voltaML-fast-stable-diffusion VS clip-interrogator

Also, VoltaML has a good reference GPU AITemplate SD 1.5 implementation:

https://github.com/VoltaML/voltaML-fast-stable-diffusion/tre...

The speed jump is massive on my desktop GPU, probably even more dramatic on cloud hardware, and it may support some things (weight swapping/lora swapping/resolution changing) better than JAX.

This kind of drama is just sad.

I dont know if you are OP, but plenty of other UIs have interrogator code, like https://github.com/VoltaML/voltaML-fast-stable-diffusion/tre...

If you just want an accelerated ui, you can check https://github.com/ddPn08/Lsmith/ or https://github.com/VoltaML/voltaML-fast-stable-diffusion which also use the same origina nvidia code. These projects don't do img2img though, you can check in my repo for the img2img pipeline if you need. You need to compile the tensorrt engines for the models first. There are a few steps you can check in their script: export onnx, optimize onnx, compile engine for optimized onnx. I streamlined that a bit and I normally just run my compile.py in docker to build engines.

Try https://github.com/VoltaML/voltaML-fast-stable-diffusion

This one: VoltaML/voltaML-fast-stable-diffusion: Lightweight library to accelerate Stable-Diffusion, Dreambooth into fastest inference models with single line of code 🔥 🔥 (github.com)

You will be waiting a lot longer for this to be implemented: https://github.com/VoltaML/voltaML-fast-stable-diffusion

It's image -> words, the inverse of stable diffusion.

see: https://github.com/pharmapsychotic/clip-interrogator

I have been using this on a CPU https://github.com/pharmapsychotic/clip-interrogator, I tried a lot of pre-trained models combinations, all are slow.

I'm addition to controlnet, try the clip interrogator to see how clip would describe the image and then use that language in your prompt. You can try the whole image or cropped portions. There is a colab available if you don't want to run it locally.

In my current process, I use CLIP Interrogator to produce a high level caption and wd14 tagger for more granular booru tags. Typically in that order, because you can append the results from the latter to the former. Both tools perform with greater accuracy than the standard interrogators in img2img and give you more flexibility and features as well. You still have to do some manual adjustments, but I generally prefer this process over starting from scratch.

If you are interested in this, definitely see if you can get some of the OSS models running and get a feel for how to interrogate them. Maybe see if you can get some mileage out of the CLIP-Interrogator

Next, I used the lists of artists, flavors, mediums, movements, and negatives that are used for the clip-interrogator and pasted these in the chat and told the bot to categorize them accordingly. As you can only paste up to certain characters in single message (4-5K in 3.5 and 6-8K in 4).

Here’s the specific one I’m using (runs in browser)

I really enjoy using the CLIP Interrogator on huggingspaces, but it is often super slow and sometimes straight up breaks. Now it is possible to locally install it, https://github.com/pharmapsychotic/clip-interrogator but I don't know if its viable to run on a laptop with 6gb videocard anyway.