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Add sdxl controlnet reference community pipeline #9893

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Add sdxl controlnet reference community pipeline #9893

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af35e56
Add reference_attn & reference_adain support for sdxl with other cont…
dimitribarbot Nov 8, 2024
8fa05d7
Update README.md
dimitribarbot Nov 8, 2024
de512c1
Merge branch 'huggingface:main' into add-sdxl-controlnet-reference
dimitribarbot Nov 8, 2024
b0ac075
Merge branch 'main' into add-sdxl-controlnet-reference
dimitribarbot Nov 10, 2024
f53177a
Merge branch 'huggingface:main' into add-sdxl-controlnet-reference
dimitribarbot Nov 15, 2024
53e6ee9
Update README.md by replacing human example with a cat one
dimitribarbot Nov 15, 2024
ba48247
Replace default human example with a cat one
dimitribarbot Nov 15, 2024
8722a36
Use example images from huggingface documentation-images repository
dimitribarbot Nov 16, 2024
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86 changes: 84 additions & 2 deletions examples/community/README.md
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Original file line number Diff line number Diff line change
Expand Up @@ -2659,7 +2659,7 @@ Output Image
`prompt: 1 girl`

`reference_attn=True, reference_adain=True, num_inference_steps=20`
![Output_image](https://github.com/zideliu/diffusers/assets/34944964/743848da-a215-48f9-ae39-b5e2ae49fb13)
![Output_image](https://github.com/user-attachments/assets/4fd5bc0b-8df6-4581-9191-c07faaf10ce8)
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Why are we changing this?

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It seems to me that the url at https://github.com/zideliu/diffusers/assets/34944964/743848da-a215-48f9-ae39-b5e2ae49fb13 cannot be found (404). The diffusers repository fork seems to have been removed by their author. Do you confirm?

Actually, I've updated the stable_diffusion_xl_reference.py file with the latest modifications from StableDiffusionXLPipeline on my side. If you agree, I propose to create a new PR:

  • Upgrading the StableDiffusionXLReferencePipeline to use the latest modifications from StableDiffusionXLPipeline (IP adapters...),
  • Replacing the human example of this updated StableDiffusionXLReferencePipeline by a non-human one and fixing the 404 url at the same time.

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Other PR is #9938.

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Maybe you could open a PR to https://hf.co/datasets/huggingface/documentation-images and host the images there?

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Yes, PR https://huggingface.co/datasets/huggingface/documentation-images/discussions/393 has been created accordingly.


Reference Image
![reference_image](https://github.com/huggingface/diffusers/assets/34944964/449bdab6-e744-4fb2-9620-d4068d9a741b)
Expand All @@ -2681,6 +2681,88 @@ Output Image
`reference_attn=True, reference_adain=True, num_inference_steps=20`
![output_image](https://github.com/huggingface/diffusers/assets/34944964/9b2f1aca-886f-49c3-89ec-d2031c8e3670)

### Stable Diffusion XL ControlNet Reference

This pipeline uses the Reference Control and with ControlNet. Refer to the [Stable Diffusion ControlNet Reference](https://github.com/huggingface/diffusers/blob/main/examples/community/README.md#stable-diffusion-controlnet-reference) and [Stable Diffusion XL Reference](https://github.com/huggingface/diffusers/blob/main/examples/community/README.md#stable-diffusion-xl-reference) sections for more information.

```py
from diffusers import ControlNetModel, AutoencoderKL
from diffusers.schedulers import UniPCMultistepScheduler
from diffusers.utils import load_image
import numpy as np
import torch

import cv2
from PIL import Image

from .stable_diffusion_xl_controlnet_reference import StableDiffusionXLControlNetReferencePipeline

# download an image
canny_image = load_image(
"https://hf.co/datasets/huggingface/documentation-images/resolve/main/diffusers/input_image_vermeer.png"
).resize((1024, 1024))

ref_image = load_image(
"https://hf.co/datasets/hf-internal-testing/diffusers-images/resolve/main/sd_controlnet/hf-logo.png"
)

# initialize the models and pipeline
controlnet_conditioning_scale = 0.5 # recommended for good generalization
controlnet = ControlNetModel.from_pretrained(
"diffusers/controlnet-canny-sdxl-1.0", torch_dtype=torch.float16
)
vae = AutoencoderKL.from_pretrained("madebyollin/sdxl-vae-fp16-fix", torch_dtype=torch.float16)
pipe = StableDiffusionXLControlNetReferencePipeline.from_pretrained(
"stabilityai/stable-diffusion-xl-base-1.0", controlnet=controlnet, vae=vae, torch_dtype=torch.float16
).to("cuda:0")

pipe.scheduler = UniPCMultistepScheduler.from_config(pipe.scheduler.config)

# get canny image
image = np.array(canny_image)
image = cv2.Canny(image, 100, 200)
image = image[:, :, None]
image = np.concatenate([image, image, image], axis=2)
canny_image = Image.fromarray(image)

# generate image
image = pipe(
prompt="1girl",
num_inference_steps=20,
controlnet_conditioning_scale=controlnet_conditioning_scale,
image=canny_image,
ref_image=ref_image,
reference_attn=False,
reference_adain=True,
style_fidelity=1.0,
generator=torch.Generator("cuda").manual_seed(42)
).images[0]
```

Canny ControlNet Image

![canny_image](https://hf.co/datasets/huggingface/documentation-images/resolve/main/diffusers/input_image_vermeer.png)

Reference Image

![ref_image](https://hf.co/datasets/hf-internal-testing/diffusers-images/resolve/main/sd_controlnet/hf-logo.png)

Output Image

`prompt: 1 girl`

`reference_attn=True, reference_adain=True, num_inference_steps=20, style_fidelity=1.0`

![Output_image](https://github.com/user-attachments/assets/b320f081-2421-4b96-9ef1-4685b77179ba)

`reference_attn=False, reference_adain=True, num_inference_steps=20, style_fidelity=1.0`

![Output_image](https://github.com/user-attachments/assets/05ee0816-6c4e-4f4b-81fc-71bb0082be1e)

`reference_attn=True, reference_adain=False, num_inference_steps=20, style_fidelity=1.0`

![Output_image](https://github.com/user-attachments/assets/cfb7426b-9e1b-4401-8e7e-609d67b84f8b)
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Can we avoid using human references in the examples and restrict ourselves to using non-human objects?

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Sure. I've pushed modifications to fix that.


### Stable diffusion fabric pipeline

FABRIC approach applicable to a wide range of popular diffusion models, which exploits
Expand Down Expand Up @@ -4692,4 +4774,4 @@ with torch.no_grad():
```

In the folder examples/pixart there is also a script that can be used to train new models.
Please check the script `train_controlnet_hf_diffusers.sh` on how to start the training.
Please check the script `train_controlnet_hf_diffusers.sh` on how to start the training.
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