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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_mvdream import MVDreamPipeline | 
					
					
						
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						pipe = MVDreamPipeline.from_pretrained( | 
					
					
						
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						    "ashawkey/imagedream-ipmv-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="ImageDream") | 
					
					
						
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						parser.add_argument("image", type=str, default='data/anya_rgba.png') | 
					
					
						
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						parser.add_argument("--prompt", type=str, default="") | 
					
					
						
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						args = parser.parse_args() | 
					
					
						
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						for i in range(5): | 
					
					
						
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						    input_image = kiui.read_image(args.image, mode='float') | 
					
					
						
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						    image = pipe(args.prompt, input_image, 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_imagedream_{i}.jpg', grid) | 
					
					
						
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