fix(studio): harden runtime integration and dependency defaults

Stabilize studio publish/visualization flow and tighten export behavior while aligning project dependencies with the monorepo runtime expectations.

opengait-studio/opengait_studio/visualizer.py

@@ -50,45 +50,24 @@ ImageArray = NDArray[np.uint8]
 # COCO-format skeleton connections (17 keypoints)
 # Connections are pairs of keypoint indices
 SKELETON_CONNECTIONS: list[tuple[int, int]] = [
-    (0, 1),   # nose -> left_eye
-    (0, 2),   # nose -> right_eye
-    (1, 3),   # left_eye -> left_ear
-    (2, 4),   # right_eye -> right_ear
-    (5, 6),   # left_shoulder -> right_shoulder
-    (5, 7),   # left_shoulder -> left_elbow
-    (7, 9),   # left_elbow -> left_wrist
-    (6, 8),   # right_shoulder -> right_elbow
+    (0, 1),  # nose -> left_eye
+    (0, 2),  # nose -> right_eye
+    (1, 3),  # left_eye -> left_ear
+    (2, 4),  # right_eye -> right_ear
+    (5, 6),  # left_shoulder -> right_shoulder
+    (5, 7),  # left_shoulder -> left_elbow
+    (7, 9),  # left_elbow -> left_wrist
+    (6, 8),  # right_shoulder -> right_elbow
     (8, 10),  # right_elbow -> right_wrist
-    (11, 12), # left_hip -> right_hip
+    (11, 12),  # left_hip -> right_hip
     (5, 11),  # left_shoulder -> left_hip
     (6, 12),  # right_shoulder -> right_hip
-    (11, 13), # left_hip -> left_knee
-    (13, 15), # left_knee -> left_ankle
-    (12, 14), # right_hip -> right_knee
-    (14, 16), # right_knee -> right_ankle
+    (11, 13),  # left_hip -> left_knee
+    (13, 15),  # left_knee -> left_ankle
+    (12, 14),  # right_hip -> right_knee
+    (14, 16),  # right_knee -> right_ankle
 ]
 
-# Keypoint names for COCO format (17 keypoints)
-KEYPOINT_NAMES: list[str] = [
-    "nose", "left_eye", "right_eye", "left_ear", "right_ear",
-    "left_shoulder", "right_shoulder", "left_elbow", "right_elbow",
-    "left_wrist", "right_wrist", "left_hip", "right_hip",
-    "left_knee", "right_knee", "left_ankle", "right_ankle"
-]
-
-# Joints where angles are typically calculated (for scoliosis/ gait analysis)
-ANGLE_JOINTS: list[tuple[int, int, int]] = [
-    (5, 7, 9),   # left_shoulder -> left_elbow -> left_wrist
-    (6, 8, 10),  # right_shoulder -> right_elbow -> right_wrist
-    (7, 5, 11),  # left_elbow -> left_shoulder -> left_hip
-    (8, 6, 12),  # right_elbow -> right_shoulder -> right_hip
-    (5, 11, 13), # left_shoulder -> left_hip -> left_knee
-    (6, 12, 14), # right_shoulder -> right_hip -> right_knee
-    (11, 13, 15),# left_hip -> left_knee -> left_ankle
-    (12, 14, 16),# right_hip -> right_knee -> right_ankle
-]
-
-
 
 class OpenCVVisualizer:
     def __init__(self) -> None:
@@ -210,7 +189,7 @@ class OpenCVVisualizer:
         if pose_data is None:
             return
 
-        keypoints_obj = pose_data.get('keypoints')
+        keypoints_obj = pose_data.get("keypoints")
         if keypoints_obj is None:
             return
 
@@ -222,7 +201,7 @@ class OpenCVVisualizer:
         h, w = frame.shape[:2]
 
         # Get confidence scores if available
-        confidence_obj = pose_data.get('confidence')
+        confidence_obj = pose_data.get("confidence")
         confidences = (
             np.asarray(confidence_obj, dtype=np.float32)
             if confidence_obj is not None
@@ -267,7 +246,7 @@ class OpenCVVisualizer:
         if pose_data is None:
             return
 
-        angles_obj = pose_data.get('angles')
+        angles_obj = pose_data.get("angles")
         if angles_obj is None:
             return
 
@@ -467,12 +446,10 @@ class OpenCVVisualizer:
 
     def _prepare_segmentation_view(
         self,
-        mask_raw: ImageArray | None,
+        _mask_raw: ImageArray | None,
         silhouette: NDArray[np.float32] | None,
-        bbox: BBoxXYXY | None,
+        _bbox: BBoxXYXY | None,
     ) -> ImageArray:
-        _ = mask_raw
-        _ = bbox
         return self._prepare_normalized_view(silhouette)
 
     def _fit_gray_to_display(
@@ -661,20 +638,7 @@ class OpenCVVisualizer:
         y_pos = h - 8
         y_top = max(0, h - MODE_LABEL_PAD)
 
-        _ = cv2.rectangle(
-            image,
-            (0, y_top),
-            (w, h),
-            COLOR_DARK_GRAY,
-            -1,
-        )
-        _ = cv2.rectangle(
-            image,
-            (x_pos - 6, y_pos - text_height - 6),
-            (x_pos + text_width + 8, y_pos + 6),
-            COLOR_DARK_GRAY,
-            -1,
-        )
+        _ = cv2.rectangle(image, (0, y_top), (w, h), COLOR_DARK_GRAY, -1)
 
         # Draw text
         _ = cv2.putText(
@@ -706,9 +670,11 @@ class OpenCVVisualizer:
         Args:
             frame: Input frame (H, W, C) uint8
             bbox: Bounding box in XYXY format (x1, y1, x2, y2) or None
+            bbox_mask: Bounding box in mask coordinates (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
+            segmentation_input: Windowed silhouette stack for model input visualization
             label: Classification label or None
             confidence: Classification confidence [0,1] or None
             fps: Current FPS