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最新推荐文章于 2024-04-22 16:59:44 发布

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本文介绍了一种使用Python版本的OpenCV通过Trackbar来调整HSV颜色空间阈值的方法，以便于实时调节图像处理参数。

python opencv trackbar 调整参数

由于最近需要利用到Python 版本的opencv 但是之前又没有接触过这个，在此纪念下利用 trackbar 去调整参数的方法。

mport cv2
import numpy as np
#optional argument
def nothing(x):
    pass

cv2.namedWindow('image')

#easy assigments
hh='Hue High'
hl='Hue Low'
sh='Saturation High'
sl='Saturation Low'
vh='Value High'
vl='Value Low'

cv2.createTrackbar(hl, 'image',0,179,nothing)
cv2.createTrackbar(hh, 'image',0,179,nothing)
cv2.createTrackbar(sl, 'image',0,255,nothing)
cv2.createTrackbar(sh, 'image',0,255,nothing)
cv2.createTrackbar(vl, 'image',0,255,nothing)
cv2.createTrackbar(vh, 'image',0,255,nothing)

while(1):

    frame = cv2.imread("55.png")
    frame=cv2.GaussianBlur(frame,(5,5),0)
    #convert to HSV from BGR
    hsv=cv2.cvtColor(frame, cv2.COLOR_BGR2HSV)


    #read trackbar positions for all
    hul=cv2.getTrackbarPos(hl, 'image')
    huh=cv2.getTrackbarPos(hh, 'image')
    sal=cv2.getTrackbarPos(sl, 'image')
    sah=cv2.getTrackbarPos(sh, 'image')
    val=cv2.getTrackbarPos(vl, 'image')
    vah=cv2.getTrackbarPos(vh, 'image')

    print "hul is :",hul
    print "huh is :",huh
    print "sal is:",sal
    print "sah is:",sah
    print "val is:",val
    print "vah is:",vah

    #make array for final values
    HSVLOW=np.array([hul,sal,val])
    HSVHIGH=np.array([huh,sah,vah])

    #apply the range on a mask
    mask = cv2.inRange(hsv,HSVLOW, HSVHIGH)
    res = cv2.bitwise_and(frame,frame, mask =mask)

    cv2.imshow('mask',mask)
    cv2.imshow('dst', res)
    cv2.imshow('yay', frame)

    k = cv2.waitKey(5) & 0xFF
    if k == 27:
        break


cv2.destroyAllWindows()