File:Twenty algorithmically-generated artworks of women created from a single Stable Diffusion prompt.png

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Description

Demonstration of the uniformity of artstyles for algorithmically-generated artworks created using exact same text prompt when using the Stable Diffusion V1-4 AI diffusion model. When the text prompt is kept the same, there is, subjectively at least, a definite visual similarity in motifs, painting styles, human anatomical proportions, and lighting effects among AI-generated outputs, even if other variables such as sampler steps, sampler type and CFG are different.

As an example of how the visual style of generated AI artwork does differ when the text prompt is changed, compare with the following image which uses a different prompt to generate the images:

Procedure/Methodology

All artworks created using a single NVIDIA RTX 3090. Front-end used for the entire generation process is Stable Diffusion web UI created by AUTOMATIC1111.

A batch of twenty 512x512 images were generated with txt2img using the following prompts:

Prompt: busty young girl, art style of artgerm and greg rutkowski

Negative prompt: (((deformed))), [blurry], bad anatomy, disfigured, poorly drawn face, mutation, mutated, (extra_limb), (ugly), (poorly drawn hands), messy drawing, ((((mutated hands and fingers))))

Among these images, an assortment of different sampling settings were selected, which include:

  • Steps: 50, Sampler: LMS, CFG scale: 7.5
  • Steps: 16, Sampler: Euler a, CFG scale: 7
  • Steps: 50, Sampler: Euler a, CFG scale: 7
  • Steps: 100, Sampler: Euler a, CFG scale: 7
  • Steps: 50, Sampler: Heun, CFG scale: 7
  • Steps: 50, Sampler: DPM2 a, CFG scale: 7
  • Steps: 50, Sampler: DDIM, CFG scale: 7
  • Steps: 50, Sampler: PLMS, CFG scale: 7
Then, two passes of the SD upscale script using "Real-ESRGAN 4x plus anime 6B" were run within img2img. The first pass used a tile overlap of 64, denoising strength of 0.3, 50 sampling steps with Euler a, and a CFG scale of 7. The second pass used a tile overlap of 128, denoising strength of 0.1, 10 sampling steps with Euler a, and a CFG scale of 7.
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Author Benlisquare
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Output images

As the creator of the output images, I release this image under the licence displayed within the template below.

Stable Diffusion AI model

The Stable Diffusion AI model is released under the CreativeML OpenRAIL-M License, which "does not impose any restrictions on reuse, distribution, commercialization, adaptation" as long as the model is not being intentionally used to cause harm to individuals, for instance, to deliberately mislead or deceive, and the authors of the AI models claim no rights over any image outputs generated, as stipulated by the license.

Addendum on datasets used to teach AI neural networks
Artworks generated by Stable Diffusion are algorithmically created based on the AI diffusion model's neural network as a result of learning from various datasets; the algorithm does not use preexisting images from the dataset to create the new image. Ergo, generated artworks cannot be considered derivative works of components from within the original dataset, nor can any coincidental resemblance to any particular artist's drawing style fall foul of de minimis. While an artist can claim copyright over individual works, they cannot claim copyright over mere resemblance over an artistic drawing or painting style. In simpler terms, Vincent van Gogh can claim copyright to The Starry Night, however he cannot claim copyright to a picture of a T-34 tank painted with similar brushstroke styles as Gogh's The Starry Night created by someone else.

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GNU head Permission is granted to copy, distribute and/or modify this document under the terms of the GNU Free Documentation License, Version 1.2 or any later version published by the Free Software Foundation; with no Invariant Sections, no Front-Cover Texts, and no Back-Cover Texts. A copy of the license is included in the section entitled GNU Free Documentation License.
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current19:05, 27 September 2022Thumbnail for version as of 19:05, 27 September 202210,240 × 8,192 (52.31 MB)Benlisquare (talk | contribs){{Information |Description=Demonstration of the uniformity of artstyles for algorithmically-generated artworks created using exact same text prompt when using the [https://github.com/CompVis/stable-diffusion Stable Diffusion V1-4] AI diffusion model. When the text prompt is kept the same, there is, subjectively at least, a definite visual similarity in motifs, painting styles, human anatomical proportions, and lighting effects among AI-generated outputs, even if other variables such as sample...

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