Mixture model segmentation
Project description
Fast Mixture Model Segmentation
Fast mixture model segmentation used in Boone and Andrews labs
Python requirements
- Numpy
- Cython
- scikit-image
Installation
Create a virtual environment (optional)
$ virtualenv -ppython3 segmentation-env
$ source segmentation-env/bin/activate
Install python requirements (needed to build the package)
$ pip install numpy cython
Install our library (pulls in all other dependencies)
$ pip install segmentation
Usage example
import segmentation as seg
from skimage.io import imread
image = imread('./001001000.tiff', plugin='tifffile')[1] # Read channel 1 of a tiff/flex
im = seg.blur_frame(image) # gaussian blur
segmented, _ = seg.mixture_model(im, debug=True) # second return argument is currently unused
labels = seg.watershed(im, segmented)
Project details
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