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Add script to build the doc
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.github/workflows/build_docs.yaml

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name: Build and Deploy Docs
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on:
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push:
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paths:
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- "doc/*.md" # Trigger on changes to any markdown file
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- "flamigo_tools/**/*.py" # Optionally include changes in Python files
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branches:
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- main # Run the workflow only on pushes to the main branch
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workflow_dispatch:
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# security: restrict permissions for CI jobs.
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permissions:
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contents: read
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jobs:
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build:
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name: Build Documentation
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runs-on: ubuntu-latest
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steps:
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- name: Checkout Code
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uses: actions/checkout@v4
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- name: Set up Micromamba
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uses: mamba-org/setup-micromamba@v2
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with:
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micromamba-version: "latest"
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environment-file: environment.yaml
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init-shell: bash
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cache-environment: true
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post-cleanup: 'all'
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- name: Install package
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shell: bash -l {0}
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run: pip install -e .
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- name: Install pdoc
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shell: bash -l {0}
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run: pip install pdoc
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- name: Generate Documentation
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shell: bash -l {0}
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run: pdoc flamingo_tools/ -d google -o doc/
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- name: Verify Documentation Output
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run: ls -la doc/
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- name: Upload Documentation Artifact
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uses: actions/upload-pages-artifact@v3
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with:
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path: doc/
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deploy:
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name: Deploy Documentation
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needs: build
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runs-on: ubuntu-latest
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permissions:
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pages: write
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id-token: write
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environment:
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name: github-pages
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url: ${{ steps.deployment.outputs.page_url }}
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steps:
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- name: Deploy to GiHub Pages
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uses: actions/deploy-pages@v4

README.md

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# Flamingo Tools
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# CochleaNet
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Data processing for light-sheet microscopy, specifically for data from [Flamingo microscopes](https://huiskenlab.com/flamingo/).
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CochleaNet is a software for the analysis of cochleae imaged in light-sheet microscopy. It is based on deep neural networks for the segmentation of spiral ganglion neurons, inner hair cells, and the detection of ribbon synapses.
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It was developed for imaging data from (clear-tissue) [flamingo microscopes](https://huiskenlab.com/flamingo/) and is also applicable to data from commercial microscopes.
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In addition to the analysis functionality, CochleaNet implements data pre-processing to convert data from flamingo microscopes into a format compatible with [BigStitcher](https://imagej.net/plugins/bigstitcher/) and to export image data and segmentation results to [ome.zarr](https://www.nature.com/articles/s41592-021-01326-w) and [MoBIE](https://mobie.github.io/).
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This functionality is applicable to any imaging data from flamingo microscopes, not only clear-tissue data or cochleae. We aim to also extend the segmentation and analysis functionality to other kinds of samples imaged in the flamingo in the future.
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For installation and usage instructions, check out [the documentation](TODO). For more details on the underlying methodology check out [our preprint](TODO).
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<!---
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The `flamingo_tools` library implements functionality for:
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- converting the lightsheet data into a format compatible with [BigDataViewer](https://imagej.net/plugins/bdv/) and [BigStitcher](https://imagej.net/plugins/bigstitcher/).
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- Cell / nucleus segmentation via a 3D U-net.
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- `load_data.py`: Example script for how to load sub-regions from the converted data into python.
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For advanced examples to segment data with a U-Net, check out the `scripts` folder.
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--->

doc/documentation.md

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## Usage
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TODO
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### Napari Plugin
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TODO
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### Command Line Interface
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TODO
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### Available Models
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TODO
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### Python Library
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TODO

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