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mac_quickstart.md

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Zero base mac installation and image style transfer

Step 1: Install Anaconda

  • Note: To use paddlepaddle, you need to install the Python environment first. Here we choose the Python integrated environment Anaconda toolkit
    • Anaconda is a commonly used python package management program
    • After installing Anaconda, you can install the python environment and the toolkit environment required by numpy
  • Anaconda Download:
  • After downloading, double click the. pkg file to enter the graphical interface
    • By default, the installation will take a while
  • It is recommended to install a code editor such as vscode or pycharm

Step 2: Open the terminal and create a conda environment

  • Open terminal

    • Press the command key and the space bar at the same time, enter "terminal" in the focus search, and double-click to enter the terminal

  • Add conda to the environment variable

    • The environment variable is added to enable the system to recognize the conda command

    • Enter the following command to open ~/.bash_profile：

      • vim ~/.bash_profile

    • In ~/.bash_profile add conda as an environment variable:

      • # Press i first to enter editing mode
# On the first line, enter:
export PATH="~/opt/anaconda3/bin:$PATH"
# If the installation location is customized during installation, change ~/opt/anaconda3/bin to the bin folder under the customized installation directory
      • # Modified ~/.bash_profile file should be as follows (where xxx is the user name):
export PATH="~/opt/anaconda3/bin:$PATH"
# >>> conda initialize >>>
# !! Contents within this block are managed by 'conda init' !!
__conda_setup="$('/Users/xxx/opt/anaconda3/bin/conda' 'shell.bash' 'hook' 2> /dev/null)"
if [ $? -eq 0 ]; then
    eval "$__conda_setup"
else
    if [ -f "/Users/xxx/opt/anaconda3/etc/profile.d/conda.sh" ]; then
        . "/Users/xxx/opt/anaconda3/etc/profile.d/conda.sh"
    else
        export PATH="/Users/xxx/opt/anaconda3/bin:$PATH"
    fi
fi
unset __conda_setup
# <<< conda initialize <<<

      • After modification, press the esc key to exit editing mode, and then enter :wq! And enter to save the exit

    • Verify that the conda command is recognized:

      • Enter source ~/.bash_profile to update environment variables
      • Then enter conda info --envs on the terminal. If the current base environment can be displayed, conda has added an environment variable

  • Create a new conda environment

    • # On the command line, enter the following command to create a file named paddle_env environment
# This is for accelerated download, use Tsinghua source
conda create --name paddle_env python=3.8 --channel https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/free/

    • This command will create an executable environment named paddle_env with Python version 3.8. It will take a while depending on the network status

    • Then the command line will output a prompt message, enter y and press Enter to continue the installation

      • conda_create

  • Activate the newly created conda environment, and enter the following command on the command line:

    • # Activate paddle_env environment
conda activate paddle_env
# View the current python location
where python
    • conda_actviate

    • The above anaconda environment and python environment have been installed

Step 3: Install the libraries required by the program

  • Use the pip command to install the pad in the newly activated environment:

    • # Enter the following command on the command line
# Confirm whether the currently used pip is the pip in the paddle_env environment
where pip
# The CPU version is installed by default. Baidu Source is recommended when installing the PaddlePaddle
pip install paddlepaddle -i https://mirror.baidu.com/pypi/simple

  • After installing Paddle, continue to install the PaddleHub in the paddle_env environment:

    • # Enter the following command on the command line
pip install paddlehub -i https://mirror.baidu.com/pypi/simple

    • Introduction document of paddlehub: https://github.com/PaddlePaddle/PaddleHub/blob/develop/README.md

    • When installing the paddlehub, other dependent libraries will be installed automatically, which may take a while

Step 4: Install the paddlehub and download the model

Step 5: Prepare the style to migrate data and code

Prepare style migration data

  • Create Working Directory style_transfer on Desktop

    • # Enter the following command in the terminal:
cd ~/Desktop  # Enter the desktop
mkdir style_transfer  # Create style_transfer folder
cd style_transfer  # Enter style_transfer directory

  • Place pictures to be converted and style pictures respectively:

    • Place the picture to be converted on the desktop style_transfer/pic.jpg
      • pic.jpg
    • Place Style Picture on Desktop style_transfer/fangao.jpg
      • fangao.jpg

代码

  • In style_transfer create code file style_transfer.py

  • Copy the following code into style_transfer.py

    • import paddlehub as hub
import cv2

# Relative address of the picture to be converted
picture = './pic.jpg'
# Relative address of style picture
style_image = './fangao.jpg'

# Create a style transfer network and load parameters
stylepro_artistic = hub.Module(name="stylepro_artistic")

# Read in pictures and start style conversion
result = stylepro_artistic.style_transfer(
                    images=[{'content': cv2.imread(picture),
                             'styles': [cv2.imread(style_image)]}],
                    visualization=True
)

  • If there is no code editor such as vscode, you can use the command line method:

    • pwd # Check whether the current directory is style_transfer， if not, enter: cd ~/Desktop/style_transfer
touch style_transfer.py  # Create an empty file
vim style_transfer.py  #  Open code file with vim editor
# Enter i first to enter editing mode
# Copy the above code into the vim editor
# Press esc key to exit editing mode, then enter ": wq" and enter Enter to save and exit

  • Running code:

    • On the command line, enter python style_transfer.py
    • When the program executes, a new folder transfer_result will be created, and save the converted file to this directory
    • The output pictures are as follows:
      • output image

Step 6: Explore the pre training model of flying oars