Stellar Diffusion
Stellar Diffusion v0.2 vs Base Stable Diffusion v1.5
prompt = A hubble photograph of a galaxy
seed = 42
size = 512x512
Version: 0.2 (Nebula) (Dreambooth / .ckpt formats)
Stable Diffusion 1.5 finetuned on high quality processed space imagery.
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")
Example Results
Suggested parameters
512x512
Place subjects and styles at the very front, roll a few times if you don't get the results you want.
Great - Nebulas, Galaxies
Good - Black holes, Pulsars, Comets, Jupiter
Decent - All other solar system planets
Reconized Tags
All reconized tags can be found in the tags.txt file. They are generated from the annotated descriptions of the photograph.
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
Dataset and Credits
Model
Rex Wang (me!)
RunwayML for their SD 1.5
Compute
Coreweave - 2x A40s (~3 A40 hours)
Dataset
91 of the 100 images from https://esahubble.org/ Top 100 Hubble Images ESA/Hubble
~100 additional images from ESA/Hubble and ~10 images from ESA/Webb
~50 additional images from images.nasa.gov
Version History
V0.2 (Codename: Galaxy) - 264 image dataset
V0.1 - 91 image dataset
Contact me
All feedback, criticisms, complaints, etc to discord preferably.
Discord: bob#1236
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