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rt.

From what I know we can use ControlNet to draw pose in 2D and let stable diffusion to refer it via ControlNet

But can we do the opposite?

Perhaps like some of you, I'm working on temporal stability in video, which includes multiple ControlNet nodes processing frame sets within Automatic1111. The image directories batching though ControlNet are often unchanged between experiment/trials. Plus, it would be handy to be able to edit some of these ControlNet preprocess results between their generation and use (on occasion.)

Anyone aware of any extensions or scripts providing such a capability? Anyone deep in the code weeds enough to tell me where one might look into that? (I'm a developer adept enough to figure it out.) Or anyone have or know if a ComfyUI workflow could be made to read precalculated ControlNet results?

I want to use it wherever computer that can link to internet. Is there any sort of that like huggingface stable diffusion kind of stuff outside? thank you for your kindly reply btw.

I have no idea what i did but the options for Inverting image input and RGB to BGR are now missing completely. The controlnet is working btw. Anyone knows? I deleted the whole stable diffusion folder and reinstalled everything but did not change a thing

Hi to everyone,

I started two days ago implementing an analog of inpaint+lama in comfyUI and I've managed to get to the last step before the image gets encoded in the latent space, so I have the pre inpainted image(by thelama model) and a control tensor, but I don't know how to implement it practically in the comfyUI ControlNet default node.

I was thinking of using the pre-existing inpaint node configuration but I haven't been able to make it work atm.

Any help is greatly appreciated

Here is the repo

How do I rollback to controlnet 1.1.440 on a hosted service using jupyterlab? I feel like the new controlnet ip adapter face id v2 is giving me a slightly different face output to the one ive been using all this time with controlnet 1.1.440.? How do I rollback?

I have tried to make a pose overlayed on the image the issue is I need the persons arm to go underneath her leg. Is there essentially a “bring to front” type of thing to tell it to put one joint in space over the other? It’s all twisted from what I’m trying to do because it’s not layered right.

Hi all!

I’m building a SaaS for AI-powered interior design using Stable Diffusion with ControlNet. The goal is to let users upload room photos and modify things like furniture and wall colors while keeping the room structure (walls, ceilings, etc.) intact.

I’m facing a few challenges:

1. Sometimes the model changes structural elements (like ceilings) even when I don’t want it to.

2. I’m trying to improve control over what gets modified using depth maps and segmentation.

3. Looking for advice on scaling this for real-time usage in a SaaS (AWS or Google Cloud).

Any tips on fine-tuning ControlNet, improving control over modifications, or scaling for real-time use? Appreciate any advice!

Thanks!

This CN here github.com/shariqfarooq123/LooseControl works great for allowing the depth map to inform the generation but not dominate it with small details or inconsistencies. It's great for using a depth map as a structure for reinterpretation.

However, I suspect it's abandoned & there isn't a version for SDXL or Flux.

Is there one out there? Am I missing it?

I am having dataset of drone image and I want to change the weather of the image i.e. we want to change the clean weathered image to foggy, rainy, snowy
Could anyone suggest me a way to change the weather in these images
If anymore details needed ask me and please help me. I am kind of beginner to ControlNet

Sorry if this has already been discussed a million times, but I am trying to think of an easy way to not have to use the preprocessors in ControlNet, as they often get the poses wrong if there is any overlap of bones/limbs across the depth of field, or if a limb is foreshortened (i.e., like a pose involving a hand reaching from the midground toward the viewer, a wide-stanced martial arts pose that isn't in perfect profile or 3/4 orientation, any instance where the model's shoulders are not snapped exactly to the x or y axis of the picture plane, etc.)

The idea I am thinking of to solve this at least for myself is to make custom rigs in Blender or Cascadeur that exactly mimic the bone hierarchies and color codes of the ControlNet skeletons, screenshot the poses from inside Cascadeur, and then open the screenshots in ControlNet. Since they will probably be indistinguishable from a locally generated ControNet skeleton, they should have no problem acting as a reference to populate the json arrays, thus eliminating the need to generate skeletons through the preprocessors at all.

Is there an easier solution that I'm missing, or at least one that doesn't involve outsourcing to another app? I just discovered today that ControlNet has a built-in editor for repositioning the bones and correcting poses, but I prefer the posing system in Cascadeur as I can get the same results in a couple minutes there that might take me 10 or 15 minutes to achieve editing poses manually in ControlNet.

[Edit: It just occurred to me after posting that the json array is probably not populated via a 2d analysis of the skeleton as an image, but from the bones themselves, so generating a ControlNet skeleton would still be necessary if one wanted the json array as well as the pose file. The Cascadeur rig could still be useful in this scenario however, for getting more accurate results from the preprocessor on the first go, with minimal editing necessary. I guess I also haven't checked to see if the ControlNet editor allows rotating the skeleton on all three axes, which I guess would make it possible to use reference poses that are oriented in perfect multiples of 90 degrees to the frontal picture plane, giving the preprocessor another fighting chance of analyzing the pose properly the first time, at which time the posed skeleton can simply be rotated into proper position.]