feat: increase blur bounding box padding, label UI speeds, default to pixelate

src/faceblur/app.py

@@ -201,8 +201,16 @@ def run() -> None:
 
         blur_method = questionary.select(
             "Select blur method:",
-            choices=["gaussian", "pixelate", "blackout", "elliptical", "median"],
-            default="gaussian",
+            choices=[
+                questionary.Choice(
+                    "Pixelate (Blazingly Fast - Recommended)", value="pixelate"
+                ),
+                questionary.Choice("Blackout (Blazingly Fast)", value="blackout"),
+                questionary.Choice("Gaussian (Moderate CPU)", value="gaussian"),
+                questionary.Choice("Elliptical (Heavy CPU)", value="elliptical"),
+                questionary.Choice("Median (Heavy CPU)", value="median"),
+            ],
+            default="pixelate",
         ).ask()
 
         if not blur_method:

src/faceblur/blur.py

@@ -13,6 +13,7 @@ def apply_blur(
     bbox: Tuple[int, int, int, int],
     method: BlurMethod = "gaussian",
     strength: float = 5.0,
+    padding: float = 0.25,
 ) -> np.ndarray:
     """Apply blur to a face region in an image.
 
@@ -21,11 +22,22 @@ def apply_blur(
         bbox: Face bounding box (x1, y1, x2, y2)
         method: Blur method name
         strength: Blur strength multiplier
+        padding: Percentage to expand the bounding box to prevent tracking lag exposure
 
     Returns:
         The modified image
     """
     x1, y1, x2, y2 = bbox
+
+    # Expand bounding box to account for interpolation lag
+    w_pad = int((x2 - x1) * padding)
+    h_pad = int((y2 - y1) * padding)
+
+    x1 -= w_pad
+    y1 -= h_pad
+    x2 += w_pad
+    y2 += h_pad
+
     h, w = image.shape[:2]
 
     # Clamp to image bounds
@@ -91,7 +103,8 @@ def interpolate_bboxes(
     Returns:
         Interpolated bounding box
     """
-    return tuple(int(a + t * (b - a)) for a, b in zip(bbox_a, bbox_b))
+    res = tuple(int(a + t * (b - a)) for a, b in zip(bbox_a, bbox_b))
+    return (res[0], res[1], res[2], res[3])
 
 
 def get_bboxes_for_frame(