions/20953273/install-opencv-for-python-3-3 (Build from source)

• openCV (Anaconda): conda install -c menpo opencv3 (Pre-built libraries)

• Step by step guide for installing chainer (Windows):
  (Tested on Win10 64-bit, python 3.5)
  Step1: Install "Microsoft Visual C++ Build Tools". Uninstall "Visual Studio 2015" if you have it.
  Step2: Install "Nvidia CUDA"
  Step3: Register and download "NVIDIA Deep Learning SDK"
  Step4: 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": http://landinghub.visualstudio.com/visual-cpp-build-tools

[RikaKagurasaka]

I'm wondering how to install OpenCV for python 3.5. Pip seems not available.

[taizan]

Thanks for comments.
I ll update install guide later.

I used anaconda and conda install -c menpo opencv3 for openCV
( not normal alittle bit... ? )

[RikaKagurasaka]

Thanks. I'm looking forward to your guidance.

[6DammK9]

Updated progress. Now downloading the 1.2G CUDA + 12GB VS2015 for Win 10 64...

[6DammK9]

Update: Reinstalled chainer for multiple times with valid CUDA_PATH (CUDA 8.0 + VS 2015 installed), same error pops out. Not sure why is happens with even os.path.exists(os.environ["CUDA_PATH"]) returns true.
Will try @liamjones solution mentioned in issue #7 .

[sdygt]

@RikaSugisawa You can use prebuilt cv2 for Python3 here
(Thanks @solring in #9 )

[6DammK9]

Finally managed to open the server. This topic may be closed.
Created a pull request for readme,
Since it is kinda long so please decide where to put the information.

[taizan]

thanks for your a pull request