clipseg VS sd-webui-controlnet

Following the comments to this old post, I tried to use in-painting with manual mask selection. I didn't get beautiful results but I'm sure with some tweaking, I could make it better. The main problem I had was having to manually select the area where I wanted to place the logo and trying to resize my logo mask to the fit the segment. I tried some automatic segmentation tools (Clipseg and Segment Anything). I couldn't tell the segmentation models to find a good area to for logo placement (i.e. some small flat surface). Given the complexity of what I was dealing with, I think there could be a better way (XY problem).

The addon utilizes clipseg for region masking, which was trained on "an extended version of the PhraseCut dataset" (many thousands of images.)

You'll also need to make sure to update your clipseg repo. The script won't do this for you. Namely you just need to update this models/clipseg.py file to ensure your clipseg has support for the new model.

For localisation at search time I ended up using OWL-ViT. This worked really well. I did not try Detic or CLIPseg but would be interested to hear if anyone else has tried these?

clipseg is an image segmentation method used to find a mask for an image from a prompt. I implemented it as an executor for dalle-flow and added it to my bot yasd-discord-bot.

Automated Replacement (txt2mask) by clipseg

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.

1.1.420 Image-wise ControlNet and StyleAlign

I opened a request thread on ControlNet GitHub you can give a support : https://github.com/Mikubill/sd-webui-controlnet/issues/2319

It has been possible for 7 months now

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.

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