Initial commit

app.py

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+import gradio as gr
+from diffusers import StableDiffusionImg2ImgPipeline
+import torch
+from PIL import Image
+import io
+import base64
+
+# Carica il modello Stable Diffusion
+pipe = StableDiffusionImg2ImgPipeline.from_pretrained("stabilityai/stable-diffusion-2-1")
+pipe.to("cuda" if torch.cuda.is_available() else "cpu")
+
+def enhance_image(image, prompt, negative_prompt, cfg_scale, denoising_strength):
+    """
+    Migliora un'immagine utilizzando Stable Diffusion Img2Img.
+    """
+    image = Image.open(image).convert("RGB")
+    enhanced_image = pipe(
+        prompt=prompt,
+        negative_prompt=negative_prompt,
+        image=image,
+        strength=denoising_strength,
+        guidance_scale=cfg_scale
+    ).images[0]
+    
+    return enhanced_image
+
+# Interfaccia utente con Gradio
+demo = gr.Interface(
+    fn=enhance_image,
+    inputs=[
+        gr.Image(type="filepath", label="Carica l'immagine:"),
+        gr.Textbox(label="Prompt", value="highly detailed, ultra high resolution"),
+        gr.Textbox(label="Negative Prompt", value="low quality, blurry, artifacts"),
+        gr.Slider(1, 20, value=7, label="CFG Scale"),
+        gr.Slider(0.1, 1.0, value=0.35, label="Denoising Strength")
+    ],
+    outputs=gr.Image(type="pil", label="Immagine migliorata"),
+    title="Image Enhancer con Stable Diffusion",
+    description="Carica un'immagine e usa Stable Diffusion per migliorarla."
+)
+
+if __name__ == "__main__":
+    demo.launch()

requirements.txt

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+diffusers
+transformers
+accelerate
+safetensors
+gradio
+torch