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Minimal documentation for installation process
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scripts/baselines/README.md

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# Baselines for the Segmentation of IHCs and SGNs
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Other networks/methods have been evaluated on SGN and IHC crops to compare the proposed method to the state of the art and justify the development of said method.
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Cellpose 3, Cellpose-SAM, micro-sam, and the distance U-Net were evaluated for both SGNs and IHCs.
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Additionally, Stardist was used for SGN segmentation.
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HCAT, a specialized tool for the segmentation of IHCs, was omitted because it is a purely 2D network and, therefore, does not fit the use case.
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## Micro-sam
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Follow [instructions](https://computational-cell-analytics.github.io/micro-sam/micro_sam.html).
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## Cellpose-SAM
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Instalation:
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```
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micromamba create --name cellpose-sam python=3.10
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micromamba activate cellpose-sam
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python -m pip install cellpose
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python -m pip install cellpose --upgrade
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```
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The script is adaapted from the [example Jupyter notebook online](https://github.com/MouseLand/cellpose/blob/main/notebooks/run_Cellpose-SAM.ipynb).
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## Cellpose 3
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Installation:
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```
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micromamba create --name cellpose3 python=3.10
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micromamba activate cellpose3
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python -m pip install cellpose==3.1.1.2
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```
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The script is adapted from the [example Jupyter notebook online](https://github.com/MouseLand/cellpose/blob/main/notebooks/run_cellpose3.ipynb).
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## Stardist
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Installation:
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```
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micromamba create -n stardist python=3.11 napari pyqt stardist-napari -y
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micromamba activate stardist
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python3.11 -m pip install 'tensorflow[and-cuda]'
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python3.11 -m pip install stardist
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python3.11 -m pip install 'numpy<2'
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```

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