描述Algorithmically-generated AI-generated artwork of a cyberpunk cityscape.png |
Algorithmically-generated AI artwork featuring a cyberpunk cityscape, 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 768x512 image was generated with txt2img using the following prompts:
Prompt: digital painting of a cyberpunk cityscape, neon signs, futuristic, art style of range murata artgerm norman rockwell wlop katsuhiro otomo shintaro kago monet
Negative prompt: none
Settings: Steps: 50, Sampler: Euler a, CFG scale: 7, Size: 768x512
Afterwards, the image was extended by 128 pixels on the top, bottom, left and right sides using fourteen successive passes of the "Outpainting mk2" script within img2img, adding additional detail to the image one after the other, until the image's dimensions reached 2048x1024 as its natively generated size (prior to the commencement of any upscaling). For each individual pass, 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 increased the field of view of the image compared to the originally generated image, from one tiny portion of the street in the centre of the image, to a significantly wider view showing the buildings on both sides, in addition to the pedestrian foreground and cityscape in the distance.
Then, two passes of the SD upscale script using "SwinIR_4x" were run within img2img. The first pass used a tile overlap of 128, 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 256, denoising strength of 0.1, 150 sampling steps with Euler a, and a CFG scale of 7. This creates our final 8192x4096 image. |
授權許可 (重用此檔案) |
- 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. |