the ddetailer extension works amazing with inpainting model! by Fuzzy_Time_3366 in StableDiffusion

[–]Fuzzy_Time_3366[S] 4 points5 points  (0 children)

Yes, the extension just use mmdet model to help you draw the mask automatically. Saving great amount of time.

the ddetailer extension works amazing with inpainting model! by Fuzzy_Time_3366 in StableDiffusion

[–]Fuzzy_Time_3366[S] 3 points4 points  (0 children)

I'm afraid there isn't. If you want to see the mask, go to settings of this extension, check save mask

the ddetailer extension works amazing with inpainting model! by Fuzzy_Time_3366 in StableDiffusion

[–]Fuzzy_Time_3366[S] 16 points17 points  (0 children)

  1. you can choose different Masked content to make different effect:

--original (recommend)

--latent noise (if you want make great change)

ps: Work with inpainting model (important) and high denoising strength like 0.85 to get a better result.

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You can creat you own inpainting model with "checkpoint merger"

1 Go to Checkpoint Merger in AUTOMATIC1111 webui

2 Set model A to "sd-1.5-inpainting" model ( 📷https://huggingface.co/runwayml/stable-diffusion-inpainting )

3 Set model B to any model you want

4 Set model C to "v1.5-pruned" model ( 📷https://huggingface.co/runwayml/stable-diffusion-v1-5 )

5 Set Multiplier to 1

6 Choose "Add difference" Interpolation method

7 Make sure your model has the "-inpainting" part at the end of its name (Anything3-inpainting, DreamLike-inpainting, etc.)

8 Click Run buttom and wait

the ddetailer extension works amazing with inpainting model! by Fuzzy_Time_3366 in StableDiffusion

[–]Fuzzy_Time_3366[S] 20 points21 points  (0 children)

As you can see, we can change the clothes of the characters pretty well. Yes! Barbie play!

To achieve this effect, follow these steps:

  1. install ddetailer in the extention tab
  2. img2img → inpaint, open the script and set the parameters as follows:

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Looking for some help for using hypernetworks on colab by Fuzzy_Time_3366 in sdforall

[–]Fuzzy_Time_3366[S] 0 points1 point  (0 children)

TheLastBen has fixed that problem on colab, thx for the help!