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from diffusers import StableDiffusionControlNetInpaintPipeline, ControlNetModel, DDIMScheduler |
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from diffusers.utils import load_image |
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import numpy as np |
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import torch |
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from dw_pose.main import dwpose |
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from PIL import Image |
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init_image = load_image( |
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"https://huggingface.co/datasets/diffusers/test-arrays/resolve/main/stable_diffusion_inpaint/boy.png" |
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) |
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init_image = Image.open("./girl.png") |
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generator = torch.Generator(device="cpu").manual_seed(1) |
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mask_image = load_image( |
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"https://huggingface.co/datasets/diffusers/test-arrays/resolve/main/stable_diffusion_inpaint/boy_mask.png" |
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) |
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mask_image = Image.open("./girlmask.png") |
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print("doing dwpose") |
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control_image = dwpose(init_image, 512) |
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print("done dwpose") |
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control_image.save("thecontrolfucking.png") |
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print("loading openpose") |
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controlnet = ControlNetModel.from_pretrained( |
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"lllyasviel/control_v11p_sd15_openpose", torch_dtype=torch.float16 |
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) |
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pipe = StableDiffusionControlNetInpaintPipeline.from_pretrained( |
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"runwayml/stable-diffusion-v1-5", controlnet=controlnet, torch_dtype=torch.float16 |
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) |
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print("loaded openpsoe") |
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pipe.scheduler = DDIMScheduler.from_config(pipe.scheduler.config) |
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pipe.enable_model_cpu_offload() |
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pipe.safety_checker = None |
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init_image_width, init_image_height = init_image.size |
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from main import resize |
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new_size = resize( |
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init_image_width, init_image_height, 1500) |
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init_image_resized = init_image.resize((int(new_size['width']), int(new_size['height']))) |
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mask_image_resized = mask_image.resize((int(new_size['width']), int(new_size['height']))) |
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control_image_resized = control_image.resize((int(new_size['width']), int(new_size['height']))) |
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print("ccreating image") |
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image = pipe( |
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"a fucking sexy girl naked", |
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num_inference_steps=20, |
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generator=generator, |
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guidance_scale=6.0, |
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eta=1.0, |
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image=init_image_resized, |
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mask_image=mask_image_resized, |
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control_image=control_image_resized, |
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).images[0].save("aha.png") |
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print("created image and saved") |
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