Metadata-Version: 2.1
Name: MiSiC
Version: 1.0.7
Summary: Microbe segmentation in dense colonies
Home-page: https://imm.cnrs.fr
Author: S.Panigrahi
Author-email: spanigrahi@imm.cnrs.fr
License: UNKNOWN
Description: # MiSiC
        ### Microbe segmentation in dense colonies.
        
        ## Installation
        Requires version python version 3.6/7
        
        `pip install MiSiC`
        
        
        ## Usage
        
        ### use package
        ```python
        from MiSiC.MiSiC import *
        from skimage.io import imsave,imread
        from skimage.transform import resize,rescale
        
        filename = 'awesome_image.tif'
        
        # read image using your favorite package
        im = imread(filename)
        
        # Parameters that need to be changed
        ## Ideally, use a single image to fine tune two parameters : mean_width and noise_variance (optional)
        
        #input the approximate mean width of microbe under consideration
        mean_width = 8
        
        # compute scaling factor
        scale = (10/mean_width)
        
        # Initialize MiSiC
        misic = MiSiC()
        
        # preprocess using inbuit function or if you are feeling lucky use your own preprocessing
        im = rescale(im,scale,preserve_range = True)
        
        # add local noise
        img = add_noise(im,sensitivity = 0.13,invert = True)
        
        # segment
        yp = misic.segment(img,invert = True)
        yp = resize(yp,[sr,sc,-1])
        
        # watershed based post processing
        yp = postprocess_ws(img,yp)
        
        # save 8-bit segmented image and use it as you like
        imsave('segmented.tif', yp.astype(np.uint8))
        ''''
        
        ### In case of gpu error, one might need to disabple gpu before importing MiSiC [ os.environ["CUDA_VISIBLE_DEVICES"]="-1" ]
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Requires-Python: >=3.5
Description-Content-Type: text/markdown
