Update multi_controlnet/README.md
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multi_controlnet/README.md
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## Generate Example:
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- Model: [andite/anything-v4.0](https://hf.co/andite/anything-v4.0)
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- Prompt: `best quality, extremely detailed, cowboy shot`
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- Negative_prompt: `cowboy, monochrome, lowres, bad anatomy, worst quality, low quality`
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- Seed: 8 (cherry-picked)
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|Control Image1|Control Image2|Generated|
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|---|---|---|
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|<img width="200" src="https://huggingface.co/takuma104/controlnet_dev/resolve/main/multi_controlnet/pac_pose_512x512.png">|<img width="200" src="https://huggingface.co/takuma104/controlnet_dev/resolve/main/multi_controlnet/pac_canny_512x512.png">|<img width="200" src="https://huggingface.co/takuma104/controlnet_dev/resolve/main/multi_controlnet/mc_pose_and_canny_result_8.png">|
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|<img width="200" src="https://huggingface.co/takuma104/controlnet_dev/resolve/main/multi_controlnet/pac_pose_512x512.png">|(none)|<img width="200" src="https://huggingface.co/takuma104/controlnet_dev/resolve/main/multi_controlnet/mc_pose_only_result_8.png">|
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|<img width="200" src="https://huggingface.co/takuma104/controlnet_dev/resolve/main/multi_controlnet/pac_canny_512x512.png">|(none)|<img width="200" src="https://huggingface.co/takuma104/controlnet_dev/resolve/main/multi_controlnet/mc_canny_only_result_8.png">|
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- Pose & Canny Control Image Generated by [*Character bones that look like Openpose for blender _ Ver_4.7 Depth+Canny*](https://toyxyz.gumroad.com/l/ciojz)
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## Code
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Using deveploment version [`StableDiffusionMultiControlNetPipeline`](https://github.com/takuma104/diffusers/tree/multi_controlnet)
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```py
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from stable_diffusion_multi_controlnet import StableDiffusionMultiControlNetPipeline
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from stable_diffusion_multi_controlnet import ControlNetProcessor
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from diffusers import ControlNetModel
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import torch
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from diffusers.utils import load_image
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pipe = StableDiffusionMultiControlNetPipeline.from_pretrained(
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"andite/anything-v4.0", safety_checker=None, torch_dtype=torch.float16
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).to("cuda")
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pipe.scheduler = EulerDiscreteScheduler.from_config("andite/anything-v4.0", subfolder="scheduler")
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pipe.enable_xformers_memory_efficient_attention()
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controlnet_canny = ControlNetModel.from_pretrained(
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"lllyasviel/sd-controlnet-canny", torch_dtype=torch.float16
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).to("cuda")
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controlnet_pose = ControlNetModel.from_pretrained(
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"lllyasviel/sd-controlnet-openpose", torch_dtype=torch.float16
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).to("cuda")
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canny_image = load_image('https://huggingface.co/takuma104/controlnet_dev/resolve/main/multi_controlnet/pac_canny_512x512.png').convert('RGB')
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pose_image = load_image('https://huggingface.co/takuma104/controlnet_dev/resolve/main/multi_controlnet/pac_pose_512x512.png').convert('RGB')
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prompt = "best quality, extremely detailed, cowboy shot"
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negative_prompt = "cowboy, monochrome, lowres, bad anatomy, worst quality, low quality"
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seed = 8
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image = pipe(
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prompt=prompt,
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negative_prompt=negative_prompt,
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processors=[
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ControlNetProcessor(controlnet_pose, pose_image),
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# ControlNetProcessor(controlnet_canny, canny_image),
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],
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generator=torch.Generator(device="cpu").manual_seed(seed),
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num_inference_steps=30,
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width=512,
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height=512,
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).images[0]
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image.save(f"./mc_pose_only_result_{seed}.png")
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image = pipe(
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prompt=prompt,
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negative_prompt=negative_prompt,
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processors=[
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# ControlNetProcessor(controlnet_pose, pose_image),
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ControlNetProcessor(controlnet_canny, canny_image),
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],
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generator=torch.Generator(device="cpu").manual_seed(seed),
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num_inference_steps=30,
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width=512,
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height=512,
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).images[0]
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image.save(f"./mc_canny_only_result_{seed}.png")
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image = pipe(
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prompt=prompt,
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negative_prompt=negative_prompt,
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processors=[
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ControlNetProcessor(controlnet_pose, pose_image),
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ControlNetProcessor(controlnet_canny, canny_image),
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],
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generator=torch.Generator(device="cpu").manual_seed(seed),
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num_inference_steps=30,
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width=512,
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height=512,
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).images[0]
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image.save(f"./mc_pose_and_canny_result_{seed}.png")
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```
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