Update detect.py

object-tracker/opencv/detect.py

@@ -163,7 +163,12 @@ def main():
  cap = cv2.VideoCapture(args.netsrc) 
 
  cap.set(cv2.CAP_PROP_BUFFERSIZE, 0)
+ timeHeartbeat = 0
  while cap.isOpened():
+ if timeHeartbeat < time.mktime(time.gmtime()):
+ timeHeartbeat = time.mktime(time.gmtime()) + 10
+ mqtt_bridge.publish("skyscan/heartbeat", "skyscan-object-tracker-" +ID+" Heartbeat", 0, False)
+ start_time = time.monotonic()
  ret, frame = cap.read()
  if not ret: 
  if args.videosrc=='file':
@@ -211,7 +216,6 @@ def main():
  cv2_im = append_objs_to_img(cv2_im, detections, labels, trdata, trackerFlag)
  follow_x, follow_y = object_to_follow(detections, labels, trdata, trackerFlag)
  if args.display == 'True':
- cv2_im = cv2.rectangle(cv2_im, (775, 440), (779, 445), (255, 255, 0), 2)
  cv2.imshow('frame', cv2_im)
 
  if follow_x != None:
@@ -222,7 +226,8 @@ def main():
  "y": follow_y
  }
  follow_json = json.dumps(follow)
- print("x: {} y:{}".format(follow_x,follow_y))
+ end_time = time.monotonic()
+ print("x: {} y:{} Inference: {:.2f} ms".format(follow_x,follow_y, (end_time - start_time) * 1000))
  mqtt_bridge.publish(mqtt_topic, follow_json, 0, False)
 
  if cv2.waitKey(1) & 0xFF == ord('q'):
@@ -251,7 +256,7 @@ def object_to_follow( objs, labels, trdata, trackerFlag):
  best_score = obj_score
 
  obj_id = int(obj[5].item())
- print("Tracking - x0: {} y0: {} x1: {} y1: {}".format(x0,y0,x1,y1))
+ #print("Tracking - x0: {} y0: {} x1: {} y1: {}".format(x0,y0,x1,y1))
  follow_x = x0 + ((x1 - x0)/2)
  follow_y = y0 + ((y1 - y0)/2)
  else:
@@ -263,7 +268,7 @@ def object_to_follow( objs, labels, trdata, trackerFlag):
  best_score = obj_score
 
  obj_id = int(obj[5].item())
- print("Detect - x0: {} y0: {} x1: {} y1: {}".format(x0,y0,x1,y1))
+ #print("Detect - x0: {} y0: {} x1: {} y1: {}".format(x0,y0,x1,y1))
 
  follow_x = x0 + ((x1 - x0)/2)
  follow_y = y0 + ((y1 - y0)/2)