Modelzoo Export about n2v HOT 3 CLOSED

name: YOUR MODEL NAME HERE
description: YOUR DESCRIPTION HERE
cite:
  text: |-
    Buchholz, T. et al. - Content-aware image restoration for electron microscopy. 
    Methods in Cell Biology, Volume 152 p.277-289, ISSN 0091-679X (2019)
  doi: https://doi.org/10.1016/bs.mch.2019.05.001
authors: [YOUR NAMES HERE]
documentation: README.md
test_input: ./test_input.tif
test_output: ./test_output.tif
covers: [./thumbnail.png]
tags: [denoising, unet2d, n2v]
license: BSD 3
format_version: 0.1.0
language: java
framework: tensorflow
source: de.csbdresden.n2v.train.N2VPrediction
inputs:
- name: raw
  axes: byxc
  data_type: float32
  data_range: [-inf, inf]
  shape:
    min: [1, 4, 4, 1]
    step: [1, 4, 4, 0]
outputs:
- name: denoised
  axes: byxc
  data_type: float32
  data_range: [-inf, inf]
  halo: [0, 32, 32, 0]
  shape:
    reference_input: raw
    scale: [1, 1, 1, 1]
    offset: [0, 0, 0, 0]
training:
  source: de.csbdresden.n2v.train.N2VTraining
  kwargs: {batchDimLength: 180, batchSize: 64, trainDimensions: 2, neighborhoodRadius: 5, numEpochs: 100,
    numStepsPerEpoch: 300, patchDimLength: 60, stepsFinished: 30000}
prediction:
  preprocess:
    spec: de.csbdresden.n2v.predict.N2VPrediction::preprocess
    kwargs: {mean: 41498.87, stdDev: 15007.021}
  weights: {source: https://github.com/bioimage-io/fiji-bioimage-io/releases/download/v0.1.0/n2v-sem-demo.zip}
  postprocess:
    spec: de.csbdresden.n2v.predict.N2VPrediction::postprocess
    kwargs: {mean: 41498.87, stdDev: 15007.021}
  dependencies: ./dependencies.yaml