windows配置tensorflow python object detection 环境

最新推荐文章于 2023-09-18 17:55:42 发布

_iorilan

最新推荐文章于 2023-09-18 17:55:42 发布

阅读量821

点赞数 1

CC 4.0 BY-SA版权

分类专栏： Iori的工具箱 Python

本文链接：https://blog.youkuaiyun.com/lan_liang/article/details/104861898

Iori的工具箱同时被 2 个专栏收录

63 篇文章

订阅专栏

Python

41 篇文章

订阅专栏

本文提供两种安装TensorFlow的方法：使用pip直接安装预编译的二进制文件或通过Anaconda创建虚拟环境。针对CPU和GPU环境，详细步骤包括环境配置、依赖库安装及环境变量设置。

摘要生成于 C知道，由 DeepSeek-R1 满血版支持，前往体验 >

option 1: pip install <binary>

pip install --upgrade https://storage.googleapis.com/tensorflow/mac/cpu/tensorflow-1.12.0-py3-none-any.whl

option 2 : use anaconda

1.https://www.anaconda.com/distribution/
打开 anaconda command

--
配置 cpu 环境

conda create -n tensorflow_cpu pip python=3.6
activate tensorflow_cpu
pip install --ignore-installed --upgrade tensorflow==1.9

配置gpu环境
--
1.载 cuda
https://developer.nvidia.com/cuda-90-download-archive?target_os=Windows&target_arch=x86_64&target_version=10&target_type=exenetwork

2.install cudnn
https://developer.nvidia.com/rdp/cudnn-download

3.Select cuDNN v7.0.5 (Feb 28, 2018), for CUDA 9.0
4.下载 cuDNN v7.0.5 Library for Windows 10:
https://developer.nvidia.com/compute/machine-learning/cudnn/secure/v7.0.5/prod/9.0_20171129/cudnn-9.0-windows10-x64-v7

5. 环境变量

6. 编辑环境变量

7.添加路径

<INSTALL_PATH>\NVIDIA GPU Computing Toolkit\CUDA\v9.0\bin
<INSTALL_PATH>\NVIDIA GPU Computing Toolkit\CUDA\v9.0\libnvvp
<INSTALL_PATH>\NVIDIA GPU Computing Toolkit\CUDA\v9.0\extras\CUPTI\libx64
<INSTALL_PATH>\NVIDIA GPU Computing Toolkit\CUDA\v9.0\cuda\bin

conda create -n tensorflow_gpu pip python=3.6
activate tensorflow_gpu
pip install --ignore-installed --upgrade tensorflow-gpu==1.9