multimodalart HF staff commited on
Commit
71c1a49
1 Parent(s): a7ae1ff

Update app.py

Browse files
Files changed (1) hide show
  1. app.py +22 -3
app.py CHANGED
@@ -110,21 +110,40 @@ face_adapter = f'/data/checkpoints/ip-adapter.bin'
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  controlnet_path = f'/data/checkpoints/ControlNetModel'
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  # load IdentityNet
 
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  identitynet = ControlNetModel.from_pretrained(controlnet_path, torch_dtype=torch.float16)
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  zoedepthnet = ControlNetModel.from_pretrained("diffusers/controlnet-zoe-depth-sdxl-1.0",torch_dtype=torch.float16)
 
 
 
 
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  vae = AutoencoderKL.from_pretrained("madebyollin/sdxl-vae-fp16-fix", torch_dtype=torch.float16)
 
 
 
 
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  pipe = StableDiffusionXLInstantIDImg2ImgPipeline.from_pretrained("rubbrband/albedobaseXL_v21",
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  vae=vae,
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  controlnet=[identitynet, zoedepthnet],
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  torch_dtype=torch.float16)
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-
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- compel = Compel(tokenizer=[pipe.tokenizer, pipe.tokenizer_2] , text_encoder=[pipe.text_encoder, pipe.text_encoder_2], returned_embeddings_type=ReturnedEmbeddingsType.PENULTIMATE_HIDDEN_STATES_NON_NORMALIZED, requires_pooled=[False, True])
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  pipe.scheduler = DPMSolverMultistepScheduler.from_config(pipe.scheduler.config, use_karras_sigmas=True)
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  pipe.load_ip_adapter_instantid(face_adapter)
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  pipe.set_ip_adapter_scale(0.8)
 
 
 
 
 
 
 
 
 
 
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  zoe = ZoeDetector.from_pretrained("lllyasviel/Annotators")
 
 
 
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  zoe.to(device)
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-
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  pipe.to(device)
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  last_lora = ""
 
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  controlnet_path = f'/data/checkpoints/ControlNetModel'
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  # load IdentityNet
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+ st = time.time()
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  identitynet = ControlNetModel.from_pretrained(controlnet_path, torch_dtype=torch.float16)
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  zoedepthnet = ControlNetModel.from_pretrained("diffusers/controlnet-zoe-depth-sdxl-1.0",torch_dtype=torch.float16)
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+ et = time.time()
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+ elapsed_time = et - st
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+ print('Loading ControlNet took: ', elapsed_time, 'seconds')
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+ st = time.time()
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  vae = AutoencoderKL.from_pretrained("madebyollin/sdxl-vae-fp16-fix", torch_dtype=torch.float16)
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+ et = time.time()
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+ elapsed_time = et - st
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+ print('Loading VAE took: ', elapsed_time, 'seconds')
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+ st = time.time()
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  pipe = StableDiffusionXLInstantIDImg2ImgPipeline.from_pretrained("rubbrband/albedobaseXL_v21",
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  vae=vae,
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  controlnet=[identitynet, zoedepthnet],
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  torch_dtype=torch.float16)
 
 
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  pipe.scheduler = DPMSolverMultistepScheduler.from_config(pipe.scheduler.config, use_karras_sigmas=True)
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  pipe.load_ip_adapter_instantid(face_adapter)
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  pipe.set_ip_adapter_scale(0.8)
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+ et = time.time()
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+ elapsed_time = et - st
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+ print('Loading pipeline took: ', elapsed_time, 'seconds')
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+ st = time.time()
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+ compel = Compel(tokenizer=[pipe.tokenizer, pipe.tokenizer_2] , text_encoder=[pipe.text_encoder, pipe.text_encoder_2], returned_embeddings_type=ReturnedEmbeddingsType.PENULTIMATE_HIDDEN_STATES_NON_NORMALIZED, requires_pooled=[False, True])
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+ et = time.time()
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+ elapsed_time = et - st
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+ print('Loading Compel took: ', elapsed_time, 'seconds')
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+
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+ st = time.time()
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  zoe = ZoeDetector.from_pretrained("lllyasviel/Annotators")
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+ et = time.time()
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+ elapsed_time = et - st
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+ print('Loading Zoe took: ', elapsed_time, 'seconds')
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  zoe.to(device)
 
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  pipe.to(device)
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  last_lora = ""