A better (?) way of doing img2img by finding the noise which reconstructs the original image

• stable-diffusion-webui

  2,808 129,975 9.9 Python

  Stable Diffusion web UI

i guess the development of this feature is still in an early state, but i managed to get the first results. basically you upload an image in img2img, interrogate to obtain the prompt ---this gives me a low vram error but still generates the prompt that you'll find on top--- in the scripts you use img2imgalternative with that prompt you have obtained (check https://github.com/AUTOMATIC1111/stable-diffusion-webui in the img2imgalt section for the parameters they are very strict for now) now generate and you should get an output very similar to your original image if you change your main prompt now (still running the script with the previously obtained prompt) you should be able to modify the image keeping most of the details

• RePaint

  2 1,705 0.0 Python

  Official PyTorch Code and Models of "RePaint: Inpainting using Denoising Diffusion Probabilistic Models", CVPR 2022

This seems to be a very similar method to RePaint.

• InfluxDB

  www.influxdata.com featured

  Power Real-Time Data Analytics at Scale. Get real-time insights from all types of time series data with InfluxDB. Ingest, query, and analyze billions of data points in real-time with unbounded cardinality.

  

• txt2imghd

  22 689 0.0 Python

  A port of GOBIG for Stable Diffusion

https://github.com/jquesnelle/txt2imghd The link was literally in the Auto's code's comments.

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