HarisIqbal88/PlotNeuralNet
HarisIqbal88/PlotNeuralNet has 25,079 GitHub stars and 3,063 forks. GitHot measured +1 stars in 24 hours. Last checked 2026-11-06 06:28 UTC. Last push 2023-08-21.
Código LaTeX para crear diagramas de redes neuronales
Crecimiento de estrellas medido
- in 24h
- +1
- in 7 days
- Actualización retrasada
- in 15 days
- Actualización retrasada
- in 1 month
- Actualización retrasada
Cambios netos en períodos que se solapan, no totales diarios. Los datos no disponibles se dejan en blanco. Las estrellas indican interés, no calidad.
README.md
OriginalPlotNeuralNet
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.
Examples
Following are some network representations:

FCN-8 (view on Overleaf)

FCN-32 (view on Overleaf)

Holistically-Nested Edge Detection (view on Overleaf)
Getting Started
Install the following packages on Ubuntu.
Ubuntu 16.04
sudo apt-get install texlive-latex-extraUbuntu 18.04.2 Base on this website, please install the following packages.
sudo apt-get install texlive-latex-base sudo apt-get install texlive-fonts-recommended sudo apt-get install texlive-fonts-extra sudo apt-get install texlive-latex-extraWindows
- Download and install MikTeX.
- Download and install bash runner on Windows, recommends Git bash or Cygwin(https://www.cygwin.com/)
Execute the example as followed.
cd pyexamples/ bash ../tikzmake.sh test_simple
TODO
- Python interface
- Add easy legend functionality
- Add more layer shapes like TruncatedPyramid, 2DSheet etc
- Add examples for RNN and likes.
Latex usage
See examples directory for usage.
Python usage
First, create a new directory and a new Python file:
$ mkdir my_project
$ cd my_project
vim my_arch.py
Add the following code to your new file:
import sys
sys.path.append('../')
from pycore.tikzeng import *
# defined your arch
arch = [
to_head( '..' ),
to_cor(),
to_begin(),
to_Conv("conv1", 512, 64, offset="(0,0,0)", to="(0,0,0)", height=64, depth=64, width=2 ),
to_Pool("pool1", offset="(0,0,0)", to="(conv1-east)"),
to_Conv("conv2", 128, 64, offset="(1,0,0)", to="(pool1-east)", height=32, depth=32, width=2 ),
to_connection( "pool1", "conv2"),
to_Pool("pool2", offset="(0,0,0)", to="(conv2-east)", height=28, depth=28, width=1),
to_SoftMax("soft1", 10 ,"(3,0,0)", "(pool1-east)", caption="SOFT" ),
to_connection("pool2", "soft1"),
to_end()
]
def main():
namefile = str(sys.argv[0]).split('.')[0]
to_generate(arch, namefile + '.tex' )
if __name__ == '__main__':
main()
Now, run the program as follows:
bash ../tikzmake.sh my_arch
Explorar proyectos relacionados
tensorflow/tensorflow
Un framework de código abierto de aprendizaje automático para todos
201,311 estrellashuggingface/transformers
🤗 Transformers: el framework de definición de modelos para modelos de aprendizaje automático de vanguardia en texto, visión, audio y multimodal, tanto para inferencia como para entrenamiento.
168,576 estrellasAUTOMATIC1111/stable-diffusion-webui
Interfaz web de Stable Diffusion
165,264 estrellasComfy-Org/ComfyUI
La GUI, la API y el backend más potentes y modulares para modelos de difusión, con una interfaz de grafos y nodos. El motor de inferencia local más rápido del mundo.
145,310 estrellas