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Update app.py
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app.py
CHANGED
@@ -7,6 +7,8 @@ is_shared_ui = True if "fffiloni/sdxl-control-loras" in os.environ['SPACE_ID'] e
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hf_token = os.environ.get("HF_TOKEN")
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login(token=hf_token)
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from diffusers import ControlNetModel, StableDiffusionXLControlNetPipeline, AutoencoderKL
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from diffusers.utils import load_image
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from PIL import Image
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@@ -30,7 +32,7 @@ pipe = StableDiffusionXLControlNetPipeline.from_pretrained(
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use_safetensors=True
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)
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pipe.to(
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@@ -60,7 +62,7 @@ def resize_image(input_path, output_path, target_height):
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def infer(use_custom_model, model_name, custom_lora_weight, image_in, prompt, negative_prompt, preprocessor, controlnet_conditioning_scale, guidance_scale, inf_steps, seed, progress=gr.Progress(track_tqdm=True)):
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prompt = prompt
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negative_prompt = negative_prompt
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generator = torch.Generator(device=
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if image_in == None:
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raise gr.Error("You forgot to upload a source image.")
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hf_token = os.environ.get("HF_TOKEN")
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login(token=hf_token)
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device="cuda" if torch.cuda.is_available() else "cpu"
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from diffusers import ControlNetModel, StableDiffusionXLControlNetPipeline, AutoencoderKL
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from diffusers.utils import load_image
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from PIL import Image
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use_safetensors=True
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)
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pipe.to(device)
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def infer(use_custom_model, model_name, custom_lora_weight, image_in, prompt, negative_prompt, preprocessor, controlnet_conditioning_scale, guidance_scale, inf_steps, seed, progress=gr.Progress(track_tqdm=True)):
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prompt = prompt
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negative_prompt = negative_prompt
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generator = torch.Generator(device=device).manual_seed(seed)
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if image_in == None:
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raise gr.Error("You forgot to upload a source image.")
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