On-Lindenmayer-Systems-and-Autoencoders

use parametric Lindenmayer system for generation of a dataset by dataset_generator.py
analyze the dataset via PCA by eigenimages.py and try to generate images
train autoencoder by autoencoder.py, check quality of the trained model and create a dataset of feature vectors
analyze the latet space of the autoencoder via PCA by eigencodes.py
play with the generator of images from feature vectors by generator.py
recognize paramaters of the dataset by encoder-regression.py or encoder-perceptron.py
train perceptron which generates feature vectors from the dataset parameters by decoder-perceptron.py and employ it for generator of images from the parameters by final-generator.py

Name		Name	Last commit message	Last commit date
Latest commit History 7 Commits
autoencoder		autoencoder
dataset		dataset
decoder		decoder
eigencodes		eigencodes
eigenimages		eigenimages
encoder		encoder
generator		generator
LICENSE		LICENSE
README.md		README.md
autoencoder.py		autoencoder.py
dataset_generator.py		dataset_generator.py
decoder-perceptron.py		decoder-perceptron.py
eigencodes.py		eigencodes.py
eigenimages.py		eigenimages.py
encoder-perceptron.py		encoder-perceptron.py
encoder-regression.py		encoder-regression.py
final-generator.py		final-generator.py
generator.py		generator.py
lsys.py		lsys.py

andylucny/On-Lindenmayer-Systems-and-Autoencoders