py-faster-rcnn:在windows上配置

0.先说一下本机配置

opencv2+cuda7.5+cudnn+anaconda，这些基础的之前都是配置好了的，python环境建议使用anaconda，用到的库基本都有了，好像没有easydict,自己装一下就好。

1.下载py-faster-rcnn

rbg大神github上的py-faster-rcnn
使用以下命令下载，直接download的话不完整

git clone --recursive https://github.com/rbgishick/py-faster-rcnn.git

2.编译lib

因为原版是在linux中使用的，在linux里可以直接编译，在windows下需要修改lib/setup.py，以下是修改后的

# --------------------------------------------------------
# Fast R-CNN
# Copyright (c) 2015 Microsoft
# Licensed under The MIT License [see LICENSE for details]
# Written by Ross Girshick
# --------------------------------------------------------

import numpy as np
import os
from os.path import join as pjoin
#from distutils.core import setup
from setuptools import setup
from distutils.extension import Extension
from Cython.Distutils import build_ext
import subprocess

#change for windows, by MrX
nvcc_bin = 'nvcc.exe'
lib_dir = 'lib/x64'

def find_in_path(name, path):
    "Find a file in a search path"
    # Adapted fom
    # http://code.activestate.com/recipes/52224-find-a-file-given-a-search-path/
    for dir in path.split(os.pathsep):
        binpath = pjoin(dir, name)
        if os.path.exists(binpath):
            return os.path.abspath(binpath)
    return None


def locate_cuda():
    """Locate the CUDA environment on the system

    Returns a dict with keys 'home', 'nvcc', 'include', and 'lib64'
    and values giving the absolute path to each directory.

    Starts by looking for the CUDAHOME env variable. If not found, everything
    is based on finding 'nvcc' in the PATH.
    """

    # first check if the CUDAHOME env variable is in use
    if 'CUDA_PATH' in os.environ:
        home = os.environ['CUDA_PATH']
        print("home = %s\n" % home)
        nvcc = pjoin(home, 'bin', nvcc_bin)
    else:
        # otherwise, search the PATH for NVCC
        default_path = pjoin(os.sep, 'usr', 'local', 'cuda', 'bin')
        nvcc = find_in_path(nvcc_bin, os.environ['PATH'] + os.pathsep + default_path)
        if nvcc is None:
            raise EnvironmentError('The nvcc binary could not be '
                'located in your $PATH. Either add it to your path, or set $CUDA_PATH')
        home = os.path.dirname(os.path.dirname(nvcc))
        print("home = %s, nvcc = %s\n" % (home, nvcc))


    cudaconfig = {'home':home, 'nvcc':nvcc,
                  'include': pjoin(home, 'include'),
                  'lib64': pjoin(home, lib_dir)}
    for k, v in cudaconfig.iteritems():
        if not os.path.exists(v):
            raise EnvironmentError('