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Add initial cellpose manifest
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sea-shunned committed Oct 15, 2024
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{
"name": "Cellpose",
"short_name": "cellpose",
"metadata": {
"description": "Cellpose is a generalist model for cell and nucleus segmentation.",
"url": "https://cellpose.readthedocs.io/en/latest/",
"repo": "https://github.com/MouseLand/cellpose",
"pubs": [
{
"info": "Cellpose v1",
"url": "https://doi.org/10.1038/s41592-020-01018-x",
"title": "Cellpose: a generalist algorithm for cellular segmentation",
"doi": "10.1038/s41592-020-01018-x",
"authors": [
{
"name": "Carsen Stringer",
"affiliation": "HHMI Janelia Research Campus, Ashburn, VA, USA"
},
{
"name": "Tim Wang",
"affiliation": "HHMI Janelia Research Campus, Ashburn, VA, USA"
},
{
"name": "Michalis Michaelos",
"affiliation": "HHMI Janelia Research Campus, Ashburn, VA, USA"
},
{
"name": "Marius Pachitariu",
"affiliation": "HHMI Janelia Research Campus, Ashburn, VA, USA"
}
]
},
{
"info": "Cellpose v2",
"url": "https://doi.org/10.1038/s41592-022-01663-4",
"title": "Cellpose 2.0: how to train your own model",
"doi": "10.1038/s41592-022-01663-4",
"authors": [
{
"name": "Marius Pachitariu",
"affiliation": "HHMI Janelia Research Campus, Ashburn, VA, USA"
},
{
"name": "Carsen Stringer",
"affiliation": "HHMI Janelia Research Campus, Ashburn, VA, USA"
}
]
},
{
"info": "Cellpose v3",
"url": "https://www.biorxiv.org/content/10.1101/2024.02.10.579780v2",
"title": "Cellpose3: one-click image restoration for improved cellular segmentation",
"doi": "10.1101/2024.02.10.579780",
"authors": [
{
"name": "Carsen Stringer",
"affiliation": "HHMI Janelia Research Campus, Ashburn, VA, USA"
},
{
"name": "Marius Pachitariu",
"affiliation": "HHMI Janelia Research Campus, Ashburn, VA, USA"
}
]
}
]
},
"versions": {
"cyto3": {
"tasks": {
"cyto": {
"location":"https://www.cellpose.org/models/cyto3"
}
}
},
"nuclei": {
"tasks": {
"nuclei": {
"location": "https://www.cellpose.org/models/nucleitorch_0"
}
}
},
"cyto1": {
"tasks": {
"cyto": {
"location": "https://www.cellpose.org/models/cytotorch_0"
}
}
},
"cyto2": {
"tasks": {
"cyto": {
"location":"https://www.cellpose.org/models/cyto2torch_0"
}
}
}
},
"params": [
{
"name": "Diameter",
"arg_name": "diameter",
"value": 0,
"tooltip": "Diameter of the cells in pixels. If None or 0, Cellpose will try to estimate it. Setting the value may improve results. See https://cellpose.readthedocs.io/en/latest/settings.html#diameter for details."
},
{
"name": "Segment Channel",
"arg_name": "segment_channel",
"value": 0,
"tooltip": "What channel to segment on. 0=grayscale, 1=red, 2=green, 3=blue. See https://cellpose.readthedocs.io/en/latest/settings.html#channels for details."
},
{
"name": "Nucleus Channel",
"arg_name": "nucleus_channel",
"value": 0,
"tooltip": "What channel contains nucleus. 0=grayscale, 1=red, 2=green, 3=blue. Unused for 'nuclei' model, where nuclei are in the segment channel. See https://cellpose.readthedocs.io/en/latest/settings.html#channels for details."
},
{
"name": "3D Segmentation",
"arg_name": "do_3D",
"value": false,
"tooltip": "Whether to do 3D segmentation. If True, will try to segment in 3D (XY, XZ, YZ). If False, will segment in 2D and combine with stitch_threshold."
},
{
"name": "Stitch Threshold",
"arg_name": "stitch_threshold",
"value": 0.0,
"tooltip": "Threshold for stitching 2D segmentations together. Value is the IoU that constitutes an overlap and thus merge. Only used if do_3D is False and >0."
},
{
"name": "Cellprob Threshold",
"arg_name": "cellprob_threshold",
"value": 0.0,
"tooltip": "Threshold for flows to determine ROIs. Decrease to find more & larger ROIs, increase if too many ROIs (esp. in dim regions). See https://cellpose.readthedocs.io/en/latest/settings.html#cellprob-threshold for details."
},
{
"name": "Flow Threshold",
"arg_name": "flow_threshold",
"value": 0.4,
"tooltip": "Threshold for flows to determine ROIs. Not used for 3D. See https://cellpose.readthedocs.io/en/latest/settings.html#cellprob-threshold for details."
},
{
"name": "Num Iterations",
"arg_name": "niter",
"value": 0,
"tooltip": "Number of iterations to simulate dynamics for. By default (0/None), proportional to ROI diameter. See https://cellpose.readthedocs.io/en/latest/settings.html#number-of-iterations-niter for details."
},
{
"name": "Anisotropy",
"arg_name": "anisotropy",
"value": null,
"dtype": "float",
"tooltip": "Optional rescaling factor for Z (e.g. set to 2.0 if Z is sampled half as dense as X or Y)."
},
{
"name": "Channel axis",
"arg_name": "channel_axis",
"value": null,
"dtype": "int",
"tooltip": "Set the axis where channels are stored. 'None' means it tries to figure it out - useful if no/poor metadata and not loading properly."
},
{
"name": "Z axis",
"arg_name": "z_axis",
"value": null,
"dtype": "int",
"tooltip": "Set the axis where Z slices are stored. 'None' means it tries to figure it out - useful if no/poor metadata and not loading properly."
},
{
"name": "Batch size",
"arg_name": "batch_size",
"value": 64,
"tooltip": "Number of 224x224 patches to run simultaneously on the GPU. Can make smaller or bigger depending on GPU memory usage."
},
{
"name": "Minimum size",
"arg_name": "min_size",
"value": 15,
"tooltip": "Size (in pixels) of ROIs/to remove if lower. 0 will not remove any masks."
}
]
}

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