Update app.py

app.py

@@ -25,7 +25,7 @@ def estimate_depth(image):
     return depth.astype(np.uint8)
 
 def blend_design(cloth_img, design_img):
-    """Blend design onto clothing naturally."""
+    """Blend design onto clothing naturally with fold adaptation."""
     cloth_img = cloth_img.convert("RGB")
     design_img = design_img.convert("RGBA")
     cloth_np = np.array(cloth_img)
@@ -38,9 +38,9 @@ def blend_design(cloth_img, design_img):
     new_w, new_h = int(dw * scale_factor), int(dh * scale_factor)
     design_np = cv2.resize(design_np, (new_w, new_h), interpolation=cv2.INTER_AREA)
     
-    # Convert design to include transparency effect
-    alpha_channel = design_np[:, :, 3] / 255.0  # Extract alpha channel
-    design_np = design_np[:, :, :3]  # Remove alpha channel for processing
+    # Extract alpha channel for transparency
+    alpha_channel = design_np[:, :, 3] / 255.0
+    design_np = design_np[:, :, :3]
     
     # Create a blank canvas and paste the resized design at the center
     x_offset = (w - new_w) // 2
@@ -59,8 +59,8 @@ def blend_design(cloth_img, design_img):
     # Generate displacement map based on depth
     displacement_x = cv2.Sobel(depth_map, cv2.CV_32F, 1, 0, ksize=5)
     displacement_y = cv2.Sobel(depth_map, cv2.CV_32F, 0, 1, ksize=5)
-    displacement_x = cv2.normalize(displacement_x, None, -3, 3, cv2.NORM_MINMAX)
-    displacement_y = cv2.normalize(displacement_y, None, -3, 3, cv2.NORM_MINMAX)
+    displacement_x = cv2.normalize(displacement_x, None, -5, 5, cv2.NORM_MINMAX)
+    displacement_y = cv2.normalize(displacement_y, None, -5, 5, cv2.NORM_MINMAX)
     
     # Warp design using displacement map
     map_x, map_y = np.meshgrid(np.arange(w), np.arange(h))