Widen_boundary/0_dist_between_two_area2.py

61 lines
2.1 KiB
Python

import cv2
import numpy as np
'''
两个区域间最短距离
https://www.lmlphp.com/user/154997/article/item/3778387/
'''
def contours(layer):
gray = cv2.cvtColor(layer, cv2.COLOR_BGR2GRAY)
ret,binary = cv2.threshold(gray, 1,255,cv2.THRESH_BINARY)
contours, hierarchy = cv2.findContours(binary,cv2.RETR_TREE,cv2.CHAIN_APPROX_NONE)
#drawn = cv2.drawContours(image,contours,-1,(150,150,150),3)
return contours #, drawn
def minDistance(contour, contourOther):
distanceMin = 99999999
for xA, yA in contour[0]:
for xB, yB in contourOther[0]:
distance = ((xB-xA)**2+(yB-yA)**2)**(1/2) # distance formula
if (distance < distanceMin):
distanceMin = distance
return distanceMin
def cntDistanceCompare(contoursA, contoursB):
cumMinDistList = []
for contourA in contoursA:
indMinDistList = []
for contourB in contoursB:
minDist = minDistance(contourA,contourB)
indMinDistList.append(minDist)
cumMinDistList.append(indMinDistList)
l = cumMinDistList
return sum(l)/len(l) #returns mean distance
def maskBuilder(bgr,hl,hh,sl,sh,vl,vh):
hsv = cv2.cvtColor(bgr, cv2.COLOR_BGR2HSV)
lower_bound = np.array([hl,sl,vl],dtype=np.uint8)
upper_bound = np.array([hh,sh,vh],dtype=np.uint8)
return cv2.inRange(hsv, lower_bound,upper_bound)
def getContourCenters(contourData):
contourCoordinates = []
for contour in contourData:
moments = cv2.moments(contour)
contourX = int(moments['m10'] / float(moments['m00']))
contourY = int(moments['m01'] / float(moments['m00']))
contourCoordinates += [[contourX, contourY]]
return contourCoordinates
img = cv2.imread('demo/73.png')
maskA=maskBuilder(img, 150,185, 40,220, 65,240)
maskB=maskBuilder(img, 3,20, 50,180, 20,250)
layerA = cv2.bitwise_and(img, img, mask = maskA)
layerB = cv2.bitwise_and(img, img, mask = maskB)
contoursA = contours(layerA)
contoursB = contours(layerB)
print(getContourCenters(contoursA))
print(getContourCenters(contoursB))
#print cntDistanceCompare(contoursA, contoursB)