fixes

CPR_Module/Common/chest_initializer.py

@@ -1,11 +1,10 @@
 import cv2
 import numpy as np
-
 from CPR_Module.Common.keypoints import CocoKeypoints
 from CPR_Module.Common.logging_config import cpr_logger
 
 class ChestInitializer:
-    """Estimates and stabilizes chest region parameters based on keypoints and bounding box."""
+    """Handles chest point detection with validations in estimation."""
     
     def __init__(self):
         self.chest_params = None
@@ -13,7 +12,7 @@ class ChestInitializer:
         self.expected_chest_params = None
 
     def estimate_chest_region(self, keypoints, bounding_box, frame_width, frame_height):
-        """Estimate chest region parameters based on keypoints and bounding box."""
+        """Estimate and validate chest region. Returns (cx, cy, cw, ch) or None."""
         try:
             # Unpack bounding box and calculate shoulder dimensions
             bbox_x1, bbox_y1, bbox_x2, bbox_y2 = bounding_box
@@ -24,62 +23,61 @@ class ChestInitializer:
             right_shoulder = keypoints[CocoKeypoints.RIGHT_SHOULDER.value]
 
             # Midpoints calculation
-            shoulder_center = np.array([
-                (left_shoulder[0] + right_shoulder[0]) / 2,
-                (left_shoulder[1] + right_shoulder[1]) / 2
-            ])
+            shoulder_center = np.array([(left_shoulder[0] + right_shoulder[0]) / 2,
+                                        (left_shoulder[1] + right_shoulder[1]) / 2])
             
-            #& Handling different patient positions
-            # If the x-coordinate shoulder center is closer to that of the Bottom-Right bbox corner (2)
-            # then the orientation is "right"
-            # If the x-coordinate shoulder center is closer to that of the Top-Left bbox corner (1)
-            # then the orientation is "left"
-            if abs(shoulder_center[0] - bbox_x2) < abs(shoulder_center[0] - bbox_x1): # Right orientation
-                chest_center_x = shoulder_center[0] - 0.3 * bbox_delta_y
-                chest_center_y = shoulder_center[1] - 0.1 * bbox_delta_y
-            else: # Left orientation
-                chest_center_x = shoulder_center[0] + 1.0 * bbox_delta_y
-                chest_center_y = shoulder_center[1] - 0.1 * bbox_delta_y
-
-            # Chest dimensions
+            # Calculate chest center by applying directional adjustment separately for x and y
+            chest_center_from_shoulder_x = shoulder_center[0] - 0.3 * bbox_delta_y
+            chest_center_from_shoulder_y = shoulder_center[1] - 0.1 * bbox_delta_y
+            chest_center_from_shoulder = np.array([chest_center_from_shoulder_x, chest_center_from_shoulder_y])
+
+            # Chest dimensions (85% of shoulder width, 40% height)
             chest_dx = bbox_delta_y * 0.8
             chest_dy = bbox_delta_y * 1.75
 
             # Calculate region coordinates
-            x1 = chest_center_x - chest_dx / 2
-            y1 = chest_center_y - chest_dy / 2
-            x2 = chest_center_x + chest_dx / 2
-            y2 = chest_center_y + chest_dy / 2
-
-            # First clamp the bounding box to frame boundaries
-            bbox_x1 = max(0, min(bbox_x1, frame_width - 1))
-            bbox_y1 = max(0, min(bbox_y1, frame_height - 1))
-            bbox_x2 = max(0, min(bbox_x2, frame_width - 1))
-            bbox_y2 = max(0, min(bbox_y2, frame_height - 1))
-
-            # Clamp to bounding box (which is already clamped to frame)
-            x1 = max(bbox_x1, min(x1, bbox_x2))
-            y1 = max(bbox_y1, min(y1, bbox_y2))
-            x2 = max(bbox_x1, min(x2, bbox_x2))
-            y2 = max(bbox_y1, min(y2, bbox_y2))
-
-            # Final validity check
+            x1 = chest_center_from_shoulder[0] - chest_dx / 2
+            y1 = chest_center_from_shoulder[1] - chest_dy / 2
+            x2 = chest_center_from_shoulder[0] + chest_dx / 2
+            y2 = chest_center_from_shoulder[1] + chest_dy / 2
+
+            # Clamp to frame boundaries
+            x1 = max(0, min(x1, frame_width - 1))
+            y1 = max(0, min(y1, frame_height - 1))
+            x2 = max(0, min(x2, frame_width - 1))
+            y2 = max(0, min(y2, frame_height - 1))
+
+            # Check validity
             if x2 <= x1 or y2 <= y1:
                 return None
 
-            return (
-                (x1 + x2) / 2,  # cx
-                (y1 + y2) / 2,  # cy
-                x2 - x1,        # cw
-                y2 - y1         # ch
-            )
+            # Adjusted parameters
+            cx = (x1 + x2) / 2
+            cy = (y1 + y2) / 2
+            cw = x2 - x1
+            ch = y2 - y1
+
+            return (cx, cy, cw, ch)
 
         except (IndexError, TypeError, ValueError) as e:
-            cpr_logger.error(f"Chest estimation error: {e}")
+            print(f"Chest estimation error: {e}")
             return None
 
     def estimate_chest_region_weighted_avg(self, frame_width, frame_height, window_size=60, min_samples=3):
-        """Estimate chest region using weighted average of recent parameters."""
+        """
+        Calculate stabilized chest parameters using weighted averaging with boundary checks.
+        
+        Args:
+            self.chest_params_history: List of recent chest parameters [(cx, cy, cw, ch), ...]
+            frame_width: Width of the video frame
+            frame_height: Height of the video frame
+            window_size: Number of recent frames to consider (default: 5)
+            min_samples: Minimum valid samples required (default: 3)
+            
+        Returns:
+            Tuple of (cx, cy, cw, ch) as integers within frame boundaries,
+            or None if insufficient data or invalid rectangle
+        """
         if not self.chest_params_history:
             return None
         
@@ -121,11 +119,11 @@ class ChestInitializer:
             )
             
         except Exception as e:
-            cpr_logger.error(f"Chest region estimation error: {e}")
+            print(f"Chest region estimation error: {e}")
             return None
     
     def draw_expected_chest_region(self, frame):
-        """Draw the expected chest region on the frame."""
+        """Draws the chest region without validation."""
         if self.expected_chest_params is None:
             return frame
 
@@ -140,7 +138,7 @@ class ChestInitializer:
 
         cv2.circle(frame, (int(cx), int(cy)), 8, (128, 128, 0), -1)
 
-        cv2.putText(frame, "CHEST", (x1, max(10, y1 - 5)), 
+        cv2.putText(frame, "EXPECTED CHEST", (x1, max(10, y1 - 5)), 
                     cv2.FONT_HERSHEY_SIMPLEX, 0.8, (128, 128, 0), 2)
         
         return frame

app.py

@@ -39,7 +39,7 @@ import signal
 
 from CPR_Module.Educational_Mode.CPRAnalyzer import CPRAnalyzer as OfflineAnalyzer
 from CPR_Module.Emergency_Mode.main import CPRAnalyzer as RealtimeAnalyzer
-from CPR_Module.Common.analysis_socket_server import AnalysisSocketServer  # adjust if needed
+from CPR_Module.Common.analysis_socket_server import AnalysisSocketServer  
 from CPR_Module.Common.logging_config import cpr_logger
 
 app = FastAPI()