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cellmap/
cerebellum_20250806_lyso_mouse_distance_16nm_358000

Name: cerebellum_20250806_lyso_mouse_distance_16nm_358000
Availability: InStock

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cerebellum_20250806_lyso_mouse_distance_16nm_358000

Fly StandardUnet model selected for cerebellum inference. Channel: lyso. Used for: jrc_mus-cerebellum-2 lyso, jrc_mus-cerebellum-3 lyso ensemble component m1. Source YAMLs: /groups/cellmap/cellmap/zouinkhim/exp_cerebellum/inference/lyso/jrc_mus-cerebellum-2/run.yaml, /groups/cellmap/cellmap/zouinkhim/exp_cerebellum/inference/lyso/jrc_mus-cerebellum-3/run.yaml.

Model Details


Architecture	StandardUnet
Framework	torch
Spatial Dims	3
Input Channels	1
Output Channels	1
Channel Names	lyso
Iteration	358000
Input Voxel Size	16, 16, 16 nm
Output Voxel Size	16, 16, 16 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_20250806_lyso_mouse_distance_16nm_358000")
model = CellmapModel(path)

Author

CellMap Project Team, HHMI Janelia

cellmap/cerebellum_20250806_lyso_mouse_distance_16nm_358000