fix(demo): stabilize visualizer bbox and mask rendering

Align bbox coordinate handling across primary and fallback paths, normalize Both-mode raw mask rendering, and tighten demo result typing to reduce runtime/display inconsistencies.

opengait/demo/visualizer.py

@@ -13,8 +13,11 @@ import cv2
 import numpy as np
 from numpy.typing import NDArray
 
+from .preprocess import BBoxXYXY
+
 logger = logging.getLogger(__name__)
 
+
 # Window names
 MAIN_WINDOW = "Scoliosis Detection"
 SEG_WINDOW = "Segmentation"
@@ -66,13 +69,13 @@ class OpenCVVisualizer:
     def _draw_bbox(
         self,
         frame: ImageArray,
-        bbox: tuple[int, int, int, int] | None,
+        bbox: BBoxXYXY | None,
     ) -> None:
         """Draw bounding box on frame if present.
 
         Args:
             frame: Input frame (H, W, 3) uint8 - modified in place
-            bbox: Bounding box as (x1, y1, x2, y2) or None
+            bbox: Bounding box in XYXY format as (x1, y1, x2, y2) or None
         """
         if bbox is None:
             return
@@ -145,7 +148,7 @@ class OpenCVVisualizer:
     def _prepare_main_frame(
         self,
         frame: ImageArray,
-        bbox: tuple[int, int, int, int] | None,
+        bbox: BBoxXYXY | None,
         track_id: int,
         fps: float,
         label: str | None,
@@ -155,7 +158,7 @@ class OpenCVVisualizer:
 
         Args:
             frame: Input frame (H, W, C) uint8
-            bbox: Bounding box or None
+            bbox: Bounding box in XYXY format (x1, y1, x2, y2) or None
             track_id: Tracking ID
             fps: Current FPS
             label: Classification label or None
@@ -324,6 +327,9 @@ class OpenCVVisualizer:
                 mask_gray = cast(ImageArray, cv2.cvtColor(mask_raw, cv2.COLOR_BGR2GRAY))
             else:
                 mask_gray = mask_raw
+            # Normalize to uint8 [0,255] for display (handles both float [0,1] and uint8 inputs)
+            if mask_gray.dtype == np.float32 or mask_gray.dtype == np.float64:
+                mask_gray = (mask_gray * 255).astype(np.uint8)
             raw_gray = cast(
                 ImageArray,
                 cv2.resize(
@@ -333,6 +339,7 @@ class OpenCVVisualizer:
                 ),
             )
 
+
         # Normalized view preparation (without indicator)
         if silhouette is None:
             norm_gray = np.zeros((DISPLAY_HEIGHT, DISPLAY_WIDTH), dtype=np.uint8)
@@ -402,7 +409,7 @@ class OpenCVVisualizer:
     def update(
         self,
         frame: ImageArray,
-        bbox: tuple[int, int, int, int] | None,
+        bbox: BBoxXYXY | None,
         track_id: int,
         mask_raw: ImageArray | None,
         silhouette: NDArray[np.float32] | None,
@@ -414,7 +421,7 @@ class OpenCVVisualizer:
 
         Args:
             frame: Input frame (H, W, C) uint8
-            bbox: Bounding box as (x1, y1, x2, y2) or None
+            bbox: Bounding box in XYXY format (x1, y1, x2, y2) or None
             track_id: Tracking ID
             mask_raw: Raw binary mask (H, W) uint8 or None
             silhouette: Normalized silhouette (64, 44) float32 [0,1] or None