Update app.py

app.py

@@ -7,7 +7,7 @@ import math
 import os
 from threading import Event
 import traceback
-import cv2
+import cv2  # Added for bilateral filtering
 
 # Constants
 IMG_SIZE = 128
@@ -165,7 +165,7 @@ class DiffusionModel(nn.Module):
         else:
             labels = labels.to(device)
 
-        # ---- REVERTED SAMPLING LOOP WITH NOISE REDUCTION ----
+        # REVERTED SAMPLING LOOP WITH NOISE REDUCTION
         for t in reversed(range(self.timesteps)):
             if cancel_event.is_set():
                 return None
@@ -199,7 +199,7 @@ class DiffusionModel(nn.Module):
         x_0 = std * x_0 + mean
         x_0 = torch.clamp(x_0, 0., 1.)
 
-        # ---- ENHANCED SHARPENING ----
+        # ENHANCED SHARPENING
         # First apply mild bilateral filtering to reduce noise while preserving edges
         x_np = x_0.cpu().permute(0, 2, 3, 1).numpy()
         filtered = []