opencv python中两条等高线之间的中间线?
我有一个形象 在我的代码运行之后 新形象是 我需要像这样找出他们之间的界限 我该怎么办 我的代码opencv python中两条等高线之间的中间线?,python,opencv,contour,Python,Opencv,Contour,我有一个形象 在我的代码运行之后 新形象是 我需要像这样找出他们之间的界限 我该怎么办 我的代码 import numpy as np import cv2 import cv2 as cv ima = cv2.imread('track1.pNg') imgray = cv2.cvtColor(ima,cv2.COLOR_BGR2GRAY) im = cv2.cvtColor(ima,cv2.COLOR_BGR2GRAY) imm = cv2.inRange(im,(0),
import numpy as np
import cv2
import cv2 as cv
ima = cv2.imread('track1.pNg')
imgray = cv2.cvtColor(ima,cv2.COLOR_BGR2GRAY)
im = cv2.cvtColor(ima,cv2.COLOR_BGR2GRAY)
imm = cv2.inRange(im,(0),(49))
kernel = np.ones((5,5),np.uint8)
gradient = cv2.morphologyEx(imm, cv2.MORPH_GRADIENT, kernel)
il = cv2.dilate(gradient, kernel, iterations=7)
ol = cv2.erode(il, kernel, iterations=7)
contours,hei = cv2.findContours(ol,cv2.RETR_TREE,cv2.CHAIN_APPROX_SIMPLE)
img = cv2.drawContours(ima, contours, -1, (200,255,0), 3)
cv2.imshow('window',ima)
如何实现这一点?此答案解释了如何找到形状两侧之间的直线。可以通过迭代腐蚀图像找到中心 结果是: 这是我使用的代码:
import cv2
import numpy as np
img = 255-cv2.imread('/home/stephen/Desktop/PITqe.png',0)
kernel = np.ones((20,20), np.uint8)
img = cv2.erode(img, kernel, iterations=2)
size = np.size(img)
skel = np.zeros(img.shape,np.uint8)
ret,img = cv2.threshold(img,127,255,0)
element = cv2.getStructuringElement(cv2.MORPH_CROSS,(3,3))
done = False
while( not done):
eroded = cv2.erode(img,element)
temp = cv2.dilate(eroded,element)
temp = cv2.subtract(img,temp)
skel = cv2.bitwise_or(skel,temp)
img = eroded.copy()
zeros = size - cv2.countNonZero(img)
cv2.imshow('img', img)
cv2.waitKey(100)
if zeros==size:
done = True
cv2.imshow("img",skel)
cv2.waitKey(0)
cv2.destroyAllWindows()
这里是另一种在OpenCV中使用距离变换和top hat形态学进行骨骼化(无需显式迭代)的方法 输入:
import cv2
import numpy as np
# read image and invert so blob is white on black background
img = 255-cv2.imread('tall_blob.png',0)
# do some eroding of img, but not too much
kernel = np.ones((20,20), np.uint8)
img = cv2.erode(img, kernel, iterations=2)
# threshold img
ret, thresh = cv2.threshold(img,127,255,0)
# do distance transform
dist = cv2.distanceTransform(thresh, distanceType=cv2.DIST_L2, maskSize=5)
# set up cross for tophat skeletonization
kernel = cv2.getStructuringElement(cv2.MORPH_CROSS,(3,3))
skeleton = cv2.morphologyEx(dist, cv2.MORPH_TOPHAT, kernel)
# threshold skeleton
ret, skeleton = cv2.threshold(skeleton,0,255,0)
# display skeleton
cv2.imshow("skeleton",skeleton)
cv2.waitKey(0)
cv2.destroyAllWindows()
# save results
cv2.imwrite('tall_blob_skeleton.png', skeleton)