semvec/pypi-packages huggingface dataset:
km3py 0.2.0
The km3py metaproject is a collection of KM3NeT Python packages.
Requires Python: >=3.6

The km3py metaproject is a collection of KM3NeT Python packages.
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.. image:: https://examples.pages.km3net.de/km3badges/docs-latest-brightgreen.svg
    :target: https://km3py.pages.km3net.de/km3py


This package includes:

- km3pipe
- km3io
- km3astro
- km3db
- km3net-testdata
- km3flux
brainseg 0.0.5
A brain segmentation tool
Requires Python: >=3.8

# Brain Seg

![Segmentation Comparison](assets/SegmentationComparison.jpg)

A brain segmentation tool using machine learning

Under development

This software has NOT been approved for medical analysis/diagnosis. Please use other
approved software for medical use.

# Models
SavedModels for use can be found at [Google Drive](https://drive.google.com/drive/folders/1DuKPhzKcxWUNXYxYbSNw8zydiAG7a8qw?usp=sharing).

Models were trained using the Mindboggle-101 data:

Klein, Arno, 2016, "Mindboggle-101 manually labeled individual brains", 
https://doi.org/10.7910/DVN/HMQKCK, Harvard Dataverse, V2

A Klein, SS Ghosh, FS Bao, J Giard, Y Hame, E Stavsky, N Lee, B Rossa, M Reuter, EC Neto, A Keshavan. 2017. 
Mindboggling morphometry of human brains. 
PLoS Computational Biology 13(3): e1005350. doi:10.1371/journal.pcbi.1005350 
(bioRxiv 2016 preprint)

# Options
    positional arguments:
      filepath              Path of file to segment
    
    optional arguments:
      -h, --help            show this help message and exit
      -s SEGMENT, --segment Segments using provided SavedModel (Directory path required)
      --segment-precision   Float32 or float64 {32,64}
      --output OUTPUT, -o   Output filepath
      --output-channels     Number of channel in output image {1,3}


# Usage Examples
```bash
# Segments a sample nifti scan
$ brainseg sample.nii.gz -s sampleSavedModel -o output.nii.gz
```

# Model Training Graphs

SavedModel_210303
![accuracy_210303](assets/accuracy_210303_235240.png)
![loss_210303](assets/loss_210303_235240.png)