import cv2
import numpy as np
''''''
tracker = cv2.trackerkcf_create()
video = cv2.videocapture(0)
kernel = cv2.getstructuringelement(cv2.morph_rect, (3, 3))
''''''
def roi_select(frame,):
# 將影象轉換到 hsv 空間
hsv = cv2.cvtcolor(frame, cv2.color_bgr2hsv)
# 設定 hsv 閾值到藍色範圍。
lower_blue = np.array([0, 80, 50]) # 最低
upper_blue = np.array([0, 255, 255]) # 最高
# 設定閾值影象中只出現藍色範圍的物件
mask = cv2.inrange(hsv, lower_blue, upper_blue)
mask2 = cv2.morphologyex(mask, cv2.morph_open, kernel)
mask3 = cv2.morphologyex(mask2, cv2.morph_close, kernel)
#res = cv2.bitwise_and(frame, frame, mask=mask3) # 這個是彩圖
maxarea = 0
maxindex = 0
for i, c in enumerate(contours):
area = cv2.contourarea(c)
if area > maxarea:
maxarea = area
maxindex = i
# cv2.drawcontours(frame1, contours, maxindex, (0, 0, 255), 3)
'''''' # 獲取外切矩形
if len(contours):
x, y, w, h = cv2.boundingrect(contours[maxindex])
cv2.rectangle(frame, (x, y), (x + w, y + h), (255, 0, 0), 2)
# 獲取中心畫素點
center_x = int(x + w / 2)
center_y = int(y + h / 2)
cv2.circle(frame, (center_x, center_y), 5, (0, 0, 255), -1)
return (x,y,w,h)
while true:
k,frame = video.read()
cv2.imshow("tracking",frame)
k = cv2.waitkey(30) & 0xff
if k == 27:
break
bbox = roi_select(frame)
'''第乙個值為矩形框中最小的x值 -列
第二個值為矩形框中最小的y值 —行
第三個值為這個矩形框的寬 -列
第四個值為這個矩形框的高 -行
'''ok = tracker.init(frame, bbox)
#cv2.destroywindow("roi selector")
while
true
: ok, frame = video.read(
) ok, bbox = tracker.update(frame)
if ok:
p1 =
(int
(bbox[0]
),int(bbox[1]
))p2 =
(int
(bbox[0]
+ bbox[2]
),int(bbox[1]
+ bbox[3]
))cv2.rectangle(frame, p1, p2,(0
,0,255),
2,2)
cv2.puttext(frame,
'kcf'
,(bbox[0]
,bbox[1]
-5),cv2.font_hershey_******x,
0.75,(
50,170,50)
,2) cv2.imshow(
"tracking"
, frame)
k = cv2.waitkey(1)
&0xff
if k ==27:
break
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