要提交的变更：

# CSST-COMMOM-CRMASK - Introduction

===================================

**CRMask** is a module for detecting cosmic rays on the CSST images using state-of-art models. It should be also applied for images from other telescopes, as long as the images have the same data structure as that of CSST.

# Python package dependencies

-----------------------------

The following python packages are needed to **CRMask**:

* astropy == 4.x (>= 5.0 will be tested in the future) 

Install these package under Ubuntu 20.04 LTS:

```

sudo apt install python3-numpy python3-scipy python3-matplotlib python3-astropy python3-ccdproc

        python3 -m pip install pytorch deepCR

sudo python3 -m pip install pytorch deepCR

```

# Usage

-------

Download crmask.py and crmask.ini, put them in the same directory.

Running it:

```

./crmask.py your_file.fits your_model

```

where **your\_file.fits** is the filename of the image which you want to do cosmic ray detection, and **your\_model** is the algorithm you select. Available algorithms are _deepCR_ and _lacosmic_.

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# Warning

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* The default training model of deepCR are obtained from HST/ACS data by Zhang and Bloom (2020). If you would like to use the native model rather than the model **CSST\_2021-12-30\_CCD23\_epoch20.pth** obtained from CSST simulated data by **Hu Yi**, you must also change the **hidden** parameters in the configuration file **crmask.ini** to 32. 

If you would like use the native training model of deepCR, which are obtained from HST/ACS

如果使用deepCR自带用HST/ACS数据训练得到的模型，在配置文件中，要将hidden这个配置参数改为32。-->

# Bugs

------

Please contact **_HU Yi_** (huyi.naoc@gmail.com) to report bugs.