blended-tiling
stable-diffusion-webui-feature-showcase
blended-tiling | stable-diffusion-webui-feature-showcase | |
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2 | 33 | |
25 | 974 | |
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2.7 | 0.0 | |
4 months ago | 7 months ago | |
Python | ||
MIT License | - |
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blended-tiling
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Enhancing local detail and cohesion by mosaicing
I wrote a PyTorch tiling algorithm a while back that works almost the same as yours, with separate control over height and width axes and other stuff: https://github.com/ProGamerGov/blended-tiling
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Testing even higher res 3200x1920 (I think my 3090 is melting ;)
This PyTorch based seamless tile blending solution I made a while back might be able to help you push out higher resolutions of any size, while also keeping each tile at 512x512: https://github.com/ProGamerGov/blended-tiling
stable-diffusion-webui-feature-showcase
- How to turn anime image to realistic image in stable diffusion?
- [Stable Diffusion] inversion textuelle avec AUTOMATIC1111 webui
- [Ainudes] Comment créer des nus IA ?
- Is there any documentation for Automatic1111 WebUI?
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Is there a properly comprehensive guide on prompt syntax?
A1111 https://github.com/AUTOMATIC1111/stable-diffusion-webui-feature-showcase
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Which one is the "official" version
Here's a quick rundown on a few of the most popular ones with links. I started out using CMDR2, which is very easy to get running as a newbie. Then I kind of graduated to NMKD because I wanted something a little more mainstream but still easy to use. Then, I finally decided I was hungry for all the strange and exotic bells and whistles that SD had to offer me, and so I installed Automatic1111. I also wanted something that would work well with my 4GB GTX 1650 laptop card, because that's considered "low ram" and kind of on the edge for running SD- Automatic1111 fit the bill there, too.
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At your service...
All generations were on the "Berry's Mix" model, which is made by combining NAI-final, Zenith's F111, r34 and SD1.4 according to this recipe. I used 30ish steps when generating images and inpainting, but 70-80 steps when outpainting because I read here that outpainting really benefits from extra steps. When outpainting I would generate 2-4 versions and pick the least broken one, then tidy up with inpainting.
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What's the name of this feature?
sounds like "outpainting", one of the very first features listed on 1111 repo with some instructions: https://github.com/AUTOMATIC1111/stable-diffusion-webui-feature-showcase
- How do you expand an image? (image to image)
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Running neural networks locally.
I have no idea what you're talking about. Just get Automatic1111
What are some alternatives?
xpytile - Automatic / dynamic window tiling for XFCE
CogVideo - Text-to-video generation. The repo for ICLR2023 paper "CogVideo: Large-scale Pretraining for Text-to-Video Generation via Transformers"
glid-3-xl-stable - stable diffusion training
stable-diffusion - This version of CompVis/stable-diffusion features an interactive command-line script that combines text2img and img2img functionality in a "dream bot" style interface, a WebGUI, and multiple features and other enhancements. [Moved to: https://github.com/invoke-ai/InvokeAI]
stable-diffusion-webui - Stable Diffusion web UI
stable-diffusion - Optimized Stable Diffusion modified to run on lower GPU VRAM
diffusionbee-stable-diffusion-ui - Diffusion Bee is the easiest way to run Stable Diffusion locally on your M1 Mac. Comes with a one-click installer. No dependencies or technical knowledge needed.
StableDiffusion-Windows-GUI
txt2imghd - A port of GOBIG for Stable Diffusion
diffusers-interpret - Diffusers-Interpret 🤗🧨🕵️♀️: Model explainability for 🤗 Diffusers. Get explanations for your generated images.
diffusion-ui - Frontend for deeplearning Image generation
stable-diffusion-ui - Easiest 1-click way to install and use Stable Diffusion on your computer. Provides a browser UI for generating images from text prompts and images. Just enter your text prompt, and see the generated image. [Moved to: https://github.com/easydiffusion/easydiffusion]