Update app.py

app.py

@@ -1,31 +1,25 @@
 import gradio as gr
 import torch
 from diffusers import StableDiffusionPipeline
-from PIL import Image
 
-# Load the pre-trained Ghibli-Diffusion model
+device = "cuda" if torch.cuda.is_available() else "cpu"
 model_id = "nitrosocke/Ghibli-Diffusion"
-pipeline = StableDiffusionPipeline.from_pretrained(model_id, torch_dtype=torch.float16)
-pipeline.to("cuda")  # Ensure GPU acceleration
 
-def generate_ghibli_portrait(image):
-    # Convert input image to PIL format
-    input_image = Image.open(image).convert("RGB").resize((512, 512))
-    
-    # Generate image using the model
-    prompt = "Ghibli-style portrait of a person, highly detailed, soft lighting"
-    result = pipeline(prompt=prompt, image=input_image).images[0]
-    
+# Load the model
+pipe = StableDiffusionPipeline.from_pretrained(model_id, torch_dtype=torch.float16 if device == "cuda" else torch.float32)
+pipe.to(device)
+
+def generate_ghibli_style(image):
+    prompt = "Studio Ghibli style portrait of a person, highly detailed, beautiful colors"
+    result = pipe(prompt, init_image=image, strength=0.75).images[0]
     return result
 
-# Gradio UI
-demo = gr.Interface(
-    fn=generate_ghibli_portrait,
-    inputs=gr.Image(type="file", label="Upload your photo"),
-    outputs=gr.Image(label="Ghibli-style Portrait"),
+iface = gr.Interface(
+    fn=generate_ghibli_style,
+    inputs=gr.Image(type="pil"),
+    outputs=gr.Image(),
     title="Studio Ghibli Portrait Generator",
-    description="Upload your photo to generate a Ghibli-style portrait using AI."
+    description="Upload a photo, and this AI will transform it into a Ghibli-style portrait!"
 )
 
-if __name__ == "__main__":
-    demo.launch()
+iface.launch()