Skip to content


Switch branches/tags

Name already in use

A tag already exists with the provided branch name. Many Git commands accept both tag and branch names, so creating this branch may cause unexpected behavior. Are you sure you want to create this branch?

Latest commit


Git stats


Failed to load latest commit information.
Latest commit message
Commit time

Andy Lomas Generative Art Dataset (ALGAD) V1.0

Repository of a generative art dataset by computer artist Andy Lomas.

Lomas Image

This repository contains a collection of 1,774 images created by computational artist Andy Lomas. The images were created using a customised cell growth model developed by the Artist [1]. Forms were evolved using Lomas' Species Explorer software [2]. In addition to the images, a csv file contains information on the parameters used to generate each form, along with an artist-assigned aesthetic ranking (0-10) and categorisation.

This dataset is provided for research purposes under the Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License. To view a copy of this license, visit or send a letter to Creative Commons, PO Box 1866, Mountain View, CA 94042, USA.

For more information on the dataset, please see the following papers:

Jon McCormack and Andy Lomas, "Deep Learning of Individual Aesthetics", Neural Computing and Applications, DOI: 10.1007/s00521-020-05376-72020 Paper on SpringerLink or Preprint on arxiv

Jon McCormack and Andy Lomas, Understanding Aesthetic Evaluation using Deep Learning, In: Romero J., et al.(eds) Artificial Intelligence in Music, Sound, Art and Design. EvoMUSART 2020. LNCS vol 12103. Springer, Cham (2020), Paper on arxiv

Thank you

Jon McCormack and Andy Lomas

Database format

The database is supplied as a single csv file (Lomas Dataset.csv), the first line is the column labels, the remaining lines are the data. Here is an explanation of the labeled columns:

Column Label Description
uid Unique identifier
fileName file name of the image associated with this entry
score artist assigned score (0-10)
category artist assigned category
planarFactor developmental gene parameter 1
springFactor developmental gene parameter 2
bulgeFactor developmental gene parameter 3
shortSplitFactor developmental gene parameter 4
bendSplitFactor developmental gene parameter 5
colinearSplitFactor developmental gene parameter 6
opositeEdgeFactor developmental gene parameter 7
randomSplitFactor developmental gene parameter 8
collisionRadius developmental gene parameter 9
collisionStrength developmental gene parameter 10
foodIncMin developmental gene parameter 11
foodIncRand developmental gene parameter 12


There are 8 artist-assigned categories, representing the general visual class discovered through exploration of the generative system. Each image has a single assigned category.

Category Number of Images
brain 317
mess 539
nogrowth 154
ballon 169
animal 104
black 251
worms 53
plant 187

Here is a visual map of each category in phenotype space. The image is dimensionally reduced from 2048 features to the 2D point in the plot using the t-SNE algorithm:

Phenotype Map by Category


The images are in the Image directory, the names correspond to those in the dataset csv file.

imageThumbs.tgz contains thumbnail (128x128) versions of all the images.

The original images are too big to be stored on Github so can be downloaded from this link.


[1] Lomas, A.: Cellular forms: An artistic exploration of morphogenesis. In: AISB 2014 - 50th Annual Convention of the AISB (2014)

[2] Lomas, A.: Species explorer: An interface for artistic exploration of multi-dimensional parameter spaces. In: J. Bowen, N. Lambert, G. Diprose (eds.) Electronic Visualisation and the Arts (EVA2016), Electronic Workshops in Computing (eWiC). BCS Learning and Development Ltd., London (2016)