Update app.py

app.py

@@ -86,25 +86,31 @@ def estimate_depth(image, model_name="depth-anything/Depth-Anything-V2-Small-hf"
     
     return depth_map
 
-def apply_depth_aware_blur(image, depth_map, max_sigma=15, min_sigma=0):
-    """Apply depth-aware blur where farther objects are more blurred."""
+def apply_depth_aware_blur(image, max_sigma=15, min_sigma=0):
+    """Apply depth-aware blur with farther objects more blurred."""
+    # Estimate depth (1 = nearest, 0 = farthest)
+    depth_map = estimate_depth(image)  # Returns 1 for near, 0 for far
     
-    # Ensure depth map is normalized between 0 (near) and 1 (far)
-    depth_map = (depth_map - depth_map.min()) / (depth_map.max() - depth_map.min())
-
-    # Convert image to NumPy array
-    image_array = np.array(image, dtype=np.float32)
-
-    # Initialize blurred image array
-    blurred_image = np.zeros_like(image_array)
-
-    # Apply pixel-wise Gaussian blur based on depth
+    # INVERT the depth map (now 1 = farthest, 0 = nearest)
+    depth_map = 1 - depth_map
+    
+    image_array = np.array(image)
+    
+    # Create single blurred version at max sigma
+    max_blurred = np.zeros_like(image_array, dtype=np.float32)
     for channel in range(3):
-        sigma_map = min_sigma + depth_map * (max_sigma - min_sigma)  # Map depth to sigma
-        blurred_image[:, :, channel] = gaussian_filter(image_array[:, :, channel], sigma=sigma_map)
+        max_blurred[:, :, channel] = gaussian_filter(
+            image_array[:, :, channel].astype(np.float32),
+            sigma=max_sigma
+        )
+    
+    # Create 3-channel depth map for blending
+    depth_3d = np.stack([depth_map] * 3, axis=2)
     
-    # Convert back to image format
-    return Image.fromarray(blurred_image.astype(np.uint8))
+    # Blend: More depth (farther) = more blur
+    result = image_array * (1 - depth_3d) + max_blurred * depth_3d
+    
+    return Image.fromarray(result.astype(np.uint8))
 
 def process_image(image, blur_type, sigma=15):
     """Process image based on blur type."""