cellpose#
Threshold/interpolation to apply to image For interpolation options are: log2, log10 or linear
img_threshold: 0
img_interpolate: 'log2'
Model is trained on two-channel images, where the first channel is the channel to segment, and the second channel is an optional nuclear channel.” Options for each:
0=grayscale, 1=red, 2=green, 3=blue
0=None (will set to zero), 1=red, 2=green, 3=blue
e.g. channels = [0,0] if you want to segment cells in grayscale
channels: [0,0]
Files to evaluate Cellpose on Options are: all (evaluate on all files), metadata (evaluate on files listed in metadata[‘test_files’]) OR list of files to evaluate on
test_files: all
Whether to use the GPU during evaluation
use_gpu: True
The following is not generic, if you need to use this please raise an issue and tag @oubino
Diameter to set for Cellpose model - NOTE: this makes no difference at the moment as we hardcode in the diameter into our Cellpose fork, which needs to be changed!
diameter: 100
Cellpose model - for a full list of models see https://cellpose.readthedocs.io/en/latest/models.html
model: 'LC1'
For two channel image, we sum them together Need the name of the first and second channel in terms of the real concepts
channel: 'egfr'
alt_channel: 'ereg'
Whether to sum the channels
sum_chan: True