sd-extension-system-info VS stable-diffusion-webui-two-shot

I've been using both SD and various LLM on linux without any issue and have done so for months. Windows support is also starting to roll out slowly, with koboldcpp-rocm recently giving me 20-25+t/s for a13B even on windows. you can see what SD performance is like on sites like these. those numbers roughly match what i get on my RX6800 as well (8t/s).

That seems a lot worse than a 2060 SUPER with PyTorch in A1111.

https://vladmandic.github.io/sd-extension-system-info/pages/... (search for 2060 SUPER)

But usually A1111 users use benchmark on this extension https://github.com/vladmandic/sd-extension-system-info

AMD SD = Setup Diaster? it was quite troublesome googling the few linux/amdgpu/rocm/sd vers/configs/params posts online. Also the whole PC may hang during generation which is bad for the harddisk. Your card is way more powerful so may not hang like mine. People are getting 8it/s https://vladmandic.github.io/sd-extension-system-info/pages/benchmark.html

According to system info benchmark, M40 is like 1-2 it/s and P4 is barely better than that.

Anyway to properly "benchmark" the impacts different switches on your image generation speed, it is better to use the benchmarking utility from extension https://github.com/vladmandic/sd-extension-system-info (it also creates a very handy table of results from other users at https://vladmandic.github.io/sd-extension-system-info/pages/benchmark.html for you to compare with.

I can see that the top performance benchmark results on SD WebUI Benchmark Data (using RTX 4090), are obtained through WSL2 running Automatic1111 on a Linux dist and Python 3.10.11, along with PyTorch 2.1.0.dev+cu121 (like benchmark id: 4126)

You should be able to compare based on the published benchmarks, just replicate the settings based on what's reported https://vladmandic.github.io/sd-extension-system-info/pages/benchmark.html

I tried Regional Prompter and Latent Couple (https://github.com/ashen-sensored/stable-diffusion-webui-two-shot) extension but they don't seem to work properly (latter has awful documentation/examples).

Option 5 is to buy a smallish GPU farm and simply rely on good specific and regional prompting pushed through brute forced generations to extract similar looking places out of the thousands of hallucinations. Some loras, checkpoints, regional prompting with the Latent Couple extension in A1111, and an abundant abuse of ControlNet could also help.

Use Latent Couple with Composable LoRA instead

The solution to this is to use the 'Latent Couple' plugin.

All three used the same prompt, which requires the Latent Couple extension.

git clone -b feature/mask_selection https://github.com/ashen-sensored/stable-diffusion-webui-two-shot.git

There are some extensions that break things even when they're disabled. If you're using Latent Couple (two shot), uninstall / delete the folder and and use this fork: https://github.com/ashen-sensored/stable-diffusion-webui-two-shot

I used the Latent Couple extension with the following mask:

I was thinking about this extension.