NectarGAN - Getting Started
This document will guide you through the process of installing NectarGAN, and get you started using the NectarGAN Toolbox, training and testing models from the command line, and interacting with the NectarGAN API.
Installing NectarGAN
Windows / Linux
[!TIP] It is recommended to install NectarGAN in a fresh environment to avoid dependency conflicts, especially as it is still in active development.
NectarGAN requires a Python version >=
3.12.
- Clone the repository:
git clone https://github.com/ZacharyBork/NectarGAN.git - Navigate to the repository root and run:
- Pip:
pip install .
- Anaconda:
conda env create -f environment.yml
- Install your preferred version of PyTorch:
From: https://pytorch.org/get-started/locally/
Version Command CPU-Only pip install torch torchvisionCUDA 11.8 pip install torch torchvision --index-url https://download.pytorch.org/whl/cu118CUDA 12.6 pip install torch torchvision --index-url https://download.pytorch.org/whl/cu126CUDA 12.8 pip install torch torchvision --index-url https://download.pytorch.org/whl/cu128
NectarGAN Docker
It is also possible to run headless training and testing with NectarGAN from a Docker container, using Visdom for runtime data visualization!
Please see the Docker quickstart guide for more information.
NectarGAN Toolbox
The Toolbox quickstart guide is split in to three sections which are intended to be followed in order.
Section 1: Training a Model
Section 2: Testing a Model
Section 3: Reviewing Results
NectarGAN CLI
For more information regarding the CLI options currently offered by NectarGAN, please see the NectarGAN CLI quickstart.
NectarGAN API
Please see the API documentation for more information on getting started with the NectarGAN API.
Testing your installation
If you would like to test whether your installation is working correctly, NectarGAN includes a number of prebuilt tests which are run in different ways depending upon your installation type. See here for more information.
Downloading a premade dataset
NectarGAN includes a script that allows you to automatically download a number of premade datasets to test your models on.
Please see here for more information.