https://github.com/erupturatis/neat-manim
Visualising your neat algorithm networks with the manim library
https://github.com/erupturatis/neat-manim
algorithm manim manim-3b1b manim-animations neat neural-network neural-network-visualizations neuroevolution reinforcement-learning visualization
Last synced: about 1 month ago
JSON representation
Visualising your neat algorithm networks with the manim library
- Host: GitHub
- URL: https://github.com/erupturatis/neat-manim
- Owner: erupturatis
- License: mit
- Created: 2022-08-18T14:55:38.000Z (about 3 years ago)
- Default Branch: master
- Last Pushed: 2023-07-19T13:43:57.000Z (about 2 years ago)
- Last Synced: 2023-07-19T14:41:53.192Z (about 2 years ago)
- Topics: algorithm, manim, manim-3b1b, manim-animations, neat, neural-network, neural-network-visualizations, neuroevolution, reinforcement-learning, visualization
- Language: Python
- Homepage:
- Size: 143 KB
- Stars: 5
- Watchers: 2
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- Contributing: Contributing.md
- License: LICENSE
Awesome Lists containing this project
README
# NEAT Manim
A repository made for visualizing the neat algorithm
networks evolving over the course of multiple generations.
This is an attempt to reproduce videos like
[this one](https://www.youtube.com/watch?v=j8oU0ksQ3Bc&t=0s)
that unfortunately haven't published their repositories
DISCLAIMER !! This repository will only work with winners saved by [this specific implementation](https://github.com/CodeReclaimers/neat-python) of NEAT.
## Run Locally
Clone the project
```bash
git clone https://github.com/erupturatis/Neat-Manim
```
Go to the project directory
```bash
cd Neat-Manim
```
Install dependencies
```bash
pip install -r requirements.txt
```
Note that you have to have manim already installed on your local machine in order to install it with pip. This project uses [manim community](https://github.com/ManimCommunity/manim). You can see how to install it [here](https://docs.manim.community/en/stable/installation.html).
For a quick startup on the manim library you should check [this playlist](https://www.youtube.com/watch?v=rUsUrbWb2D4&list=PLsMrDyoG1sZm6-jIUQCgN3BVyEVOZz3LQ)
### Folder structure and usage
To start with working with this project you should run:
```bash
cd NeatManim
```
And then:
```bash
manim -pql manim_visualization.py VisualizeNetwork
```
This will run the main scene that will run all the other scrips.
Your winner files should be placed in
```
./NeatManim/winners/winner_list/...(here are the winners)
```
The folder should also contain a contain a config.txt file corresponding to the winners in
```
./NeatManim/winners/...(here is the config)
```
And a winners_names.txt file in the same place as the config
```
./NeatManim/winners/...(winners_names)
```
You have some boilerplate winner already placed in there as an example
. If for any reason you can't get this to work feel free to open an issue
## Results
This is the kind of result you should expect
## Contributing
All contributions are always welcome! I would like to expand the functionality of this repo for more machine and deep learning algorithms and eventually turn it into a library.
You could start by editing `contributing.md`