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cellmap/
cerebellum_setup11_nuc_32nm_190000

Name: cerebellum_setup11_nuc_32nm_190000
Availability: InStock

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cerebellum_setup11_nuc_32nm_190000

Fly StandardUnet model selected for cerebellum inference. Channel: nuc. Used for: jrc_mus-cerebellum-1 nuc, jrc_mus-cerebellum-3 nuc. Source YAMLs: /groups/cellmap/cellmap/zouinkhim/exp_cerebellum/inference/nuc/jrc_mus-cerebellum-1/run.yaml, /groups/cellmap/cellmap/zouinkhim/exp_cerebellum/inference/nuc/jrc_mus-cerebellum-3/run.yaml.

Model Details


Architecture	StandardUnet
Framework	torch
Spatial Dims	3
Input Channels	1
Output Channels	1
Channel Names	nuc
Iteration	190000
Input Voxel Size	32, 32, 32 nm
Output Voxel Size	32, 32, 32 nm
Inference Input Shape	378, 378, 378
Inference Output Shape	256, 256, 256

Available Formats

File	Format	Usage
`model.pt`	PyTorch pickle	`torch.load("model.pt")`
`model.ts`	TorchScript	`torch.jit.load("model.ts")`
`model.onnx`	ONNX	`onnxruntime.InferenceSession("model.onnx")`
`metadata.json`	JSON	Model metadata

Usage

pip install cellmap-models

python

from cellmap_models.model_export.cellmap_model import CellmapModel

model = CellmapModel("path/to/model/folder")

# Inference
output = model.ts_model(input_tensor)

# Finetuning
trainable_model = model.train()

Or download from this repo and load directly:

python

from huggingface_hub import snapshot_download
from cellmap_models.model_export.cellmap_model import CellmapModel

path = snapshot_download(repo_id="cerebellum_setup11_nuc_32nm_190000")
model = CellmapModel(path)

Author

CellMap Project Team, HHMI Janelia

cellmap/cerebellum_setup11_nuc_32nm_190000