🏞️ Variational Autoencoder for Meandering Rivers

This repository contains an implementation of a Variational Autoencoder (VAE) model for generating 128x128 images of meandering rivers.

🛠️ Requirements

🚀 Usage

📓 Notebooks

Fully Connected

• Training the VAE Fully Connected: train_vae_fconnected_notebook
• Evaluating the VAE Fully Connected: eval_vae_fconnected_notebook

Fully Convolutional

• Training the VAE Fully Convolutional: train_vae_fconv_notebook
• Evaluating the VAE Fully Convolutional: eval_vae_fconv_notebook

GIFs & Videos

• Generating GIFs/Videos: video_gif_generator.ipynb

📦 Installing Dependencies

You can install all the necessary dependencies listed in the requirements.txt file using one of the following methods:

1. Using pip from the terminal

If you are in the root directory of the project, where the requirements.txt file is located, run:

$ pip install -r requirements.txt

🤖 Train

If you prefer to run the model directly without using the notebooks, you can execute the training script from the terminal:

Fully Connected

!python train.py --path "./train_images.h5" --model fconnected  --batch_size 128 --epochs 100

Fully Convolutional

!python train.py --path "./train_images.h5" --model fconv --batch_size 128 --epochs 100

This will start the training process using the train.py script, which is configured to load the dataset, prepare the model, and begin training.