67 lines
1.5 KiB
Python
67 lines
1.5 KiB
Python
# -*- coding: UTF-8 -*-
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import cv2
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import time
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import numpy as np
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import skimage.exposure
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'''
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两个区域间最短距离
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https://www.cnpython.com/qa/1329750
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'''
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import math
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def downsample(num_arr,downsample_rate):
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'''
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下采样数组，隔着downsample_rate个数取一个值
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num_arr为数组
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downsample_rate为采用概率，为1-n的正整数
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'''
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num_arr_temp=[]
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for i in range(len(num_arr)//downsample_rate-1):
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num_arr_temp.append(num_arr[i*downsample_rate])
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return num_arr_temp
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# 中间输入的代码
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# 将数组存在num_arr1和num_arr2中
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t1=time.time()
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# 1.读入图片
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# img = cv2.imread('demo/171.png')
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img = cv2.imread('demo/9.png')
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t2=time.time()
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img_gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
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contours, thresh = cv2.threshold(img_gray, 0, 255, cv2.THRESH_BINARY + cv2.THRESH_OTSU)
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# 2.寻找轮廓(多边界)
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contours, hierarchy = cv2.findContours(thresh, cv2.RETR_LIST, 2)
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# 3.轮廓数组转为列表(多边界)
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list_contours=[]
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record=[]
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num_arr1=contours[0]
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num_arr2=contours[1]
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# 3.对边界进行下采样，减小点数量。
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num_arr11=downsample(num_arr1,10) #下采样边界点
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num_arr22=downsample(num_arr2,10) #下采样边界点
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print(num_arr1)
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t3=time.time()
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for i in num_arr11:
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for j in num_arr22:
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# record.append(abs(i[0] - j[0]))
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record.append(math.sqrt((i[0][0] - j[0][0]) ** 2 +(i[0][1] - j[0][1]) ** 2 ) )
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print('两区域最小距离',min(record))
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t4=time.time()
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print('读图时间:%s 找边界时间:%s 区域最短距离计算时间:%s'%(t2-t1,t3-t2,t4-t3))
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