**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.
**CRMask** is a module for detecting cosmic rays on the CSST images using state-of-art algorithms. It should be also applicable for images from other telescopes, as long as the images have the same data structure as that of CSST.
# Python package dependencies
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@@ -51,6 +51,8 @@ where **your\_file.fits** is the filename of the image which you want to do cosm
* 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.
***CSST\_2021-12-30\_CCD23\_epoch20.pth** model is **_ONLY_** suitable for CSST-MSC simulated images. You need to train your own models for CSST-MSC simulated slitless spretra or images/spectra from other telescopes.
* The input images must be **bias-substracted** (either by bias reference fram or overscan region) no matter which algorithm selected, otherwise you will get very inefficient detection rate thus wrong results. Flat-field corrected images are preferable, but not necessary.
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If you would like use the native training model of deepCR, which are obtained from HST/ACS
