Debugging logs for IDs

people_tracking_v2/scripts/HoC.py

@@ -30,6 +30,7 @@ def segmented_images_callback(self, msg):
 
                 # Extract the ID from the incoming message
                 detection_id = msg.ids[i]
+                rospy.loginfo(f"Received Detection ID: {detection_id} for segmented image #{i + 1}")
 
                 # Publish the HoC vectors with the detection ID
                 self.publish_hoc_vectors(hoc_hue, hoc_sat, detection_id)

people_tracking_v2/scripts/pose_estimation_node.py

@@ -70,8 +70,8 @@ def __init__(
         self._image_subscriber = rospy.Subscriber("/Webcam/image_raw", Image, self._image_callback)
         self._recognitions_publisher = rospy.Publisher("/pose_recognitions", Recognitions, queue_size=10)
         self._pose_distance_publisher = rospy.Publisher("/pose_distances", BodySize, queue_size=10)
-        if self._topic_publish_result_image or self._service_publish_result_image:
-            self._result_image_publisher = rospy.Publisher("/pose_result_image", Image, queue_size=10)
+        #if self._topic_publish_result_image or self._service_publish_result_image:
+        self._result_image_publisher = rospy.Publisher("/pose_result_image", Image, queue_size=10)
 
         self.last_master_check = rospy.get_time()
 
@@ -95,6 +95,7 @@ def _image_callback(self, image_msg):
                 pose_distance_msg = BodySize()
                 pose_distance_msg.header.stamp = rospy.Time.now()
                 pose_distance_msg.id = i + 1  # Assigning the same sequential ID
+                rospy.loginfo(f"Processing Pose with ID: {pose_distance_msg.id}")
 
                 if "LShoulder" in pose and "LHip" in pose:
                     pose_distance_msg.left_shoulder_hip_distance = self._wrapper.compute_distance(pose["LShoulder"], pose["LHip"])

people_tracking_v2/scripts/yolo_seg.py

@@ -20,6 +20,7 @@ def __init__(self):
         self.model = YOLO("yolov8n-seg.pt")  # Ensure the model supports segmentation
 
         self.image_sub = rospy.Subscriber("/Webcam/image_raw", Image, self.image_callback)
+        #self.depth_sub = rospy.Subscriber("/depth_registered/image", Image, self.image_callback)
         self.segmented_images_pub = rospy.Publisher("/segmented_images", SegmentedImages, queue_size=10)
         self.individual_segmented_image_pub = rospy.Publisher("/individual_segmented_images", Image, queue_size=10)
         self.bounding_box_image_pub = rospy.Publisher("/bounding_box_image", Image, queue_size=10)
@@ -65,6 +66,7 @@ def image_callback(self, data):
         for i, (box, score, label, mask) in enumerate(human_detections):
             detection = Detection()
             detection.id = i + 1  # Assigning sequential ID starting from 1
+            rospy.loginfo(f"Detection ID: {id} for box: {box}")
             detection.x1 = float(box[0])
             detection.y1 = float(box[1])
             detection.x2 = float(box[2])
@@ -131,6 +133,7 @@ def image_callback(self, data):
                 segmented_images_msg.ids.append(i + 1)  # Add the ID to the ids list
 
         # Publish segmented images as a batch
+        rospy.loginfo(f"Publishing Segmented Images with IDs: {segmented_images_msg.ids}")
         self.segmented_images_pub.publish(segmented_images_msg)
 
         # Publish bounding box image