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def main(): |
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from diffusers.utils import load_image |
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pipe = StableDiffusionMultiControlNetPipeline.from_pretrained( |
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"runwayml/stable-diffusion-v1-5", safety_checker=None, torch_dtype=torch.float16 |
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).to("cuda") |
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pipe.enable_xformers_memory_efficient_attention() |
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controlnet_canny = ControlNetModel.from_pretrained("lllyasviel/sd-controlnet-canny", torch_dtype=torch.float16).to( |
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"cuda" |
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) |
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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_left = load_image("https://huggingface.co/takuma104/controlnet_dev/resolve/main/vermeer_left.png") |
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canny_right = load_image("https://huggingface.co/takuma104/controlnet_dev/resolve/main/vermeer_right.png") |
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pose_right = load_image("https://huggingface.co/takuma104/controlnet_dev/resolve/main/pose_right.png") |
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image = pipe( |
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prompt="best quality, extremely detailed", |
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negative_prompt="monochrome, lowres, bad anatomy, worst quality, low quality", |
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processors=[ |
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ControlNetProcessor(controlnet_canny, canny_left), |
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ControlNetProcessor(controlnet_canny, canny_right), |
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], |
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generator=torch.Generator(device="cpu").manual_seed(0), |
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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("/tmp/canny_left_right.png") |
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image = pipe( |
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prompt="best quality, extremely detailed", |
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negative_prompt="monochrome, lowres, bad anatomy, worst quality, low quality", |
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processors=[ |
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ControlNetProcessor(controlnet_canny, canny_left), |
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ControlNetProcessor(controlnet_pose, pose_right), |
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], |
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generator=torch.Generator(device="cpu").manual_seed(0), |
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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("/tmp/canny_left_pose_right.png") |
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if __name__ == "__main__": |
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main() |
