In a notebookΒΆ

See settings for more information on run settings.

import numpy as np
import matplotlib.pyplot as plt
from cellpose import models

# model_type='cyto' or model_type='nuclei'
model = models.Cellpose(model_type='cyto')

# list of files
files = ['/media/carsen/DATA1/TIFFS/onechan.tif']

imgs = [ for f in files]
nimg = len(imgs)

# define CHANNELS to run segementation on
# grayscale=0, R=1, G=2, B=3
# channels = [cytoplasm, nucleus]
# if NUCLEUS channel does not exist, set the second channel to 0
channels = [[0,0]]
# IF ALL YOUR IMAGES ARE THE SAME TYPE, you can give a list with 2 elements
# channels = [0,0] # IF YOU HAVE GRAYSCALE
# channels = [2,3] # IF YOU HAVE G=cytoplasm and B=nucleus
# channels = [2,1] # IF YOU HAVE G=cytoplasm and R=nucleus

# if diameter is set to None, the size of the cells is estimated on a per image basis
# you can set the average cell `diameter` in pixels yourself (recommended)
# diameter can be a list or a single number for all images

masks, flows, styles, diams = model.eval(imgs, diameter=None, channels=channels)

See full notebook at run_cellpose.ipynb.