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from diffusers import DiffusionPipeline, KandinskyPriorPipeline, DDPMScheduler, DDIMScheduler |
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import torch |
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import os |
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from huggingface_hub import HfApi |
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from pathlib import Path |
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api = HfApi() |
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pipe_prior = KandinskyPriorPipeline.from_pretrained("kandinsky-community/kandinsky-2-1-prior", torch_dtype=torch.float16) |
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pipe_prior.to("cuda") |
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prompt = "A alien cheeseburger creature eating itself, claymation, cinematic, moody lighting" |
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negative_prompt = "low quality, bad quality" |
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generator = torch.Generator(device="cuda").manual_seed(10) |
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image_embeds, negative_image_embeds = pipe_prior(prompt, negative_prompt, guidance_scale=1.0, generator=generator).to_tuple() |
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t2i_pipe = DiffusionPipeline.from_pretrained("kandinsky-community/kandinsky-2-1", torch_dtype=torch.float16) |
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t2i_pipe.to("cuda") |
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print(t2i_pipe.scheduler.config) |
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images = t2i_pipe(prompt, num_images_per_prompt=4, image_embeds=image_embeds, negative_image_embeds=negative_image_embeds, negative_prompt=negative_prompt).images |
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for i, image in enumerate(images): |
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path = os.path.join(Path.home(), "images", f"aa_{i}.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/aa_{i}.png") |
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