stable-diffusion VS cog-stable-diffusion

Download this training project: git clone https://github.com/justinpinkney/stable-diffusion.git

looks like it's using the https://github.com/justinpinkney/stable-diffusion/blob/4ac995b6f663b74dfe65400285e193d4167d259c/scripts/gradio_image_mixer.py to do the bulk of the work meaning the core functionality is built into stable diffusion, seems the UI just isn't built to support it. Their ckpt is here too https://huggingface.co/lambdalabs/image-mixer/tree/main.

Any idea how to make Image Mixer work in this build? On RTX 3060 with 12Gb of memory I get the message:

References: ►Read the full article: https://www.louisbouchard.ai/imagic/ ►Kawar, B., Zada, S., Lang, O., Tov, O., Chang, H., Dekel, T., Mosseri, I. and Irani, M., 2022. Imagic: Text-Based Real Image Editing with Diffusion Models. arXiv preprint arXiv:2210.09276. ► Use it with Stable Diffusion: https://github.com/justinpinkney/stable-diffusion/blob/main/notebooks/imagic.ipynb ►My Newsletter (A new AI application explained weekly to your emails!): https://www.louisbouchard.ai/newsletter/

The notebook: https://github.com/justinpinkney/stable-diffusion/blob/main/notebooks/imagic.ipynb

There's a script for the SD --> Diffusers here: https://github.com/justinpinkney/stable-diffusion/blob/main/scripts/convert_sd_to_diffusers.py

You can start with the github which contains the code: https://github.com/justinpinkney/stable-diffusion

Hmmm, I just double checked the hashes of my local file, what's on huggingface, and what you showed above and they all match. I'm not familiar with that repo, so maybe something weird is going on. I tested it using the original txt2img script in the stable diffusion repo:

*PICK\* (Added Sep. 12, 2022) Web app Stable Diffusion Image Variations by lambdalabs. GitHub repo. Generates variations of an input image without use of a text prompt. Censored.

Stable Diffusion

stable-diffusion: A latent text-to-image diffusion model capable of generating photorealistic images given any text input

Next, make a Flask app so your app can receive the inbound text message to your Twilio phone number. That string is then passed to Replicate 's stable diffusion model to generate photo-realistic images given that prompt.

The Azure Function App executes a serverless function that: a) Runs the text summary model (Azure Cognitive Service for Language) b) Runs the image generation model (stable-diffusion on Replicate AI) c) Uploads the image to Azure Blob Storage

I'm testing prompts online because it's faster than my computer: https://replicate.com/stability-ai/stable-diffusion

There isn't a direct integration with Zapier, but you can use the Webhooks & API calls within Zapier to connect to Stable diffusion. The simplest way is to do it through Replicate: https://replicate.com/stability-ai/stable-diffusion

I ended up using stable diffusion from replicate. They don't have a filter on the input text, they just analyse the output for NSWF and block it if it seems to be NSFW. So sometimes NSWF-ish pictures may slip through.

I'm getting same-ish results as mine with replicate. They don't have PLMS as an option and euler trips that silly porn filter on the dressed pirates for whatever reason, but it seems to closely match.