updated

app.py

@@ -15,11 +15,11 @@ def pad_to_divisible(img, div=32):
     padded = cv2.copyMakeBorder(img, 0, pad_bottom, 0, pad_right, cv2.BORDER_CONSTANT, value=[0, 0, 0])
     return padded
 
-# Force CPU for Hugging Face Spaces
+
 device = torch.device("cpu")
 print("Using device:", device)
 
-# Load weights into UNet model with ResNet34 backbone
+
 model_path = "best_unet.pth"
 if os.path.exists(model_path):
     model = smp.Unet(
@@ -65,8 +65,8 @@ demo = gr.Interface(
         gr.Image(label="Predicted Mask"),
         gr.Image(label="Overlay on Image")
     ],
-    title="Wrinkle Segmentation with UNet + ResNet34",
-    description="Upload a face image to see wrinkle regions detected by a UNet model trained for wrinkle segmentation."
+    title="Wrinkle Segmentation"
+    description="Upload a face image to see wrinkle regions detected"
 )
 
 demo.launch()