Metadata-Version: 2.1
Name: surfcut
Version: 0.0.3rc1
Summary: Cutting confocal stacks at various depths relative to surface signal 
Home-page: UNKNOWN
License: UNKNOWN
Description: ***************************
        Surfcut for Python & Matlab
        ***************************
        
        Surfcut for Python & Matlab is based on Surfcut for ImageJ
        
        Paper:
        Erguvan, O., Louveaux, M., Hamant, O., Verger, S. (2019) ImageJ SurfCut: a user-friendly pipeline for high-throughput extraction of cell contours from 3D image stacks. BMC Biology, 17:38. https://doi.org/10.1186/s12915-019-0657-1
        
        Software:
        Verger Stéphane. (2019, April 10). sverger/SurfCut: SurfCut (Version v1.1.0). Zenodo. http://doi.org/10.5281/zenodo.2635737
        
        Example Data:
        Erguvan Özer, & Verger Stéphane. (2019). Dataset of confocal microscopy stacks from plant samples - ImageJ SurfCut: a user-friendly, high-throughput pipeline for extracting cell contours from 3D confocal stacks [Data set]. Zenodo. http://doi.org/10.5281/zenodo.2577053
        
        Headless Mode
        =============
        
        If you are a Python user, this package is available on pip:
        
        ::
        
            pip install surfcut
        
        To run from the command line:
        
        ::
        
            surfcut <image name>.tif
        
        This version implements Surfcut exactly as in the original paper.
        
        A version including morphological operations (erode and dilate) is available for surfaces which are very curved, but is much slower than the original approach.
        
        ::
        
            surfcut <image name>.tif -m
        
        .. image:: resources/morph.gif
        
        For more options:
        
        ::
        
            surfcut --help
        
Platform: UNKNOWN
Requires-Python: >=3.6
Description-Content-Type: text/x-rst
