Radiata
sd-webui-controlnet
Radiata | sd-webui-controlnet | |
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8 | 247 | |
981 | 16,056 | |
- | - | |
8.1 | 9.6 | |
8 months ago | 2 days ago | |
Python | Python | |
Apache License 2.0 | GNU General Public License v3.0 only |
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Radiata
- 🌠🌟Radiata TensorRT WebUI ⚡🏎️💨
- 🌠🌟Radiata Stable Diffusion with TensorRT WebUI🏎️💨
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Automatic1111 is still active
I didn't and don't! Are you saying that can be applied in the a1111 gui? The things I've found by googling it seem to be about a separate UI which uses this optimisation to radically speed up generation.
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I made a tutorial on how to speed up SD on windows
wow You might be into something here I am going to try this today. Have you tried Lsmith is MIA for 1 month now but is base on TensorRT and it was supper fast when I ran it you need to convert the models to tensorRT format but once they run they are blazingly fast https://github.com/ddPn08/Lsmith
- Stable Diffusion as a game renderer test
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WIP - TensorRT accelerated stable diffusion img2img from mobile camera over webrtc + whisper speech to text. Interdimensional cable is here! Code: https://github.com/venetanji/videosd
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.
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TensorRT txt2img GUI: 20 to 30% speed boost
I just found this amazing GUI that uses the accelerated models of SD to get a speed boost of up to 30%. https://github.com/ddPn08/Lsmith
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What is the fastest stable diffusion text to image implementation?
just released https://github.com/ddPn08/Lsmith
sd-webui-controlnet
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OpenPose ControlNet: A Beginner's Guide
A crucial step for achieving stable diffusion controlnet settings is the installation of the controlnet extension in Google Colab. Whether on a Windows PC or Mac, installing controlnet is vital for stable diffusion of human pose details. Additionally, updating the controlnet extension is necessary to maintain stability and achieve the desired results in OpenPose model. To install the v1.1 controlnet extension, go to the “extensions” tab and install it from this URL: https://github.com/Mikubill/sd-webui-controlnet. If you already have v1 controlnets installed, delete the folder from stable-diffusion-webui/extensions/. Install the v1.
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StyleAligned node for ComfyUI
1.1.420 Image-wise ControlNet and StyleAlign
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PATCHFUSION is really impressive. High resolution depth maps in 16bit. I've been waiting for this. https://github.com/zhyever/PatchFusion
I opened a request thread on ControlNet GitHub you can give a support : https://github.com/Mikubill/sd-webui-controlnet/issues/2319
- Going to lose my mind at this point with this problem
- Samples of style-aligned
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Is it possible to outpaint with SD or SDXL as easy as with photoshop? (no prompts)
It has been possible for 7 months now
- Reference Only Broken (Can someone with a working Reference Only CN upload there extension folder)
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Web app prototype to create controlnet segmentation maps for Stable Diffusion
I sometimes use a very similar technique in Cinema4d (here is a link to a c4d file with preset materials referencing proper colors for Semantic Segmentation if any other c4d user wants to try it), but yours is a much more accessible solution as it's free and it's accessible online.
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Dalle-3 Examples
There are models available that give you more control - in some senses, at least.
For example, you can use Stable Diffusion with 'ControlNet' [1] where for example, you can input an 'openpose' to choose the pose of people in the scene.
There's also a 'Regional Prompter' [2] which lets you use different prompts for different areas of the image, giving you some control over the composition.
You can also use 'inpainting' to regenerate select parts of your image if, for example, you don't like the shape of the clouds.
Of course this stuff isn't perfect - for example, you'll get hands with the wrong number of fingers sometimes, no matter what you specify :)
[1] https://github.com/Mikubill/sd-webui-controlnet
- ControlNet SDXL for Automatic1111-WebUI official release: sd-webui-controlnet 1.1.400
What are some alternatives?
voltaML-fast-stable-diffusion - Beautiful and Easy to use Stable Diffusion WebUI
ComfyUI - The most powerful and modular stable diffusion GUI, api and backend with a graph/nodes interface.
was-node-suite-comfyui - An extensive node suite for ComfyUI with over 190 new nodes
openpose-editor - Openpose Editor for AUTOMATIC1111's stable-diffusion-webui
a1111-batch-interrogate - Example batch scripts using the A1111 SD Webui API [Moved to: https://github.com/d3x-at/a1111-api-examples]
T2I-Adapter - T2I-Adapter
stable-diffusion-webui - Stable Diffusion web UI
ControlNet - Let us control diffusion models!
stable-diffusion-webui-rocm - A stable diffusion webui configuration for AMD ROCm
stable-diffusion-webui-colab - stable diffusion webui colab
a1111-api-batch-examples - Example batch scripts using the A1111 SD Webui API [Moved to: https://github.com/d3x-at/a1111-api-examples]
stable-diffusion-webui - Stable Diffusion web UI