Create app.py

app.py

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+import gradio as gr
+from diffusers import StableDiffusionPipeline
+import torch
+from PIL import Image
+import io
+
+# Load the Stable Fast 3D model
+model_id = "stabilityai/stable-fast-3d"
+pipe = StableDiffusionPipeline.from_pretrained(model_id, torch_dtype=torch.float16)
+pipe = pipe.to("cuda")
+
+def convert_2d_to_3d(input_image, prompt):
+    # Prepare the input image
+    if input_image is not None:
+        input_image = Image.open(io.BytesIO(input_image))
+        input_image = input_image.resize((512, 512))
+    
+    # Generate the 3D preview
+    output_image = pipe(
+        prompt=prompt,
+        image=input_image,
+        num_inference_steps=50,
+        guidance_scale=7.5
+    ).images[0]
+    
+    return output_image
+
+# Create the Gradio interface
+iface = gr.Interface(
+    fn=convert_2d_to_3d,
+    inputs=[
+        gr.Image(type="filepath", label="Upload 2D Floor Layout"),
+        gr.Textbox(label="Prompt (e.g., '3D render of a modern apartment floor plan')")
+    ],
+    outputs=gr.Image(type="pil", label="3D Preview"),
+    title="2D to 3D Floor Layout Converter",
+    description="Upload a 2D floor layout image and get a 3D preview using Stable Fast 3D model."
+)
+
+# Launch the app
+iface.launch()