Synthetic GPR Image Generation using Generative Adversarial Networks
Copyright (C) 2020  Jan Rottmayer

This program is free software: you can redistribute it and/or modify
it under the terms of the GNU General Public License as published by
the Free Software Foundation, either version 3 of the License, or
(at your option) any later version.

This program is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
GNU General Public License for more details.

You should have received a copy of the GNU General Public License
along with this program.  If not, see <https://www.gnu.org/licenses/>.

Boundless Generative Adversarial Network

This code is part of my project work in generating synthetic Ground Penetrating Radar Grams using Generative Adversarial Networks. The model architecture is fully based on Boundless .

Installation

The model requirements are given in the requirements.txt file. The most important dependency is pytorch 1.7.1

Install the dependencies in your local environment.

$ pip install -r requirements.txt

General Useage

Training the model

$ python model.py

Reset Standard Model

$ python reset.py

Generate panorama sample (experimental)

$ python panorama_sample.py

Dataset

Create "/data" and place your own dataset in it. The subfolder structure is irrelevant.