keejkrej/spotiflow-onnx

license: bsd-3-clause library_name: onnx tags:

• onnx
• spot-detection
• fluorescence-microscopy
• bioimage-analysis
• spotiflow

Spotiflow ONNX — General

ONNX export of the general pretrained Spotiflow model for 2D fluorescent spot detection in microscopy images.

Model Details

Usage

Python (onnxruntime)

import onnxruntime as ort
import numpy as np

session = ort.InferenceSession("model.onnx")
image = np.random.rand(1, 1, 512, 512).astype(np.float32)
outputs = session.run(None, {"input": image})
heatmaps, flow = outputs[0], outputs[-1]  # flow has shape [B, 3, H, W]

Rust (spotiflow-rs)

use spotiflow_rs::{SpotiflowSession, PredictParams};

let mut session = SpotiflowSession::new("model.onnx")?;
let (spots, heatmaps, flows) = session.predict(&image_f32, h, w, PredictParams::default())?;

Export

Exported from the official PyTorch weights using a wrapper that converts the model's dictionary output to an explicit (heatmaps, flow) tuple for correct ONNX tracing:

python scripts/export_onnx.py --model general --output model.onnx

License

BSD 3-Clause — same as the original Spotiflow repository.

Copyright (c) 2023, Albert Dominguez Mantes, Martin Weigert.

Citation

@article{dominguez2024spotiflow,
  title={Spotiflow: accurate and efficient spot detection for fluorescence microscopy with deep stereographic flow regression},
  author={Dominguez Mantes, Albert and Herrera, Antonio and Khven, Irina and Schlaeppi, Anjalie and Aho, Eftychia and Erskine, Amber and Laubscher, Eleonora and Hendriks, Gert-Jan and Thiran, Jean-Philippe and Bhatt, Deepak K and Wegner, Joerg D and Weigert, Martin},
  journal={bioRxiv},
  year={2024},
  publisher={Cold Spring Harbor Laboratory}
}