language: en
license: mit
thumbnail: https://i.ibb.co/6NLyc1P/stellar-diffusion.png
tags:
- stable-diffusion
- text-to-image
Stellar Diffusion
Stellar Diffusion v0.1 vs Base Stable Diffusion v1.5
prompt = A hubble photograph of a galaxy
seed = 42
size = 512x512
Version: 0.1
Stable Diffusion 1.5 finetuned on high quality processed space imagery.
Example Results
prompt = A barred spiral galaxy
seed = 44
size = 512x512
prompt = bright, constellation, hubble, clouds
seed = 42
size = 512x512
prompt = a hubble photograph of a nebula
seed = 42
size = 512x512
prompt = ngc 7714
seed = 42
size = 512x512
Suggested parameters
512x512
Reconized Tags
All reconized tags can be found in the tags.txt file. They are generated from the annotated descriptions of the photograph. Current Dataset is small and is poor at generating exact celestial bodies, but is better at generating common generic bodies like nebula, galaxies etc.
Partial support for scientific celestial body tags as follows:
NGC - New General Catalogue of Nebulae and Clusters of Stars
M / Messier - A set of 110 astronomical objects catalogued by the French astronomer Charles Messier
UGC – (catalog) Uppsala General Catalogue, a catalog of galaxies
Partial support for the following classification methods as follows:
By recording instrument/spacecraft (ex. Voyager, Hubble)
By Color
By Celestial Body type
Python Usage
from diffusers import StableDiffusionPipeline
import torch
model_id = "rexwang8/stellar-diffusion"
pipe = StableDiffusionPipeline.from_pretrained(model_id, torch_dtype=torch.float16)
pipe = pipe.to("cuda")
prompt = "A hubble photograph of a galaxy"
image = pipe(prompt).images[0]
image.save("hubble_galaxy.png")
Dataset and Credits
Model
Rex Wang (me!)
RunwayML for their SD 1.5
Compute
Coreweave - 2x A40s
Dataset
91 of the 100 images from https://esahubble.org/ Top 100 Hubble Images ESA/Hubble
Planned
Expansion of dataset to include:
Solar system
Asteroids
More star types
Black holes
Exo planets
More data in general
Version History
V0.1 - 91 image dataset