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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 time |
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from diffusers import DiffusionPipeline |
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pipe = DiffusionPipeline.from_pretrained("/home/patrick_huggingface_co/stable-diffusion-2-1-unclip-i2i-l", torch_dtype=torch.float16) |
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pipe.to("cuda") |
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url = "https://huggingface.co/datasets/hf-internal-testing/diffusers-images/resolve/main/stable_unclip/image%20(13).png" |
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response = requests.get(url) |
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init_image = Image.open(BytesIO(response.content)).convert("RGB") |
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images = pipe(4 * [init_image]).images |
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for i in range(len(images)): |
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images[i].save(f"fantasy_landscape_{i}.png") |
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