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from diffusers import StableDiffusionInpaintPipeline |
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import requests |
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import torch |
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from PIL import Image |
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from io import BytesIO |
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import os |
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from pathlib import Path |
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from huggingface_hub import HfApi |
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api = HfApi() |
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url = "https://raw.githubusercontent.com/CompVis/stable-diffusion/main/assets/stable-samples/img2img/sketch-mountains-input.jpg" |
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def download_image(url): |
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response = requests.get(url) |
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return Image.open(BytesIO(response.content)).convert("RGB") |
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img_url = "https://raw.githubusercontent.com/CompVis/latent-diffusion/main/data/inpainting_examples/overture-creations-5sI6fQgYIuo.png" |
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mask_url = "https://raw.githubusercontent.com/CompVis/latent-diffusion/main/data/inpainting_examples/overture-creations-5sI6fQgYIuo_mask.png" |
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init_image = download_image(img_url).resize((512, 512)) |
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mask_image = download_image(mask_url).resize((512, 512)) |
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path = "runwayml/stable-diffusion-inpainting" |
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run_compile = True |
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pipe = StableDiffusionInpaintPipeline.from_pretrained(path, torch_dtype=torch.float16) |
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pipe = pipe.to("cuda:0") |
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torch.manual_seed(33) |
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prompt = "A cute dog" |
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image = pipe(prompt=prompt, image=init_image, mask_image=mask_image, force_unmasked_unchanged=True).images[0] |
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file_name = "aa" |
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path = os.path.join(Path.home(), "images", f"{file_name}.png") |
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image.save(path) |
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api.upload_file( |
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path_or_fileobj=path, |
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path_in_repo=path.split("/")[-1], |
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repo_id="patrickvonplaten/images", |
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repo_type="dataset", |
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) |
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print(f"https://huggingface.co/datasets/patrickvonplaten/images/blob/main/{file_name}.png") |
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