# PlotNeuralNet
[![DOI](https://zenodo.org/badge/DOI/10.5281/zenodo.2526396.svg)](https://doi.org/10.5281/zenodo.2526396)

Latex code for drawing neural networks for reports and presentation. Have a look into examples to see how they are made. Additionally, lets consolidate any improvements that you make and fix any bugs to help more people with this code.

## TODO

- [X] Python interfaz
- [ ] Pytorch generate graph arquiture
- [ ] Add easy legend functionality
- [ ] Add more layer shapes like TruncatedPyramid, 2DSheet etc

## Usage

    mkdir my_project
    cd my_project
    vim my_arch.py

        import sys
        sys.path.append('../')
        from core.tikzeng import *

        # defined your arch
        arch = [
            to_head( '..' ),
            to_cor(),
            to_begin(),
            to_Conv( 'conv1', 572, 64, offset="(0,0,0)", to="(0,0,0)" ),
            to_Pool("pool1", offset="(0,0,0)", to="(conv1-east)"),
            to_SoftMax( "soft1", "SOFT", 10 ,"(3,0,0)", "(pool1-east)"  ),
            to_connection( "pool1", "soft1"),
            to_end()
            ]

        def main():
            namefile = str(sys.argv[0]).split('.')[0]
            to_generate(arch, namefile + '.tex' )

        if __name__ == '__main__':
            main()

    bash ../tikzmake.sh my_arch

## Examples

Following are some network representations:

<p align="center"><img  src="https://user-images.githubusercontent.com/17570785/50308846-c2231880-049c-11e9-8763-3daa1024de78.png" width="85%" height="85%"></p>
<h6 align="center">FCN-8</h6>


<p align="center"><img  src="https://user-images.githubusercontent.com/17570785/50308873-e2eb6e00-049c-11e9-9587-9da6bdec011b.png" width="85%" height="85%"></p>
<h6 align="center">VGG16</h6>


<p align="center"><img  src="https://user-images.githubusercontent.com/17570785/50308911-03b3c380-049d-11e9-92d9-ce15669017ad.png" width="85%" height="85%"></p>
<h6 align="center">Holistically-Nested Edge Detection</h6>