perform cellpose segmentation — doCellposeSegmentation • Giotto

perform the Giotto Wrapper of cellpose segmentation. This is for a model inference to generate segmentation mask file from input image. main parameters needed

doCellposeSegmentation(
  python_env = "giotto_cellpose",
  image_dir,
  mask_output,
  channel_1 = 0,
  channel_2 = 0,
  model_name = "cyto3",
  batch_size = 8,
  resample = TRUE,
  channel_axis = NULL,
  z_axis = NULL,
  normalize = TRUE,
  invert = FALSE,
  rescale = NULL,
  diameter = NULL,
  flow_threshold = 0.4,
  cellprob_threshold = 0,
  do_3D = FALSE,
  anisotropy = NULL,
  stitch_threshold = 0,
  min_size = 15,
  niter = NULL,
  augment = FALSE,
  tile = TRUE,
  tile_overlap = 0.1,
  bsize = 224,
  interp = TRUE,
  compute_masks = TRUE,
  progress = NULL,
  verbose = TRUE,
  ...
)

Arguments

image_dir: character, required. Provide a path to a gray scale or a three channel image.
mask_output: required. Provide a path to the output mask file.
channel_1: channel number for cytoplasm, default to 0(gray scale)
channel_2: channel number for Nuclei, default to 0(gray scale)
model_name: Name of the model to run inference. Default to 'cyto3', if you want to run cutomized trained model, place your model file in ~/.cellpose/models and specify your model name.
batch_size: Cellpose Parameter, Number of 224x224 patches to run simultaneously on the GPU. Can make smaller or bigger depending on GPU memory usage. Defaults to 8.
resample: Cellpose Parameter
channel_axis: Cellpose Parameter
z_axis: Cellpose Parameter
normalize: Cellpose Parameter
invert: Cellpose Parameter
rescale: Cellpose Parameter
diameter: Cellpose Parameter
flow_threshold: Cellpose Parameter
cellprob_threshold: Cellpose Parameter
do_3D: Cellpose Parameter
anisotropy: Cellpose Parameter
stitch_threshold: Cellpose Parameter
min_size: Cellpose Parameter
niter: Cellpose Parameter
augment: Cellpose Parameter
tile: Cellpose Parameter
tile_overlap: Cellpose Parameter
bsize: Cellpose Parameter
interp: Cellpose Parameter
compute_masks: Cellpose Parameter
progress: Cellpose Parameter
python_path: python environment with cellpose installed. default = "giotto_cellpose".

Value

No return variable, as this will write directly to output path provided.

Examples

# example code
doCellposeSegmentation(
    image_dir = input_image,
    mask_output = output, channel_1 = 2,
    channel_2 = 1, model_name = "cyto3", batch_size = 4
)
#> python already initialized in this session
#>  active environment : '/usr/bin/python3'
#>  python version : 3.10
#> specified py env from `envname` = 'giotto_cellpose' not found
#> Error: package 'cellpose' is not yet installed
#> 
#>  To install:
#> ## active python env: '/usr/bin/python3' 
#> ## python version: 3.10
#> ## restart session then use GiottoClass::set_giotto_python_path() if this is incorrect
#> reticulate::conda_install(envname = '/usr/bin/python3', packages = c('cellpose'), pip = TRUE)