PyVaporation VS awesome-stable-diffusion

Compare PyVaporation vs awesome-stable-diffusion and see what are their differences.

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PyVaporation awesome-stable-diffusion
4 10
71 1,422
- 2.4%
1.3 0.0
about 1 year ago about 1 month ago
Jupyter Notebook
Apache License 2.0 Mozilla Public License 2.0
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.

awesome-stable-diffusion

Posts with mentions or reviews of awesome-stable-diffusion. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2023-01-29.

What are some alternatives?

When comparing PyVaporation and awesome-stable-diffusion you can also consider the following projects:

discoart - πŸͺ© Create Disco Diffusion artworks in one line

sd-webui-colab - A repo for the maintenance of the Colab version of stable-diffusion-webui repo

Kandinsky-2 - Kandinsky 2 β€” multilingual text2image latent diffusion model

diffusers - πŸ€— Diffusers: State-of-the-art diffusion models for image and audio generation in PyTorch and FLAX.

proposal-symbols-as-weakmap-keys - Permit Symbols as keys in WeakMaps, entries in WeakSets and WeakRefs, and registered in FinalizationRegistries

glid-3-xl-stable - stable diffusion training

doohickey - Doohickey is a stable diffusion tool for technical artists who want to stay up-to-date with the latest developments in the field.

stable_diffusion.openvino

paint-with-words-sd - Implementation of Paint-with-words with Stable Diffusion : method from eDiff-I that let you generate image from text-labeled segmentation map.

stable-diffusion

diffusers-interpret - Diffusers-Interpret πŸ€—πŸ§¨πŸ•΅οΈβ€β™€οΈ: Model explainability for πŸ€— Diffusers. Get explanations for your generated images.

CogVideo - Text-to-video generation. The repo for ICLR2023 paper "CogVideo: Large-scale Pretraining for Text-to-Video Generation via Transformers"