---
library_name: cellmap-models
tags:
- pytorch
- onnx
- torchscript
- 3d
- segmentation
- electron-microscopy
- cellmap
- er
license: bsd-3-clause
---

# er_resunet_setup_67

Endoplasmic reticulum (er) from FIB-SEM at 8 nm, 3D residual U-Net (InstanceNorm, valid convs), exp_mito setup_67 at 20000 iterations. Valid convolutions (88 voxels of context per axis); outputs raw logits. ONNX web version: cellmap/onnx-web-models/setup_67.

## Model Details

| | |
|---|---|
| **Architecture** | ResUNet3DValid |
| **Framework** | torch |
| **Spatial Dims** | 3 |
| **Input Channels** | 1 |
| **Output Channels** | 1 |
| **Channel Names** | er |
| **Iteration** | 20000 |
| **Input Voxel Size** | 8, 8, 8 nm |
| **Output Voxel Size** | 8, 8, 8 nm |
| **Inference Input Shape** | 300, 300, 300 |
| **Inference Output Shape** | 212, 212, 212 |
| **Input Normalization** | {"max": 1.0, "method": "min_max", "min": -1.0} |
| **Inference Output Activation** | {"apply_after_model": true, "name": "sigmoid"} |

## Available Formats

| File | Format | Usage |
|---|---|---|
| `model.pt2` | torch.export program | `torch.export.load("model.pt2").module()` |
| `model_state_dict.pt` + `model_def.py` | PyTorch state_dict + module code | see "PyTorch original" below |
| `model.ts` | TorchScript | `torch.jit.load("model.ts")` |
| `model.onnx` (+ `model.onnx.data`) | ONNX | `onnxruntime.InferenceSession("model.onnx")` |
| `metadata.json` | JSON | Model metadata |
| `torch_source.json` | JSON | class + constructor arguments for `model_def.py` |

## Usage

```bash
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="cellmap/er-resunet-setup-67")
model = CellmapModel(path)
```

## Author

Marwan Zouinkhi

## Links

- [cellmap-models](https://github.com/janelia-cellmap/cellmap-models)
- [CellMap Project](https://www.janelia.org/project-team/cellmap)

## PyTorch original (for finetuning / re-export)

`model_state_dict.pt` (plain tensors, `weights_only=True`) + the module code (`model_def.py`); `torch_source.json`
names the class and constructor arguments.

```python
import json, importlib.util, torch
src = json.load(open("torch_source.json"))
spec = importlib.util.spec_from_file_location("model_def", src["module"]); mod = importlib.util.module_from_spec(spec)
spec.loader.exec_module(mod)
model = getattr(mod, src["class"])(**src["kwargs"])
model.load_state_dict(torch.load("model_state_dict.pt", weights_only=True))
model.eval()
```