Step install linux virtual environment

1, create a file named env_wcs, python version 3.6 of the virtual environment
Conda the Create -n env_wcs Python = 3.6
Conda the Create -n my_ env = 3.6 Python numpy matplotlib
2, activated environment
Source of an activate my_env
3, exit the virtual environment:
Source deactivate
4, delete environmental
Conda the Remove --all -n my_env
5, see the list of environment
Conda env list
# install the required packages
6, install OpenCV
PIP install Python OpenCV-
7, install torchversion
PIP install Torcy
hvision
8, install tqdm
% tqdm is a fast, scalable Python progress bar may be added to a progress message, the user need only wrap any iterator tqdm (iterator) in Python long cycle.
install tqdm PIP
9, install Cython
% Cython allows us to easily: The syntax of Python written in Python and mixed C / C ++ code that enhance the speed of Python, call the C / C ++ code.
the install Cython PIP
10, mounted scikit-image
% opencv for our tensorflow training data preprocessing is too Taicaixiaoyong, and it opencv installation is not very convenient. So, take some more streamlined lightweight framework to help us do the data preprocessing, scikit-image is such an expansion pack
pip install scikit-image