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       celeste_standalone - Cloud identification


       celeste_standalone [options] image1 image2 [..]


       Celeste has been trained using Support vector machine techniques to
       identify clouds in photos and remove control points from these areas.
       celeste_standalone is a command-line tool with all the same
       functionality as Celeste in hugin.

       Simple usage is to just ’clean’ an existing project file:

        celeste_standalone -i project.pto -o project.pto


       -i <filename>
           Input Hugin PTO file. Control points over SVM threshold will be
           removed before being written to the output file. If -m is set to 1,
           images in the file will be also be masked.

       -o <filename>
           Output Hugin PTO file. Default: ’<filename>_celeste.pto’

       -d <filename>
           SVM model file. Default: ’data/celeste.model’

       -s <int>
           Maximum dimension for re-sized image prior to processing. A higher
           value will increase the resolution of the mask but is significantly
           slower. Default: 800

       -t <float>
           SVM threshold. Raise this value to remove fewer control points,
           lower it to remove more. Range 0 to 1. Default: 0.5

       -m <1│0>
           Create masks when processing Hugin PTO file. Default: 0

       -f <string>
           Mask file format. Options are PNG, JPEG, BMP, GIF and TIFF.
           Default: PNG

       -r <1│0>
           Filter radius. 0 = large (more accurate), 1 = small (higher
           resolution mask, slower, less accurate). Default: 0

       -h  Print usage.


       Written by Tim Nugent.