如何使用 Python OpenCV 确定内轮廓和外轮廓

据我所知，你试图区分外部轮廓和内部轮廓.要确定哪些轮廓在内外，只需使用轮廓层次来区分两者.具体来说，当使用cv2.findContours时，可以使用cv2.RETR_TREE来提取外部或内部轮廓.完整解释见understanding contour hierarchies: how to distinguish between contours.从我们给出的完整拓Flutter 图中，我们可以过滤出轮廓，其 idea 是，如果父轮廓有内部轮廓，这意味着它是OUT轮廓，内部的子轮廓是IN轮廓.另一种情况是，如果一个轮廓没有内部子对象，那么我们知道它是一个IN轮廓.

以下是一个例子:

输入图像

后果

密码

import cv2

# Load image, grayscale, Otsu's threshold
image = cv2.imread('2.png')
gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
thresh = cv2.threshold(gray, 0, 255, cv2.THRESH_BINARY_INV + cv2.THRESH_OTSU)[1]

# Filter using contour hierarchy
cnts, hierarchy = cv2.findContours(thresh, cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE)[-2:]
hierarchy = hierarchy[0]
for component in zip(cnts, hierarchy):
    currentContour = component[0]
    currentHierarchy = component[1]
    x,y,w,h = cv2.boundingRect(currentContour)
    # Has inner contours which means it is IN
    if currentHierarchy[2] < 0:
        cv2.putText(image, 'IN', (x,y-10), cv2.FONT_HERSHEY_SIMPLEX, 0.7, (36,255,12), 2)
    # No child which means it is OUT
    elif currentHierarchy[3] < 0:
        cv2.putText(image, 'OUT', (x,y-5), cv2.FONT_HERSHEY_SIMPLEX, 0.7, (36,255,12), 2)

cv2.imshow('image', image)
cv2.waitKey()