cellmap/mito-aff-unet-setup-19-worms
By cellmap · ↓ 0 · ♥ 0 · Updated 2026-03-17
What's in this repo
This page lists the files in cellmap/mito-aff-unet-setup-19-worms.
- No .onnx files in this repository
- 6 files, including 1 .md, 1 .json, 1 .pt, 1 .pt2, 1 .ts
- Last updated 2026-03-17
ONNX files
This repository has no .onnx files. See the full file list on the right for other formats.
How to use
These ONNX files can be loaded with ONNX Runtime. To inspect a model graph, upload the file to the Netron viewer. Download links point to the original files on Hugging Face.
README
mito_aff_unet_setup_19_worms
C-elegans worms affinities for mitochondria segmentation using a UNet architecture trained on setup 19 with 370k iterations.
Model Details
| Architecture | UNet |
| Framework | torch |
| Spatial Dims | 3 |
| Input Channels | 1 |
| Output Channels | 3 |
| Channel Names | mito_aff_1, mito_aff_2, mito_aff_3 |
| Iteration | 370000 |
| 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
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:
from huggingface_hub import snapshot_download
from cellmap_models.model_export.cellmap_model import CellmapModel
path = snapshot_download(repo_id="mito_aff_unet_setup_19_worms")
model = CellmapModel(path)
Author
Marwan Zouinkhi
Links
Model info
Created: 2026-03-17
Updated: 2026-03-17
View on Hugging FaceFiles (6)
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