OpenCV - 如何找到圆角矩形的矩形轮廓？

Question

我试图在图像中找到具有圆角的矩形对象的轮廓。我尝试 HoughLinesP 和 findContours ，但没有达到预期的结果。

我想找到这样的矩形：

代码：

 import cv2
import matplotlib.pyplot as plt
import util

image = cv2.imread("./img/findrect0.png", 1)
gray = util.grayImage(image)

edges = cv2.Canny(image, 50, 200)
lines = cv2.HoughLinesP(edges, 1, cv2.cv.CV_PI/180, 50, minLineLength=50, maxLineGap=10)[0]
linesImage = image.copy()
util.drawLines(linesImage, lines, thickness=10)

contoursImage = image.copy()
(contours, hierarchy) = cv2.findContours(gray.copy(), cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)

util.drawContours(contoursImage, contours, thickness=10)

util.showOpenCVImagesGrid([image, edges, linesImage, contoursImage], 2, 2, titles=["original image", "canny image", "lines image", "contours image"])

效用：

 import cv2
import math
import matplotlib.pyplot as plt

def showOpenCVImagesGrid(images, x, y, titles=None, axis="on"):
    fig = plt.figure()
    i = 1
    for image in images:
        copy = image.copy()
        channel = len(copy.shape)
        cmap = None
        if channel == 2:
            cmap = "gray"
        elif channel == 3:
            copy = cv2.cvtColor(copy, cv2.COLOR_BGR2RGB)
        elif channel == 4:
            copy = cv2.cvtColor(copy, cv2.COLOR_BGRA2RGBA)

        fig.add_subplot(x, y, i)
        if titles is not None:
            plt.title(titles[i-1])
        plt.axis(axis)
        plt.imshow(copy, cmap=cmap)
        i += 1
    plt.show()

def grayImage(image):
    gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
    return gray

def drawLines(image, lines, thickness=1):
    for line in lines:
        # print("line="+str(line))
        cv2.line(image, (line[0], line[1]), (line[2], line[3]),
                (0, 0, 255), thickness)

def drawContours(image, contours, thickness=1):
    i = 0
    for contour in contours:
        cv2.drawContours(image, [contours[i]], i, (0, 255, 0), thickness)
        area = cv2.contourArea(contour)
        i += 1

我正在使用 Python 2.7.13 和 OpenCV 2.4.13.3 。

我一直在考虑延长这些线并获得线的交点。最后，我将得到矩形的四个坐标。但是如果图像比较复杂，就不知道怎么处理了。

原文由 tomfriwel 发布，翻译遵循 CC BY-SA 4.0 许可协议

Answer 1

您需要找到找到的轮廓的边界矩形。

 img = cv2.imread("image.png", -1)

gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)

binary = cv2.bitwise_not(gray)

(_,contours,_) = cv2.findContours(binary, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_NONE)

for contour in contours:
    (x,y,w,h) = cv2.boundingRect(contour)
    cv2.rectangle(img, (x,y), (x+w,y+h), (0,255,0), 2)

原文由 zindarod 发布，翻译遵循 CC BY-SA 4.0 许可协议

Answer 2

您可以找到非零点的边界矩形。

 image = cv2.imread("./img/findrect0.png", 1)
gray = util.grayImage(image)
gray_inv = cv2.bitwise_not(gray)
points = cv2.findNonZero(gray)
rect = cv2.boundingRect(points)

原文由 Kamil Szelag 发布，翻译遵循 CC BY-SA 3.0 许可协议