gwm_outpainting版本v2.0-brushnet (ID: 673415)

Update (07/29/2024)

We finetune brushnet with our dataset. Now, new version can transfer inpainting ability to arbitrary SDXL models. This version is cityscape-friendly!!!

Have fun and make sure to add a ❤️ to receive future updates.

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● This model is finetuned based on the diffusers/stable-diffusion-xl-1.0-inpainting-0.1 and can outpaint the pictures by using a mask.
● The uploaded part only has the UNet.
● The showcase is presented in the order output_result-raw_image.

Usage:

1. The input is a masked image(expanded from source image and fill the expanded part with the value you like) and its mask(set the expanded part to 255 and the source image part to 0).
2. Use the diffusers pipeline(eg. StableDiffusionXLInpaintPipeline) to automatically match the 9 input channels of the outpainting UNet.
3. Set the strength parameter to 1.0 (very important!!!).
Recommended:
1. Recommend diffusers pipeline. Automatic1111 does not support inpaint-XL model yet.
2. Sampling scheduler: DPM++ 2M SDE Karras, steps: 30, cfg: 3.
3. In order to have a better experience, the expansion ratio of the image height should not exceed 1.3, and the expansion ratio of the image width should not exceed 1.5.
4. Use lower cfg to reduce the impact of incorrect prompt.
5. More friendly for scenery image input.
Attention:

1. Higher expansion ratio than recommended may generate repetitive parts. For better experience, you can first expand single side and a more suitable prompt or use progressive generation method.
2. Prompt is not necessary. If use prompt, preferably describe the contents of the extended part you want rather than the objects already in the image(eg. Cars) to avoid repetitive objects, especially in the case of high expansion ratio.
3. We're working on the next version.

Update:

(01/26/2024): upload an instruction for infering : https://civitai.com/articles/3835

Have fun and make sure to add a ❤️ to receive future updates.

(For model showcase, we use some real images as input and indicate the source of the image as much as possible in the comment. For infringement, please contact us deleted.)

描述:

We finetune brushnet with our dataset. Now, new version can transfer inpainting ability to arbitrary SDXL models.

Have fun and make sure to add a ❤️ to receive future updates.

训练词语: