
Architecture	Sequential
Framework	torch
Spatial Dims	3
Input Channels	1
Output Channels	8
Channel Names	all_mem, organelle, mito, er, nucleus, pm, vs, ld
Iteration	700000
Input Voxel Size	8, 8, 8 nm
Output Voxel Size	8, 8, 8 nm
Inference Input Shape	178, 178, 178
Inference Output Shape	56, 56, 56

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="fly_organelles_run07_700000")
model = CellmapModel(path)

Author

Larissa Heinrich

cellmap/fly_organelles_run07_700000

fly_organelles_run07_700000

Model Details

Available Formats

Usage

Author

Links

cellmap/
fly_organelles_run07_700000