python opencv目标外接图形
DanCheng-studio 人气:0当使用cv2.findContours函数找到图像中的目标后,我们通常希望使用一个集合区域将图像包围起来,这里介绍opencv几种几何包围图形。
- 边界矩形
- 最小外接矩形
- 最小外接圆
简介
无论使用哪种几何外接方法,都需要先进行轮廓检测。
当我们得到轮廓对象后,可以使用boundingRect()得到包裹此轮廓的最小正矩形,minAreaRect()得到包裹轮廓的最小矩形(允许矩阵倾斜),minEnclosingCircle()得到包裹此轮廓的最小圆形。
最小正矩形和最小外接矩形的区别如下图所示:
实现
这里给出上述5中外接图形在python opencv上的实现:
①. 边界矩形
import cv2 import numpy as np img = cv2.imread('/home/pzs/图片/test.jpg') gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY) thresh, binary = cv2.threshold(gray, 180, 255, cv2.THRESH_BINARY_INV) binary, contours, hierarchy = cv2.findContours(binary, cv2.RETR_TREE, cv2.CHAIN_APPROX_NONE) cv2.imshow('binary', binary) cv2.waitKey(0) for cnt in contours: x,y,w,h = cv2.boundingRect(cnt) cv2.rectangle(img, (x, y), (x+w, y+h), (0, 255, 0), 1) cv2.imshow('image', img) cv2.waitKey(0)
②. 最小外接矩形
import cv2 import numpy as np img = cv2.imread('/home/pzs/图片/test.jpg') gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY) thresh, binary = cv2.threshold(gray, 180, 255, cv2.THRESH_BINARY_INV) binary, contours, hierarchy = cv2.findContours(binary, cv2.RETR_TREE, cv2.CHAIN_APPROX_NONE) cv2.imshow('binary', binary) cv2.waitKey(0) for cnt in contours: rect = cv2.minAreaRect(cnt) box = cv2.boxPoints(rect) box = np.int0(box) cv2.drawContours(img, [box], 0, (0, 0, 255), 2) cv2.imshow('image', img) cv2.waitKey(0)
③. 最小外接圆
import cv2 import numpy as np img = cv2.imread('/home/pzs/图片/test.jpg') gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY) thresh, binary = cv2.threshold(gray, 180, 255, cv2.THRESH_BINARY_INV) binary, contours, hierarchy = cv2.findContours(binary, cv2.RETR_TREE, cv2.CHAIN_APPROX_NONE) cv2.imshow('binary', binary) cv2.waitKey(0) for cnt in contours: (x, y), radius = cv2.minEnclosingCircle(cnt) center = (int(x), int(y)) radius = int(radius) cv2.circle(img, center, radius, (255, 0, 0), 2) cv2.imshow('image', img) cv2.waitKey(0)
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