Update app.py

app.py

@@ -1,6 +1,7 @@
 """
 Insta360 3D Reconstruction - Hugging Face Space Version
 Optimized for longer videos with intelligent frame sampling
+Supports ZeroGPU for faster processing
 """
 
 import gradio as gr
@@ -17,6 +18,7 @@ import time
 import warnings
 from scipy import ndimage
 from scipy.ndimage import gaussian_filter
+import spaces  # For ZeroGPU support
 
 warnings.filterwarnings('ignore')
 
@@ -25,13 +27,9 @@ print("🔄 Loading depth estimation model...")
 try:
     dpt_processor = DPTImageProcessor.from_pretrained("Intel/dpt-large")
     dpt_model = DPTForDepthEstimation.from_pretrained("Intel/dpt-large")
-    if torch.cuda.is_available():
-        dpt_model = dpt_model.cuda()
-        print("✓ GPU detected and enabled")
-    else:
-        print("ℹ Running on CPU (slower but works)")
+    # Don't move to CUDA here - ZeroGPU will handle it in decorated functions
     dpt_model.eval()
-    print("✅ Model loaded successfully!")
+    print("✅ Model loaded successfully! (ZeroGPU will handle GPU allocation)")
 except Exception as e:
     print(f"❌ Error loading model: {e}")
     dpt_processor = None
@@ -198,13 +196,12 @@ def equirectangular_to_perspective(equirect_img, fov=90, theta=0, phi=0, height=
     
     return perspective_img
 
+@spaces.GPU  # ZeroGPU decorator for GPU acceleration
 def estimate_depth_enhanced(image, processor, model):
     """Enhanced depth estimation with multi-scale processing"""
     inputs = processor(images=image, return_tensors="pt")
     
-    if torch.cuda.is_available():
-        inputs = {k: v.cuda() for k, v in inputs.items()}
-    
+    # ZeroGPU automatically handles device placement
     with torch.no_grad():
         outputs = model(**inputs)
         predicted_depth = outputs.predicted_depth
@@ -590,4 +587,4 @@ with gr.Blocks(title="Insta360 3D Reconstruction", theme=gr.themes.Soft()) as de
     """)
 
 if __name__ == "__main__":
-    demo.launch()
+    demo.launch()