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Update app.py
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app.py
CHANGED
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@@ -40,9 +40,9 @@ DEFAULT_STYLE_NAME = "Japanese Anime"
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global models_dict
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use_va = True
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models_dict = {
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"RealVision": "SG161222/RealVisXL_V4.0" ,
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# "Unstable": "stablediffusionapi/sdxl-unstable-diffusers-y"
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}
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photomaker_path = hf_hub_download(repo_id="TencentARC/PhotoMaker", filename="photomaker-v1.bin", repo_type="model")
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@@ -436,7 +436,7 @@ use_safetensors= False
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# pipe1.scheduler.set_timesteps(50)
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###
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pipe2 = PhotoMakerStableDiffusionXLPipeline.from_pretrained(
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models_dict["
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pipe2 = pipe2.to("cpu")
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pipe2.load_photomaker_adapter(
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os.path.dirname(photomaker_path),
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@@ -520,7 +520,7 @@ def process_generation(_sd_type,_model_type,_upload_images, _num_steps,style_nam
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num_steps =_num_steps
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use_safe_tensor = True
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if style_name == "(No style)":
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sd_model_path = models_dict["
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if _model_type == "original":
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pipe = StableDiffusionXLPipeline.from_pretrained(sd_model_path, torch_dtype=torch.float16)
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pipe = pipe.to(device)
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@@ -529,7 +529,7 @@ def process_generation(_sd_type,_model_type,_upload_images, _num_steps,style_nam
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# pipe.scheduler.set_timesteps(50)
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set_attention_processor(pipe.unet,id_length_,is_ipadapter = False)
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elif _model_type == "Photomaker":
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if _sd_type != "
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pipe = pipe2.to(device)
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pipe.id_encoder.to(device)
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set_attention_processor(pipe.unet,id_length_,is_ipadapter = False)
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global models_dict
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use_va = True
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models_dict = {
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"Juggernaut": "RunDiffusion/Juggernaut-XL-v8",
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# "RealVision": "SG161222/RealVisXL_V4.0" ,
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"SDXL":"stabilityai/stable-diffusion-xl-base-1.0" ,
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# "Unstable": "stablediffusionapi/sdxl-unstable-diffusers-y"
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}
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photomaker_path = hf_hub_download(repo_id="TencentARC/PhotoMaker", filename="photomaker-v1.bin", repo_type="model")
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# pipe1.scheduler.set_timesteps(50)
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###
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pipe2 = PhotoMakerStableDiffusionXLPipeline.from_pretrained(
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models_dict["Juggernaut"], torch_dtype=torch.float16, use_safetensors=use_safetensors)
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pipe2 = pipe2.to("cpu")
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pipe2.load_photomaker_adapter(
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os.path.dirname(photomaker_path),
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num_steps =_num_steps
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use_safe_tensor = True
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if style_name == "(No style)":
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sd_model_path = models_dict["Juggernaut"]
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if _model_type == "original":
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pipe = StableDiffusionXLPipeline.from_pretrained(sd_model_path, torch_dtype=torch.float16)
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pipe = pipe.to(device)
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# pipe.scheduler.set_timesteps(50)
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set_attention_processor(pipe.unet,id_length_,is_ipadapter = False)
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elif _model_type == "Photomaker":
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if _sd_type != "Juggernaut" and style_name != "(No style)":
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pipe = pipe2.to(device)
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pipe.id_encoder.to(device)
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set_attention_processor(pipe.unet,id_length_,is_ipadapter = False)
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