基於Opencv的多目標跟蹤

python實現：

import cv2

import sys
(major_ver, minor_ver, subminor_ver)
=(cv2.__version__)
.split(
'.')
print
(major_ver, minor_ver, subminor_ver)
if __name__ ==
'__main__'
:# 建立***
# 'boosting', 'mil','kcf', 'tld', 'medianflow', 'goturn', 'mosse'
tracker_type =
'mil'
tracker = cv2.multitracker_create(
)#獲得追蹤的初始化結果
# 建立視窗
cv2.namedwindow(
"tracking"
)#給視窗命名
video = cv2.videocapture(
"./pig/001.mp4"
)# 讀入第一幀
ok, frame = video.read()if
not ok:
print()
sys.exit(
)# 定義乙個bounding box
#多目標跟蹤，這裡定義3個box
box1 = cv2.selectroi(
"tracking"
, frame)
#在第一幀上進行選框操作
box2 = cv2.selectroi(
"tracking"
, frame)
box3 = cv2.selectroi(
"tracking"
, frame)
# 用第一幀初始化
ok = tracker.add(cv2.trackermil_create(
), frame, box1)
ok1 = tracker.add(cv2.trackermil_create(
), frame, box2)
ok2 = tracker.add(cv2.trackermil_create(
), frame, box3)
while
true
: ok, frame = video.read()if
not ok:
break
# 計時
timer = cv2.gettickcount(
)# 更新追蹤器tracker
ok, boxes = tracker.update(frame)
print
(ok, boxes)
# 計算fps
fps = cv2.gettickfrequency()/
(cv2.gettickcount(
)- timer)
for box in boxes:
# 畫bonding box
if ok:
p1 =
(int
(box[0]
),int(box[1]
))p2 =
(int
(box[0]
+ box[2]
),int(box[1]
+ box[3]
))cv2.rectangle(frame, p1, p2,
(255,0
,0),
2,1)
else
: cv2.puttext(frame,
"tracking failed detected",(
100,80)
, cv2.font_hershey_******x,
0.75,(
0,0,
255),2
)# 展示tracker型別
cv2.puttext(frame, tracker_type+
"tracker",(
100,20)
, cv2.font_hershey_******x,
0.75,(
50,170,50)
,2)# 展示fps
cv2.puttext(frame,
"fps:"
+str
(fps),(
100,50)
, cv2.font_hershey_******x,
0.75,(
50,170,50)
,2)# result
cv2.imshow(
"tracking"
, frame)
# exit
k = cv2.waitkey(1)
&0xff
if k ==27:
break

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