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Runtime error
Runtime error
Update app.py
Browse files
app.py
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@@ -15,7 +15,11 @@ import gradio as gr
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USE_TORCH_COMPILE = 0
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ENABLE_CPU_OFFLOAD = 0
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#
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def download_file(url, folder_path, filename):
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if not os.path.exists(folder_path):
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os.makedirs(folder_path)
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@@ -34,73 +38,26 @@ def download_file(url, folder_path, filename):
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print(f"Error downloading the file. Status code: {response.status_code}")
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# Download necessary models and files
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# MODEL
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download_file(
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"https://huggingface.co/dantea1118/juggernaut_reborn/resolve/main/juggernaut_reborn.safetensors?download=true",
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"models/models/Stable-diffusion",
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"juggernaut_reborn.safetensors"
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)
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# UPSCALER
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download_file(
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"https://huggingface.co/ai-forever/Real-ESRGAN/resolve/main/RealESRGAN_x2.pth?download=true",
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"models/upscalers/",
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"RealESRGAN_x2.pth"
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)
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download_file(
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"https://huggingface.co/ai-forever/Real-ESRGAN/resolve/main/RealESRGAN_x4.pth?download=true",
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"models/upscalers/",
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"RealESRGAN_x4.pth"
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)
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# NEGATIVE
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download_file(
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"https://huggingface.co/philz1337x/embeddings/resolve/main/verybadimagenegative_v1.3.pt?download=true",
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"models/embeddings",
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"verybadimagenegative_v1.3.pt"
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)
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download_file(
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"https://huggingface.co/datasets/AddictiveFuture/sd-negative-embeddings/resolve/main/JuggernautNegative-neg.pt?download=true",
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"models/embeddings",
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"JuggernautNegative-neg.pt"
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)
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# LORA
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download_file(
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"https://huggingface.co/philz1337x/loras/resolve/main/SDXLrender_v2.0.safetensors?download=true",
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"models/Lora",
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"SDXLrender_v2.0.safetensors"
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)
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download_file(
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"https://huggingface.co/philz1337x/loras/resolve/main/more_details.safetensors?download=true",
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"models/Lora",
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"more_details.safetensors"
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)
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# CONTROLNET
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download_file(
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"https://huggingface.co/lllyasviel/ControlNet-v1-1/resolve/main/control_v11f1e_sd15_tile.pth?download=true",
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"models/ControlNet",
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"control_v11f1e_sd15_tile.pth"
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)
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# VAE
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download_file(
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"https://huggingface.co/stabilityai/sd-vae-ft-mse-original/resolve/main/vae-ft-mse-840000-ema-pruned.safetensors?download=true",
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"models/VAE",
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"vae-ft-mse-840000-ema-pruned.safetensors"
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)
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# Set up the device
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device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
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class LazyRealESRGAN:
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def __init__(self, device, scale):
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@@ -215,26 +172,7 @@ class ImageProcessor:
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return pipe
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condition_image = resize_and_upscale(input_image, resolution)
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condition_image = create_hdr_effect(condition_image, hdr)
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result = self.pipe(
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prompt=prompt,
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negative_prompt=negative_prompt,
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image=condition_image,
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control_image=condition_image,
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width=condition_image.size[0],
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height=condition_image.size[1],
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strength=strength,
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num_inference_steps=num_inference_steps,
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guidance_scale=guidance_scale,
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generator=torch.manual_seed(0),
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).images[0]
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return result
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# Create an instance of ImageProcessor
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image_processor = ImageProcessor()
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@spaces.GPU
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USE_TORCH_COMPILE = 0
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ENABLE_CPU_OFFLOAD = 0
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# Set up the device
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device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
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# Function to download files (from the example)
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def download_file(url, folder_path, filename):
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if not os.path.exists(folder_path):
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os.makedirs(folder_path)
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print(f"Error downloading the file. Status code: {response.status_code}")
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# Download necessary models and files
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def download_models():
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models = {
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"MODEL": ("https://huggingface.co/dantea1118/juggernaut_reborn/resolve/main/juggernaut_reborn.safetensors?download=true", "models/models/Stable-diffusion", "juggernaut_reborn.safetensors"),
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"UPSCALER_X2": ("https://huggingface.co/ai-forever/Real-ESRGAN/resolve/main/RealESRGAN_x2.pth?download=true", "models/upscalers/", "RealESRGAN_x2.pth"),
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"UPSCALER_X4": ("https://huggingface.co/ai-forever/Real-ESRGAN/resolve/main/RealESRGAN_x4.pth?download=true", "models/upscalers/", "RealESRGAN_x4.pth"),
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"NEGATIVE_1": ("https://huggingface.co/philz1337x/embeddings/resolve/main/verybadimagenegative_v1.3.pt?download=true", "models/embeddings", "verybadimagenegative_v1.3.pt"),
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"NEGATIVE_2": ("https://huggingface.co/datasets/AddictiveFuture/sd-negative-embeddings/resolve/main/JuggernautNegative-neg.pt?download=true", "models/embeddings", "JuggernautNegative-neg.pt"),
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"LORA_1": ("https://huggingface.co/philz1337x/loras/resolve/main/SDXLrender_v2.0.safetensors?download=true", "models/Lora", "SDXLrender_v2.0.safetensors"),
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"LORA_2": ("https://huggingface.co/philz1337x/loras/resolve/main/more_details.safetensors?download=true", "models/Lora", "more_details.safetensors"),
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"CONTROLNET": ("https://huggingface.co/lllyasviel/ControlNet-v1-1/resolve/main/control_v11f1e_sd15_tile.pth?download=true", "models/ControlNet", "control_v11f1e_sd15_tile.pth"),
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"VAE": ("https://huggingface.co/stabilityai/sd-vae-ft-mse-original/resolve/main/vae-ft-mse-840000-ema-pruned.safetensors?download=true", "models/VAE", "vae-ft-mse-840000-ema-pruned.safetensors"),
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}
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for model, (url, folder, filename) in models.items():
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download_file(url, folder, filename)
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download_models()
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class LazyRealESRGAN:
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def __init__(self, device, scale):
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return pipe
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image_processor = ImageProcessor()
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@spaces.GPU
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