Windows环境下使用tensorflow opencv的小事儿

安装

一、anaconda+tensorflow+opencv+spyder

二、python+tensorflow+opencv+pycharm

三、python3.5+tensorflow-gpu1.3+cuda8.0+cudnn6.0

这两种方式我都尝试过了，第一种方式推荐一个博主的，写的很详细，能走通，但是要的时间很长，需要下很多东西，所以我用的第二种，因为时间比较赶

ananconda+tensorflow安装：https://blog.csdn.net/weixin_37669436/article/details/71392905

anaconda+opencv安装：https://blog.csdn.net/zstarwalker/article/details/72855781

第二种首先下载python3.5.exe ：https://www.python.org/downloads/release/python-350/

记得要add python3.5.25 to path 

其他的就默认就好，完成后Win+r输入cmd 键入python查看安装版本

安装tensorflow隔了几天了有些问题可能记不清了，就写个大概的，如果大家安装遇到问题，给我留言，我会回的

第一种是pip install tensorflow 

要求是装了pip 还可能会遇到一个更新pip的问题，这个很好解决的，不知道大家能不能看懂命令行的提示，一般在一个问题出来了以后它会给你提供解决方案，按照他给的指令输入就好了，如果出现什么提交到github 这种提示，这个问题我也就解决不了了

这方式存在一个问题是安装包都是在线上下，可能出现下不下来，网络中断这样的情况

第二种 安装镜像文件，cd到镜像文件在的目录，运行镜像文件，可以下下来，也可以在线安装，我是下下来的，网址我找不到了一会儿给个百度网盘的地址分享出来吧

运行命令是 pip install *.whl

安装opencv

要装很多的包  numpy scipy, matplotlib, opencv,...

所以我装的镜像文件

我都分享到网盘里，有问题找我

网盘连接是https://pan.baidu.com/s/1815k5DT_p88FRC-gmJ-1cw  没有密码，里面是python3.5的安装包，tensorflow的镜像文件、opencv3的镜像文件

我写的可能不是很详细，不过你不会装或者安装遇到什么问题可以找我，因为在这个里面爬了一个星期，希望可以减少大家的问题

 三、python3.5+tensorflow-gpu1.3+cuda8.0+cudnn6.0

注意问题：版本对应

cuda下载地址，可选择版本

https://developer.nvidia.com/cuda-toolkit-archive

cubnn下载地址，可以选择版本，需要注册，填写问卷调查，这是正常的，

https://developer.nvidia.com/rdp/cudnn-archive

cuda安装完成以后，将cubnn压缩包里的文件放到cuda安装地址对应的包里面，即bin对应bin include对应clude  lib对应lib，拷贝文件到相应的地址

cuda默认安装的地址是 C:Program FilesNVIDIA GPU Computing ToolkitCUDA

tensorflow1.3 更新  命令

pip install --upgrade https://mirrors.tuna.tsinghua.edu.cn/tensorflow/windows/gpu/tensorflow_gpu-1.3.0rc0-cp35-cp35m-win_amd64.whl

win10系统相关安装包分享：https://pan.baidu.com/s/11y7HIZwJ_JQxpikplmnuVg

 通过运行如下文件查看是否安装成功

# -*- coding:utf-8-*-
import ctypes
import imp
import sys


def main():
    try:
        import tensorflow as tf
        print("TensorFlow successfully installed.")
        if tf.test.is_built_with_cuda():
            print("The installed version of TensorFlow includes GPU support.")
        else:
            print("The installed version of TensorFlow does not include GPU support.")
        sys.exit(0)
    except ImportError:
        print("ERROR: Failed to import the TensorFlow module.")

    candidate_explanation = False

    python_version = sys.version_info.major, sys.version_info.minor
    print("
- Python version is %d.%d." % python_version)
    if not (python_version == (3, 5) or python_version == (3, 6)):
        candidate_explanation = True
        print("- The official distribution of TensorFlow for Windows requires "
              "Python version 3.5 or 3.6.")

    try:
        _, pathname, _ = imp.find_module("tensorflow")
        print("
- TensorFlow is installed at: %s" % pathname)
    except ImportError:
        candidate_explanation = False
        print("""  
- No module named TensorFlow is installed in this Python environment. You may  
  install it using the command `pip install tensorflow`.""")

    try:
        msvcp140 = ctypes.WinDLL("msvcp140.dll")
    except OSError:
        candidate_explanation = True
        print("""  
- Could not load 'msvcp140.dll'. TensorFlow requires that this DLL be  
  installed in a directory that is named in your %PATH% environment  
  variable. You may install this DLL by downloading Microsoft Visual  
  C++ 2015 Redistributable Update 3 from this URL:  
  https://www.microsoft.com/en-us/download/details.aspx?id=53587""")

    try:
        cudart64_80 = ctypes.WinDLL("cudart64_80.dll")
    except OSError:
        candidate_explanation = True
        print("""  
- Could not load 'cudart64_80.dll'. The GPU version of TensorFlow  
  requires that this DLL be installed in a directory that is named in  
  your %PATH% environment variable. Download and install CUDA 8.0 from  
  this URL: https://developer.nvidia.com/cuda-toolkit""")

    try:
        nvcuda = ctypes.WinDLL("nvcuda.dll")
    except OSError:
        candidate_explanation = True
        print("""  
- Could not load 'nvcuda.dll'. The GPU version of TensorFlow requires that  
  this DLL be installed in a directory that is named in your %PATH%  
  environment variable. Typically it is installed in 'C:WindowsSystem32'.  
  If it is not present, ensure that you have a CUDA-capable GPU with the  
  correct driver installed.""")

    cudnn5_found = False
    try:
        cudnn5 = ctypes.WinDLL("cudnn64_5.dll")
        cudnn5_found = True
    except OSError:
        candidate_explanation = True
        print("""  
- Could not load 'cudnn64_5.dll'. The GPU version of TensorFlow  
  requires that this DLL be installed in a directory that is named in  
  your %PATH% environment variable. Note that installing cuDNN is a  
  separate step from installing CUDA, and it is often found in a  
  different directory from the CUDA DLLs. You may install the  
  necessary DLL by downloading cuDNN 5.1 from this URL:  
  https://developer.nvidia.com/cudnn""")

    cudnn6_found = False
    try:
        cudnn = ctypes.WinDLL("cudnn64_6.dll")
        cudnn6_found = True
    except OSError:
        candidate_explanation = True

    if not cudnn5_found or not cudnn6_found:
        print()
        if not cudnn5_found and not cudnn6_found:
            print("- Could not find cuDNN.")
        elif not cudnn5_found:
            print("- Could not find cuDNN 5.1.")
        else:
            print("- Could not find cuDNN 6.")
            print("""  
  The GPU version of TensorFlow requires that the correct cuDNN DLL be installed  
  in a directory that is named in your %PATH% environment variable. Note that  
  installing cuDNN is a separate step from installing CUDA, and it is often  
  found in a different directory from the CUDA DLLs. The correct version of  
  cuDNN depends on your version of TensorFlow:  

  * TensorFlow 1.2.1 or earlier requires cuDNN 5.1. ('cudnn64_5.dll')  
  * TensorFlow 1.3 or later requires cuDNN 6. ('cudnn64_6.dll')  

  You may install the necessary DLL by downloading cuDNN from this URL:  
  https://developer.nvidia.com/cudnn""")

    if not candidate_explanation:
        print("""  
- All required DLLs appear to be present. Please open an issue on the  
  TensorFlow GitHub page: https://github.com/tensorflow/tensorflow/issues""")

    sys.exit(-1)


if __name__ == "__main__":
    main()




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原文地址：https://www.cnblogs.com/html-css-js/p/8834623.html