T2I-Adapter
T2I-Adapter (by TencentARC)
ControlNet-v1-1-nightly
Nightly release of ControlNet 1.1 (by lllyasviel)
| T2I-Adapter | ControlNet-v1-1-nightly | |
|---|---|---|
| 25 | 31 | |
| 3,158 | 4,314 | |
| 2.9% | - | |
| 7.9 | 8.4 | |
| 6 months ago | 6 months ago | |
| Python | Python | |
| Apache License 2.0 | - |
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
T2I-Adapter
Posts with mentions or reviews of T2I-Adapter.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2023-08-03.
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Help me understand ControlNet vs T2I-adapter vs CoAdapter
I've found some documentation here https://github.com/TencentARC/T2I-Adapter/blob/SD/docs/coadapter.md
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Color-Diffusion: using diffusion models to colorize black and white images
Yeah, if you have a high res image, you can get color info at super low-res and then regenerate the colors at high res with another model. (though this isn't an efficient approach at all)
https://github.com/TencentARC/T2I-Adapter
i've also seen a controlnet do this.
- Uni-ControlNet: All-in-One Control to Text-to-Image Diffusion Models
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Reflected Diffusion Models
https://github.com/TencentARC/T2I-Adapter
It works with the Mikubill ControlNet plugin for A1111.
- Is it possible to replace objects with an already segmented image by ControlNet?
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ControlNet v1.1 has been released
These are from Tencent: https://github.com/TencentARC/T2I-Adapter
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Can someone explain some of these newer controlnet models and preprocessors? Clipvision? Color? Pidinet? Binary?
I think they're for T2I-adapter models, which can be downloaded here.
- T2I-Adapter: Text-to-Image Models with Unprecedented Control
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How do I combine two images using AUTOMATIC1111?
Apart from Controlnet, T2I Adapter works quite well for this. https://github.com/TencentARC/T2I-Adapter
- T2IAdapter creates Coadapter(inspired by Composer)
ControlNet-v1-1-nightly
Posts with mentions or reviews of ControlNet-v1-1-nightly.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2023-10-27.
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Making a ControlNet inpaint for sdxl
1- https://github.com/lllyasviel/ControlNet-v1-1-nightly/issues/89
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AI Yearbook Photos Workflow with Stable Diffusion 1.5 Automatic1111
Install ControlNet and download the models you want to use (canny/depth/openpose should be enough for this): https://github.com/lllyasviel/ControlNet-v1-1-nightly
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can you downgrade Controlnet?
you can find the previous version on their git and if it's a previous version of v1.1 then you probably have to search for the right branch on the new git version and download that
- Could you help me with this problem?
- Controlnet v1.1 Lineart
- Request for current ControlNet information
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AI conceptual massing iterations within a context image with input control sketch
Stable Diffusion: https://huggingface.co/runwayml/stable-diffusion-v1-5 with ControlNet extension: https://github.com/lllyasviel/ControlNet-v1-1-nightly running on Automatic1111 web UI: https://github.com/AUTOMATIC1111/stable-diffusion-webui
- Inpaint Anything (uses "Segment Anything") - Cool A1111 Extension not (yet) on the in App list
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Architectural design using Stable Diffusion and ControlNet
Sure thing, after testing midjourney a bit I found out that yhe quality of images produced is best but you have zero control on over what is produced. The big breakthrough here is ControlNet which is a Stable Diffusion extension that makes you control the initial noise based on image inputs (or at least this is what i understand) more on it here: https://github.com/lllyasviel/ControlNet-v1-1-nightly
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Setting Removed from ControlNET - "Skip img2img processing when using img2img initial image" - why?
https://github.com/lllyasviel/ControlNet-v1-1-nightly/issues/61 it seems get removed as duplicated.
What are some alternatives?
When comparing T2I-Adapter and ControlNet-v1-1-nightly you can also consider the following projects:
sd-webui-controlnet - WebUI extension for ControlNet
ComfyUI - The most powerful and modular stable diffusion GUI, api and backend with a graph/nodes interface.
ControlNet - Let us control diffusion models!
sd-webui-reactor - Fast and Simple Face Swap Extension for StableDiffusion WebUI (A1111 SD WebUI, SD WebUI Forge, SD.Next, Cagliostro)
style2paints - sketch + style = paints :art: (TOG2018/SIGGRAPH2018ASIA)
ControlNet-v1-1-nightly-colab - controlnet v1.1 colab
Color-diffusion - A diffusion model to colorize black and white images
Latent-Paint-Mesh - NVDiffrast based implementation of Latent-Paint
sd-webui-inpaint-anything - Inpaint Anything extension performs stable diffusion inpainting on a browser UI using masks from Segment Anything.
T2I-Adapter vs sd-webui-controlnet
ControlNet-v1-1-nightly vs sd-webui-controlnet
T2I-Adapter vs ComfyUI
ControlNet-v1-1-nightly vs ControlNet
T2I-Adapter vs ControlNet
ControlNet-v1-1-nightly vs sd-webui-reactor
T2I-Adapter vs style2paints
ControlNet-v1-1-nightly vs ControlNet-v1-1-nightly-colab
T2I-Adapter vs Color-diffusion
ControlNet-v1-1-nightly vs style2paints
T2I-Adapter vs Latent-Paint-Mesh
ControlNet-v1-1-nightly vs sd-webui-inpaint-anything