dykyivladk1 / ProGAN

This is Progressive Growing of GANs implementation.

ProGAN Implementation

This repository contains the implementation of Progressive Growing of GANs. This type of GAN is designed to generate high-quality images.

Getting Started

Follow these steps to use this implementation:

Prerequisites

Ensure you have Python installed on your system. This code is compatible with Python 3.9 and newer versions.

Dataset

For training and testing the ProGAN model, you'll need a dataset. I used CelebA dataset which you download using the following link:

CelebA Link

After downloading, place the dataset in an appropriate directory within the your project structure, such as "./data".

Installation

1. Clone the repository to your local computer:

   git clone https://github.com/dykyivladk1/ProGAN.git
   

2. Install the required dependencies. It's recommended to create and use a virtual environment:

   python -m venv venv
   source venv/bin/activate  # On Windows use `venv\Scripts\activate`
   pip install -r requirements.txt
   

3. Training model

   To train a model for custom dataset, you can use the following command:

   python scripts/trainer.py --train_dir <train_path>
   

4. Visualisations

   You can use Netron app for opening the .onnx files stored in visualisations folder. I used them for understanding the model structure.

5. Note

   If you want to see my documentation for this model you can visit the following link on Notion:

   Documentation