vfv_config.yaml

Experiment:
    name: "my_exp"
    basepath: "/path/to/experiment/outputs"

VirtualFusedVolume:
    name: "vfv_name"
    config_file: "/path/to/vfv/stitch.yml" # can be also a .tiff file (if it fits into memory...)
    dim_resolution: [2., .65, .65]
    patch_shape: [160, 480, 480]
    patch_overlap: [12, 36, 36] # NOTE: it should be at least two times the diameter of the largest cell
    mask_path: "/path/to/mask.tiff" # can be any resolution, any shape difference with the VFV will be accounted for
    outdir: "/path/to/vfv/predictions/folder"

# Attn! Should be identical to the training phase! Be aware of any differences: check training config file!
PreProcessing:
    clip: "bit" # can be one of ['constant', 'bit', 'quantile', 'auto', null]
    clip_value: 14
    center: null # can be one of ['constant', 'min', 'mean', null]
    center_value: null
    scale: "bit" # can be one of ['constant', 'bit', 'max', 'std', 'none', null]
    scale_value: 14