Haris Iqbal
68 lines
2.3 KiB
Markdown
68 lines
2.3 KiB
Markdown
# PlotNeuralNet
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[](https://doi.org/10.5281/zenodo.2526396)
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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.
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## TODO
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- [X] Python interfaz
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- [ ] Add easy legend functionality
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- [ ] Add more layer shapes like TruncatedPyramid, 2DSheet etc
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- [ ] Add examples for RNN and likes.
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## Latex Usage
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see examples
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## PyUsage
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mkdir my_project
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cd my_project
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vim my_arch.py
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import sys
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sys.path.append('../')
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from pycore.tikzeng import *
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# defined your arch
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arch = [
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to_head( '..' ),
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to_cor(),
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to_begin(),
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to_Conv("conv1", 512, 64, offset="(0,0,0)", to="(0,0,0)", height=64, depth=64, width=2 ),
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to_Pool("pool1", offset="(0,0,0)", to="(conv1-east)"),
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to_Conv("conv2", 128, 64, offset="(1,0,0)", to="(pool1-east)", height=32, depth=32, width=2 ),
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to_connection( "pool1", "conv2"),
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to_Pool("pool2", offset="(0,0,0)", to="(conv2-east)", height=28, depth=28, width=1),
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to_SoftMax("soft1", 10 ,"(3,0,0)", "(pool1-east)", caption="SOFT" ),
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to_connection("pool2", "soft1"),
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to_end()
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]
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def main():
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namefile = str(sys.argv[0]).split('.')[0]
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to_generate(arch, namefile + '.tex' )
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if __name__ == '__main__':
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main()
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bash ../tikzmake.sh my_arch
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## Examples
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Following are some network representations:
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<p align="center"><img src="https://user-images.githubusercontent.com/17570785/50308846-c2231880-049c-11e9-8763-3daa1024de78.png" width="85%" height="85%"></p>
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<h6 align="center">FCN-8</h6>
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<p align="center"><img src="https://user-images.githubusercontent.com/17570785/50308873-e2eb6e00-049c-11e9-9587-9da6bdec011b.png" width="85%" height="85%"></p>
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<h6 align="center">FCN-32</h6>
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<p align="center"><img src="https://user-images.githubusercontent.com/17570785/50308911-03b3c380-049d-11e9-92d9-ce15669017ad.png" width="85%" height="85%"></p>
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<h6 align="center">Holistically-Nested Edge Detection</h6>
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