python 大杂烩
Python 环境大杂烩
https://tensorflow.google.cn/install/source?hl=zh_cn http://hpc.pku.edu.cn/_book/guide/soft/case/case/vasp.html https://blog.csdn.net/Mr_Cat123/article/details/82993357 yum install python3-dev python3-pip python3-venv yum install zlib-devel bzip2-devel openssl-devel ncurses-devel sqlite-devel readline-devel tk-devel gdbm-devel db4-devel libpcap-devel xz-devel 设置pip 加速 http://www.zyglz.com/index.php/archives/18.html -------------------------------------------------------------------------------------- mkdir ~/.pip cat > ~/.pip/pip.conf << EOF [global] trusted-host=mirrors.aliyun.com index-url=https://mirrors.aliyun.com/pypi/simple/ EOF -------------------------------------------------------------------------------------- 阿里云源：https://mirrors.aliyun.com/pypi/simple 腾讯云源：https://mirrors.cloud.tencent.com/pypi/simple 豆瓣源：https://pypi.doubanio.com/simple 清华源：https://pypi.tuna.tsinghua.edu.cn/simple 华为源：https://repo.huaweicloud.com/simple ./configure --prefix=/usr/local/mpich make && make install python -m pip install --upgrade pip pip 卸载全部包 pip freeze pip freeze > packages.txt pip uninstall -r packages.txt -y pip install -r packages.txt pip 安装依赖 2.生成requirements.txt文件： 3.安装requirements.txt依赖： pip freeze > requirements.txt pip install -r requirements.txt pip 指定包的目录 方法一 指定安装numpy包到固定文件夹下，比如这里“文件夹”是安装路径 pip install -t 文件夹 numpy 方法2 查看目录 python -m site 打开 \Programs\Python\Python37\Lib\ 修改 USER_SITE 和 USER_BASE 两个字段的值(之前是null). #自定义依赖安装包的路径 USER_SITE = null #自定义的启用Python脚本的路径 USER_BASE = null 我这里修改为 USER_SITE = "D:\program\Anaconda\envs\py36\Lib\site-packages" USER_BASE = "D:\program\Anaconda\envs\py36\Scripts" 验证 python -m site 1.安装 Anaconda-Clean package 打开 Anaconda Prompt， 输入以下命令： conda install anaconda-clean 输入以下命令卸载 anaconda-clean --yes 经过 Solution A 的方式卸载。
Conda 环境
yum install python3-dev python3-pip python3-venv yum install zlib-devel bzip2-devel openssl-devel ncurses-devel sqlite-devel readline-devel tk-devel gdbm-devel db4-devel libpcap-devel xz-devel 设置pip 加速 http://www.zyglz.com/index.php/archives/18.html -------------------------------------------------------------------------------------- mkdir ~/.pip cat > ~/.pip/pip.conf << EOF [global] trusted-host=mirrors.aliyun.com index-url=https://mirrors.aliyun.com/pypi/simple/ EOF -------------------------------------------------------------------------------------- pip3 install tensorflow==2.0.0 -i https://pypi.tuna.tsinghua.edu.cn/simple # 获得最新的miniconda安装包； wget https://repo.anaconda.com/miniconda/Miniconda3-latest-Linux-x86_64.sh # 安装到自己的HOME目录software/miniconda3中，这个目录在安装前不能存在； sh Miniconda3-latest-Linux-x86_64.sh -b -p ${HOME}/software/miniconda3 # 安装成功后删除安装包 rm -f Miniconda3-latest-Linux-x86_64.sh # 将环境变量写入~/.bashrc文件中； echo "export PATH=${HOME}/software/miniconda3/bin:\$PATH" >> ~/.bashrc # 退出重新登录或者执行以下命令 source ~/.bashrc #加速 conda config --add channels https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/free/ conda config --set show_channel_urls yes #GPU 版 conda create -n tf-gpu-2.3.0 tensorflow-gpu==2.3.0 -y #CPU 版 conda create -n tf-2.3.0 tensorflow==2.3.0 -y source activate tf-2.3.0 python -c "import tensorflow as tf;print(tf.reduce_sum(tf.random.normal([1000, 1000])))" import os os.environ['TF_CPP_MIN_LOG_LEVEL'] = '2' #＃保证sess.run()能够正常运行 2.0版本的 import tensorflow as tf tf.__version__ tf.compat.v1.disable_eager_execution() hello = tf.constant('hello,tensorflow') sess= tf.compat.v1.Session() print(sess.run(hello)) #导入包 from hyperlpr import * #导入OpenCV库 import cv2 #读入图片 image = cv2.imread("D:\\tensorflow\\lpr-master\\test-imgs\\1.jpg") cv2.imshow("Image", image） #识别结果 print(HyperLPR_plate_recognition(image)) source deactivate win pip install tensorflow-1.6.0-cp36-cp36m-win_amd64.whl pip install tensorflow-2.3.0-cp38-cp38m-win_amd64.whl
Win 10
1.python -m pip install --upgrade pip 临时使用： pip install --trusted-host https://repo.huaweicloud.com -i https://repo.huaweicloud.com/repository/pypi/simple 安装的包名 或者 pip install -i https://repo.huaweicloud.com/simple/sqlalchemy 永久使用： # Window 完整地址：C:\Users\%UserName%\pip\pip.ini Ctrl + R 进入运行，地址栏输入：C:\Users\%UserName%，然后创建pip文件夹，然后创建pip.ini文件 内容： [global] index-url = https://repo.huaweicloud.com/repository/pypi/simple trusted-host = repo.huaweicloud.com timeout = 120 ———————————————————————— # Linux mkdir -p ~/.pip/ cat <<EOF > ~/.pip/pip.conf [global] index-url = https://repo.huaweicloud.com/repository/pypi/simple trusted-host = repo.huaweicloud.com timeout = 120 EOF pip freeze > requirements.txt pip install -r requirements.txt 2.生成requirements.txt文件： 3.安装requirements.txt依赖： import os os.environ['TF_CPP_MIN_LOG_LEVEL'] = '2' import tensorflow as tf tf.__version__ tf.compat.v1.disable_eager_execution() ＃保证sess.run()能够正常运行 hello = tf.constant('hello,tensorflow') sess= tf.compat.v1.Session()＃版本2.0的函数 print(sess.run(hello))
