Image-to-Image
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Update README.md

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  1. README.md +5 -7
README.md CHANGED
@@ -52,10 +52,8 @@ from schedulers.lcm_single_step_scheduler import LCMSingleStepScheduler
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  from module.ip_adapter.utils import load_adapter_to_pipe
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  from pipelines.sdxl_instantir import InstantIRPipeline
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- # prepare models under ./checkpoints
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- dcp_adapter = f'./models/adapter.pt'
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- previewer_lora_path = f'./models'
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- instantir_path = f'./models/aggregator.pt'
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  # load pretrained models
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  pipe = InstantIRPipeline.from_pretrained('stabilityai/stable-diffusion-xl-base-1.0', torch_dtype=torch.float16)
@@ -63,17 +61,17 @@ pipe = InstantIRPipeline.from_pretrained('stabilityai/stable-diffusion-xl-base-1
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  # load adapter
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  load_adapter_to_pipe(
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  pipe,
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- dcp_adapter,
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  image_encoder_or_path = 'facebook/dinov2-large',
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  )
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  # load previewer lora
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- pipe.prepare_previewers(previewer_lora_path)
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  pipe.scheduler = DDPMScheduler.from_pretrained('stabilityai/stable-diffusion-xl-base-1.0', subfolder="scheduler")
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  lcm_scheduler = LCMSingleStepScheduler.from_config(pipe.scheduler.config)
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  # load aggregator weights
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- pretrained_state_dict = torch.load(instantir_path)
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  pipe.aggregator.load_state_dict(pretrained_state_dict)
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  # send to GPU and fp16
 
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  from module.ip_adapter.utils import load_adapter_to_pipe
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  from pipelines.sdxl_instantir import InstantIRPipeline
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+ # prepare models under ./models
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+ instantir_path = f'./models'
 
 
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  # load pretrained models
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  pipe = InstantIRPipeline.from_pretrained('stabilityai/stable-diffusion-xl-base-1.0', torch_dtype=torch.float16)
 
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  # load adapter
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  load_adapter_to_pipe(
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  pipe,
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+ f"{instantir_path}/adapter.pt",
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  image_encoder_or_path = 'facebook/dinov2-large',
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  )
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  # load previewer lora
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+ pipe.prepare_previewers(instantir_path)
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  pipe.scheduler = DDPMScheduler.from_pretrained('stabilityai/stable-diffusion-xl-base-1.0', subfolder="scheduler")
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  lcm_scheduler = LCMSingleStepScheduler.from_config(pipe.scheduler.config)
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  # load aggregator weights
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+ pretrained_state_dict = torch.load(f"{instantir_path}/aggregator.pt")
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  pipe.aggregator.load_state_dict(pretrained_state_dict)
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  # send to GPU and fp16