def correlation_tracker(self):
flag = time.time()
for track in self.tracks:
if track.source == 'tracking':
if track.updated:
print '===!!!==='
print 'Track updated!!!'
# use .start_tracking method
track.tracker.start_track(self.img, \
dlib.rectangle(*track.updatebox))
track.updated = False
else:
# use .update method
track.tracker.update(self.img)
rect = track.tracker.get_position()
track.bbox = [int(rect.left()),\
int(rect.top()), \
int(rect.right()),\
int(rect.bottom())]
print 'Track one frame', time.time()-flag
else:
# do nothing
pass
python类correlation_tracker()的实例源码
def timer(self):
"""docstring for timer"""
if self.RUN:
# print 'New Frame', self.idx
flag = time.time()
self.readIMG() # read new frame
self.correlation_tracker() # update correlation_tracker(s)
# self.display() # display img and boxes
self.checkState()
self.singleLog()
# self.log()
time_consumed = time.time() - flag
if time_consumed > 0.04:
print 'Time > 40 ms!'
Timer(0, self.timer).start() # excuted instantly
else:
Timer(0.04 - time_consumed, self.timer).start() # excute this function every 40 ms
return
def correlation_tracker(self):
"""docstring for correlation_tracker"""
for track in self.tracks:
if track.USE_CT:
assert self.img != None
assert self.img_old != None
track.CT_run(self.img, self.img_old, self.img_last) # update tracks
return
def __init__(self):
self.t=dlib.correlation_tracker()
def __init__(self,bbox,img):
self.tracker = correlation_tracker()
self.tracker.start_track(img,rectangle(long(bbox[0]),long(bbox[1]),long(bbox[2]),long(bbox[3])))
self.confidence = 0. # measures how confident the tracker is! (a.k.a. correlation score)
self.time_since_update = 0
self.id = CorrelationTracker.count
CorrelationTracker.count += 1
self.hits = 0
self.hit_streak = 0
self.age = 0
def initTracker(self):
return dlib.correlation_tracker()
def timer(self):
if self.idx < 100:
self.idx += 1
self.oldimg = self.img
# print imdb_path+'/%04d'%self.idx
self.img = cv2.imread(imdb_path+'/%04d.jpg'%self.idx)
assert self.img != None
# print self.idx
self.correlation_tracker()
Timer(0.04, self.timer).start()
def createNewTracks(self, unassignedDetections, detection):
global tracker_id
print detection
print unassignedDetections
bboxes = detection[unassignedDetections,:]
n = bboxes.shape[0]
for i in xrange(n):
bbox = bboxes[i,:].tolist()
track = Track(tracker_id, bbox, dlib.correlation_tracker())
tracker_id += 1
self.tracks.append(track)
# delete below!!!
def _CT_init(self):
CT = dlib.correlation_tracker()
return CT
def correlation_tracker(self):
"""docstring for correlation_tracker"""
for track in self.tracks:
if track.USE_CT:
assert self.img != None
assert self.img_old != None
track.CT_run(self.img, self.img_old) # update tracks
return
def _CT_init(self):
CT = dlib.correlation_tracker()
return CT
def correlation_tracker(self):
"""docstring for correlation_tracker"""
for track in self.tracks:
if track.USE_CT:
assert self.img != None
assert self.img_old != None
track.CT_run(self.img, self.img_old) # update tracks
return
def _CT_init(self):
CT = dlib.correlation_tracker()
return CT
def correlation_tracker(self):
"""docstring for correlation_tracker"""
for track in self.tracks:
if track.USE_CT:
assert self.img != None
assert self.img_old != None
track.CT_run(self.img, self.img_old) # update tracks
return
def _CT_init(self):
CT = dlib.correlation_tracker()
return CT
def timer(self):
"""docstring for timer"""
if self.RUN:
# print 'New Frame', self.idx
flag = time.time()
self.readIMG() # read new frame
self.correlation_tracker() # update correlation_tracker(s)
# self.display() # display img and boxes
self.checkState()
self.singleLog()
# self.log()
time_consumed = time.time() - flag
if time_consumed > 0.04:
print 'Time > 40 ms!'
Timer(0, self.timer).start() # excuted instantly
else:
Timer(0.04 - time_consumed, self.timer).start() # excute this function every 40 ms
return
# def buildLogPath(self):
# if not os.path.exists(self.logPath):
# os.makedirs(self.logPath)
# print 'Path Build', self.logPath
