边界框最小矩形区域和最小闭圆的轮廓:
找到一个正方形轮廓很简单 找不规则的歪斜的以及旋转的形状可用 OpencV 的 cv2.findContours 函数
- import cv2
- import numpy as np
- img = cv2.pyrDown(cv2.imread("hammer.jpg", cv2.IMREAD_UNCHANGED))
- ret, thresh = cv2.threshold(cv2.cvtColor(img.copy(), cv2.COLOR_BGR2GRAY) , 127, 255, cv2.THRESH_BINARY)
- image, contours, hier = cv2.findContours(thresh, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
- for c in contours:
- # find bounding box coordinates
- x,y,w,h = cv2.boundingRect(c)
- cv2.rectangle(img, (x,y), (x+w, y+h), (0, 255, 0), 2)
- # find minimum area
- rect = cv2.minAreaRect(c)
- # calculate coordinates of the minimum area rectangle
- box = cv2.boxPoints(rect)
- # normalize coordinates to integers
- box = np.int0(box)
- # draw contours
- cv2.drawContours(img, [box], 0, (0,0, 255), 3)
- # calculate center and radius of minimum enclosing circle
- (x,y),radius = cv2.minEnclosingCircle(c)
- # cast to integers
- center = (int(x),int(y))
- radius = int(radius)
- # draw the circle
- img = cv2.circle(img,center,radius,(0,255,0),2)
- cv2.drawContours(img, contours, -1, (255, 0, 0), 1)
- cv2.imshow("contours", img)
- cv2.waitKey()
- cv2.destroyAllWindows()
结果:
加载图片后先进行阈值处理, 由于原图为黑白图片所以阈值较为简单
计算简单的边界框:
x,y,w,h=cv2.boundingRect(c)
转化为框的坐标及宽度, 再画出框:
cv.rectangle(img,(x,y),(x+w,y+h),(0,255,0),2)
第二步计算出包围最小的矩形区域
- rect = cv2.minAreaRect(c)
- # calculate coordinates of the minimum area rectangle
- box = cv2.boxPoints(rect)
- # normalize coordinates to integers
- box = np.int0(box)
注意计算所得的顶点坐标为浮点型的, 像素坐标必须为整数, 所以必须做一个转换, 然后画出这个矩形, 可以用 cv2.drawContours 函数来:
cv2.drawContours(img,[box],0,(0,0,255),3)
该函数的第二个参数接收一个保存着轮廓的数组, 从而可以在一次操作中绘制一系列轮廓第三个参数为所要绘制的轮廓的索引,-1 为绘制所有的轮廓, 否则只会绘制轮廓组中指定的轮廓
最后检查的边界轮廓为最小闭圆:
- (x,y),radius = cv2.minEnclosingCircle(c)
- # cast to integers
- center = (int(x),int(y))
- radius = int(radius)
cv2.minEnclosingCircle 函数会返回一个二元组, 第一个元素为圆心坐标组成的元组, 第二个元素为圆的半径值
来源: http://click.aliyun.com/m/42875/