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import torch |
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import kiui |
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import numpy as np |
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import argparse |
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from pipeline import MVDreamPipeline |
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pipe = MVDreamPipeline.from_pretrained( |
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'ashawkey/mvdream-sd2.1-diffusers', |
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torch_dtype=torch.float16, |
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trust_remote_code=True, |
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) |
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pipe = pipe.to("cuda") |
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parser = argparse.ArgumentParser(description="MVDream") |
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parser.add_argument("prompt", type=str, default="a cute owl 3d model") |
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args = parser.parse_args() |
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for i in range(5): |
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image = pipe(args.prompt, guidance_scale=5, num_inference_steps=30, elevation=0) |
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grid = np.concatenate( |
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[ |
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np.concatenate([image[0], image[2]], axis=0), |
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np.concatenate([image[1], image[3]], axis=0), |
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], |
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axis=1, |
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) |
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kiui.write_image(f'test_mvdream_{i}.jpg', grid) |
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