'''
basicUDP.py - This is basic UDP example.
Created by Yasin Kaya (selengalp), January 2, 2019.
Modified by Saeed Johar (saeedjohar), October 3, 2019.
'''
from tracker import tracker
from time import sleep
node = tracker.Tracker()
#node.Sendline()
node.readNMEA()
sleep(2)
while True:
message = node.readNMEA()
msg = message.decode(encoding="utf-8", errors='ignore')
#print(msg)
msg = ""
sleep(2)
def init_tracker(self,model_proto,model_weight): self.tracker = tracker.Tracker(model_proto,model_weight);
def pipeline_single_tracker(det,img,otsu_box,track,draw=False):
track.frame_count+=1
org_im=img.copy()
img_dim = (img.shape[1], img.shape[0])
if debug:
print('\nFrame:', track.frame_count,' \n')
#Detect person in the image
detect_box = det.get_localization(img) # measurement
final_box=[]
improved=False
#check for small box
if len(detect_box)!=0:
detect_box=helpers.remove_small_box(detect_box[0],height_limit=150,width_limit=150)
#If Detected
if len(detect_box)!=0:
if debug:
print("Detection found")
# detect_box=detect_box[0]
if draw:
img1= helpers.draw_box_label('Org Det.',img, detect_box, box_color=(255, 0, 0))
#Tracker alive or not
if track.current_tracker!=None:
#If alive
if debug:
print("Tracker Alive")
track_box=track.current_tracker.box
#Track result matches,detection or not
#------------------------------------
#If matches
if helpers.box_iou2(track_box,detect_box)>track.detect_track_iou_thres:
#Check abnormal detect box
#Abnormal, use previous box NOTE can be improved
# detect_area=helpers.find_area(detect_box)
# track_area=helpers.find_area(track_box)
height_d,width_d=helpers.find_dim(detect_box)
height_t,width_t=helpers.find_dim(track_box)
delta=0.2
delta2=0.3
if height_d<(1-delta)*height_t or width_d<(1-delta)*width_t or height_d>(1+delta2)*height_t or width_d>(1+delta2)*width_t:
if debug:
print("Detection improved by tracker")
improved=True
detect_box=track.current_tracker.box
# detect_box=helpers.union_box(track_box,detect_box)
#Track box does not matched
elif otsu_box==True and helpers.box_ios(detect_box,track_box)>track.box_ios_thres and helpers.box_iou2(track_box,helpers.largest_contour(img))>track.otsu_iou_thres:
if debug:
print("Detect box is subset of track. Track box and Otsu are similar.")
print("Detection improved by tracker")
detect_box=track.current_tracker.box
improved=True
else:
if debug:
print("Tracker lost deleting the current tracker")
track.tracker_list.append(track.current_tracker)
track.current_tracker=None
#Improve detect_box by Otsu or any other way
if otsu_box==True:
ret,detect_box=helpers.detection_otsu(img,detect_box,draw=True,threshold=track.otsu_iou_thres)
#Update or create tracker
#Update if exist or matched
if track.current_tracker!=None:
final_box = detect_box
z = np.expand_dims(detect_box, axis=0).T
track.current_tracker.kalman_filter(z)
xx = track.current_tracker.x_state.T[0].tolist()
xx =[xx[0], xx[2], xx[4], xx[6]]
if improved:
final_box = xx
track.current_tracker.box =xx
track.current_tracker.hits += 1
track.current_tracker.no_losses =0
else:
final_box = detect_box
z = np.expand_dims(detect_box, axis=0).T
track.current_tracker = tracker.Tracker() # Create a new tracker
x = np.array([[z[0], 0, z[1], 0, z[2], 0, z[3], 0]]).T
track.current_tracker.x_state = x
track.current_tracker.predict_only()
xx = track.current_tracker.x_state
xx = xx.T[0].tolist()
xx =[xx[0], xx[2], xx[4], xx[6]]
track.current_tracker.box =xx
track.current_tracker.id = track.track_id_list.popleft() # assign an ID for the tracker
if debug:
print("New Tracker\n ID: ",track.current_tracker.id)
#Not Detection
else:
#Tracker alive or not
#alive
if track.current_tracker!=None:
if debug:
print("Tracker Alive")
track.current_tracker.predict_only()
xx = track.current_tracker.x_state
xx = xx.T[0].tolist()
xx =[xx[0], xx[2], xx[4], xx[6]]
if otsu_box==True:
# if False:
current_state=xx
flag,current_otsu=helpers.tracker_otsu(img,current_state,draw=True,threshold=track.otsu_iou_thres)
if not flag:
if debug:
print("Tracker does not matched with Otsu box, Tracker id",track.current_tracker.id)
xx=helpers.remove_small_box(xx,height_limit=150,width_limit=150)
if len(xx)==0:
if debug:
print("Small track box. Deleting...............")
track.tracker_list.append(track.current_tracker)
track.current_tracker=None
final_box = []
else:
track.current_tracker.no_losses+=1
track.current_tracker.box =xx
final_box = xx
else:
if debug:
print("Tracker box matched with Otsu box, Tracker id",track.current_tracker.id)
track.current_tracker.no_losses += 0.5
final_box = current_otsu
current_otsu = np.expand_dims(current_otsu, axis=0).T
track.current_tracker.kalman_filter(current_otsu)
xx = track.current_tracker.x_state.T[0].tolist()
xx =[xx[0], xx[2], xx[4], xx[6]]
track.current_tracker.box =xx
else:
if debug:
print("No Otsu")
xx=helpers.remove_small_box(xx,height_limit=150,width_limit=150)
if len(xx)==0:
if debug:
print("Small track box. Deleting...............")
track.tracker_list.append(track.current_tracker)
track.current_tracker=None
final_box = []
else:
track.current_tracker.no_losses += 1
track.current_tracker.box =xx
final_box = xx
#---------------------
#Person left the frames or not
#If left
#Not left, no detection
#Not active tracker
else:
if debug:
print("No tracked Box ")
#Final box
if track.current_tracker!=None:
if ((track.current_tracker.hits >= min_hits) and (track.current_tracker.no_losses <=max_age)):
# final_box = track.current_tracker.box
if debug:
print('updated box: ', final_box)
print()
if draw:
img= helpers.draw_box_label("Final",img, final_box,show_label=True) # Draw the bounding boxes on the
img= helpers.draw_box_label(track.current_tracker.id,img, track.current_tracker.box,box_color=(255, 255,0),show_label=False) # Draw the bounding boxes on the
elif track.current_tracker.no_losses >max_age:
if debug:
print('Tracker age criteria is not satisfied. Deleting..........')
track.tracker_list.append(track.current_tracker)
track.current_tracker=None
else:
if debug:
print('Tracker zero hit')
if draw:
img= helpers.draw_box_label("Final",img, final_box,show_label=True) # Draw the bounding boxes on the
if debug:
print("Final Box")
print(final_box)
return final_box,img
def main_tracker():
t = tracker.Tracker()
t.run()