File:Algorithmically-generated black and white portrait art of a young Japanese woman in the snow.png

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Summary

Description

Algorithmically-generated AI portrait artwork in monochrome style, featuring a young Japanese woman at the front of a castle on a snowy day, created using the Stable Diffusion V1-4 AI diffusion model.

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 single 512x768 image was generated with txt2img using the following prompts:

Prompt: black and white, highly detailed line art, (close up shot of:0.6) (full body1.3) of a teenage Japanese geisha girl (pretty face:1.4) (realistic eyes:1.2) (detailed pupils) (ornate coiffed hair), in front of battlements, on a moonlit night, snowfall, [:falling snowflakes:0.7], by (Yoji Shinkawa:1.2), (Kentaro Miura), (WLOP), (Artgerm), (intricate human hands), [bodycon] intricate

Negative prompt: disney, two heads, ((mutated hands and fingers and face and nose)) (walleyed), blurred face, ((poorly drawn face)) (long neck) ((ugly)) frown, ((neutral expressions)), curly hair, [[child]]

Settings: Steps: 50, Sampler: Euler a, CFG scale: 6, Size: 512x768

Afterwards, the image was extended by 256 pixels total on the bottom using two 128 pixel passes of the "Outpainting mk2" script within img2img. This was done using a setting of 100 sampling steps with Euler a, denoising strength of 0.8, CFG scale of 7, mask blur of 8, fall-off exponent value of 1.8, colour variation set to 0.03. This subsequently increases the image's dimensions to 512x1024, while also revealing the young woman's hands and lower dress, which were previously absent from the original AI-generated image made within txt2img which only featured the woman from the navel upwards.

Then, two passes of the SD upscale script using "SwinIR_4x" were run within img2img. The first pass used a tile overlap of 64, denoising strength of 0.1, 150 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, 150 sampling steps with Euler a, and a CFG scale of 7. This creates our final 2048x4096 image.
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Author Benlisquare
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(Reusing this file)
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.

Licensing

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attribution share alike
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  • share alike – If you remix, transform, or build upon the material, you must distribute your contributions under the same or compatible license as the original.
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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7 October 2022

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current22:47, 7 October 2022Thumbnail for version as of 22:47, 7 October 20222,048 × 4,096 (11.19 MB)Benlisquare{{Information |Description=Algorithmically-generated AI portrait artwork in monochrome style, featuring a young Japanese woman at the front of a castle on a snowy day, created using the [https://github.com/CompVis/stable-diffusion Stable Diffusion V1-4] AI diffusion model. ;Procedure/Methodology All artworks created using a single NVIDIA RTX 3090. Front-end used for the entire generation process is [https://github.com/AUTOMATIC1111/stable-diffusion-webui Stable Diffusion web UI] created by [...
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