108 lines
2.7 KiB
Python
108 lines
2.7 KiB
Python
# -*- coding: UTF-8 -*-
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#!/usr/bin/env python
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# -*- encoding: utf-8 -*-
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'''
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@File : 多边形等距缩放.py
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@data ：2021/7/5 15:53
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@Desciption :
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@Version :
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@License :
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'''
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import cv2
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import numpy as np
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def contours_2_list(data):
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"""将opencv读取的边界numpy数组（3个维度）转化为list（2个维度）
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Args:
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data为数组
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Returns:
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list（2个维度）
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"""
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yyy = data[0]
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# print(yyy)
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list_contours = []
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for i in range(yyy.shape[0]):
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list_contours.append([yyy[i][0][0], yyy[i][0][1]])
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return list_contours
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def scale(data, sec_dis):
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"""多边形等距缩放
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Args:
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data: 多边形按照逆时针顺序排列的的点集
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sec_dis: 缩放距离
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Returns:
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缩放后的多边形点集
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"""
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num = len(data)
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scal_data = []
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for i in range(num):
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x1 = data[(i) % num][0] - data[(i - 1) % num][0]
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y1 = data[(i) % num][1] - data[(i - 1) % num][1]
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x2 = data[(i + 1) % num][0] - data[(i) % num][0]
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y2 = data[(i + 1) % num][1] - data[(i) % num][1]
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d_A = (x1 ** 2 + y1 ** 2) ** 0.5
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d_B = (x2 ** 2 + y2 ** 2) ** 0.5
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Vec_Cross = (x1 * y2) - (x2 * y1)
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if (d_A * d_B==0):
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continue
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sin_theta = Vec_Cross / (d_A * d_B)
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if (sin_theta==0):
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continue
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dv = sec_dis / sin_theta
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v1_x = (dv / d_A) * x1
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v1_y = (dv / d_A) * y1
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v2_x = (dv / d_B) * x2
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v2_y = (dv / d_B) * y2
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PQ_x = v1_x - v2_x
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PQ_y = v1_y - v2_y
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Q_x = data[(i) % num][0] + PQ_x
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Q_y = data[(i) % num][1] + PQ_y
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scal_data.append([Q_x, Q_y])
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return scal_data
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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('image/171.jpg')
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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
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contours, hierarchy = cv2.findContours(thresh, cv2.RETR_LIST, 2)
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list_contours=contours_2_list(contours)
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# for i in range(yyy.shape[0]):
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# list_contours.append([yyy[i][0][0],yyy[i][0][1]])
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data=list_contours
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data1 = scale(data,-150)
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print(data1)
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# temp = np.ones((img_gray.shape[0],img_gray.shape[1],3), np.uint8) * 255
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temp = np.zeros((img_gray.shape[0],img_gray.shape[1],3), np.uint8) * 255
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# cv2.polylines(temp, data1, 1, 255)
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cv2.polylines(temp,[np.array(data1, dtype=np.int32)],True, (255, 0, 0), 5)
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# cv2.polylines(temp , [np.array(data1 , dtype=np.int32)], True, (0, 0, 255), 1)
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cv2.namedWindow("boundary",cv2.WINDOW_NORMAL);
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cv2.resizeWindow("boundary", 640, 480);
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cv2.imshow("boundary",temp)
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# cv2.imshow ("img",temp)
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cv2.imwrite("1.jpg",temp)
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cv2.waitKey(0)
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