Txt2Vectorgraphics VS deforum-for-automatic1111-webui

I use the earlier version of this https://github.com/GeorgLegato/Txt2Vectorgraphics and it's great for output destined for cricut, laser, or 2-color z-hop graphics on 3D printer.

Indeed. Same guy who created this cool extension: https://github.com/GeorgLegato/Txt2Vectorgraphics

https://github.com/GeorgLegato/Txt2Vectorgraphics the repo will be renamed to vectorstudio containing the features of this video (svg editor, sendto controlnet:img2img )

In addition I used my Txt2Vectorgraphics script to produce svg graphics as side effect and to ensure b/w only GeorgLegato/Txt2Vectorgraphics: Custom Script for Automatics1111 StableDiffusion-WebUI. (github.com)

Release 0.3: SVG in gallery, controlnet support · GeorgLegato/Txt2Vectorgraphics (github.com)

Deforum https://github.com/deforum-art/deforum-for-automatic1111-webui

might be deforum (project) (webui extension) or img2img loopback wave (webui extension). it's definitely something with img2img though. that's clear from how it's warping.

Thanks for the workflow. To simplify the process I created a PR that hopefully will make it a bit faster, specially if you're working in rented cloud GPU's.

The sequence after the train with the flashing background is the only exception (1:03 to 1:24), that part was made using the Deforum notebook: https://deforum.github.io/

ive gotten better results applying some color correction to my loops using the same way as they do in deforum https://github.com/deforum-art/deforum-for-automatic1111-webui/blob/automatic1111-webui/scripts/deforum_helpers/colors.py

🔸 Deforum extension for Automatic1111 (Local Install): https://github.com/deforum-art/deforum-for-automatic1111-webui

Deforum plugin settings files: render, coloration. The black and white canny edges + scribble-mode mid-stage rendered video. You can check the prompts keyframing file to see if I got the characters names right. Despite my best efforts, some of the characters appearances were off, I think it was either the character names were incorrectly spelled (I was referring to the Touhou wiki) or they had been underrepresented in the dataset or there was overlap between their naming and some other franchises. There is also the issue of random unrelated characters appearing when the prompt contains no characters and instead is purely abstract, I guess it relates to this specific model retraining.