OpenCV Python：绘制 minAreaRect（未实现 RotatedRect）
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OpenCV Python: Draw minAreaRect ( RotatedRect not implemented)
提问by handle
Are there any helper methods to draw a rotated rectangle that is returned by cv2.minAreaRect()presumably as ((x1,y1),(x2,y2),angle)? cv2.rectangle()does not support an angle.
And since the tuple returned is not of the "RotatedRect" class (because it seems to not be implemented in the Python bindings) there is no points()method, as shown in the C++ tutorial "Creating Bounding rotated boxes and ellipses for contours?".
是否有任何辅助方法可以绘制由cv2.minAreaRect()返回的旋转矩形，大概为((x1,y1),(x2,y2),angle)？cv2.rectangle()不支持角度。并且由于返回的元组不属于“RotatedRect”类（因为它似乎没有在 Python 绑定中实现），因此没有points()方法，如 C++ 教程“为轮廓创建边界旋转框和椭圆？”中所示。.
How could a rotated rectangle be drawn from lines - rotate about the center point or the first point given?
如何从直线绘制旋转的矩形 - 围绕中心点或给定的第一个点旋转？
采纳答案by Tobias Hermann
rect = cv2.minAreaRect(cnt)
box = cv2.cv.BoxPoints(rect) # cv2.boxPoints(rect) for OpenCV 3.x
box = np.int0(box)
cv2.drawContours(im,[box],0,(0,0,255),2)
should do the trick.
应该做的伎俩。
sources:
来源：
1) http://opencvpython.blogspot.in/2012/06/contours-2-brotherhood.html
1) http://opencvpython.blogspot.in/2012/06/contours-2-brotherhood.html
回答by smajtkst
I know this was asked long ago, but I would like to share a different approach as the one proposed by the accepted answer, maybe this could be helpful for someone else (actually this has been done before in C++, but it seems python still lacks of RotatedRectclass).
我知道很久以前就有人问过这个问题，但是我想分享一种与接受的答案提出的方法不同的方法，也许这对其他人有帮助（实际上这已经在 C++ 中完成了，但似乎 python 仍然缺乏的RotatedRect类）。
The idea is to define a rotated rectangle from an angle, a size (W and H) and an initial point. This initial point is the relative top-left corner (the top-left corner of the same size rectangle with no rotation angle). From here, the four vertices can be obtained, which allows us to draw the rotated rectangle with four lines.
这个想法是从一个角度、一个大小（W 和 H）和一个初始点定义一个旋转的矩形。这个初始点是相对的左上角（没有旋转角度的相同大小矩形的左上角）。从这里，可以获得四个顶点，这允许我们用四条线绘制旋转的矩形。
class RRect:
def __init__(self, p0, s, ang):
self.p0 = (int(p0[0]),int(p0[1]))
(self.W, self.H) = s
self.ang = ang
self.p1,self.p2,self.p3 = self.get_verts(p0,s[0],s[1],ang)
self.verts = [self.p0,self.p1,self.p2,self.p3]
def get_verts(self, p0, W, H, ang):
sin = numpy.sin(ang/180*3.14159)
cos = numpy.cos(ang/180*3.14159)
P1 = (int(self.H*sin)+p0[0],int(self.H*cos)+p0[1])
P2 = (int(self.W*cos)+P1[0],int(-self.W*sin)+P1[1])
P3 = (int(self.W*cos)+p0[0],int(-self.W*sin)+p0[1])
return [P1,P2,P3]
def draw(self, image):
print(self.verts)
for i in range(len(self.verts)-1):
cv2.line(image, (self.verts[i][0], self.verts[i][1]), (self.verts[i+1][0],self.verts[i+1][1]), (0,255,0), 2)
cv2.line(image, (self.verts[3][0], self.verts[3][1]), (self.verts[0][0], self.verts[0][1]), (0,255,0), 2)
(W, H) = (30,60)
ang = 35 #degrees
P0 = (50,50)
rr = RRect(P0,(W,H),ang)
rr.draw(image)
cv2.imshow("Text Detection", image)
cv2.waitKey(200)
I guess, a similar approach can be used to define the rotated rectangle in terms of its center instead of its relative top-left initial point, but I haven't tried it yet.
我想，可以使用类似的方法根据其中心而不是其相对左上角的初始点来定义旋转矩形，但我还没有尝试过。
回答by nathancy
Here's a concrete example to draw the rotated rectangle. The idea is to obtain a binary image with Otsu's thresholdthen find contours using cv2.findContours. We can obtain the rotated rectangle using cv2.minAreaRectand the four corner vertices using cv2.boxPoints. To draw the rectangle we can use cv2.drawContoursor cv2.polylines.
这是绘制旋转矩形的具体示例。这个想法是使用Otsu 阈值获得二值图像，然后使用 找到轮廓cv2.findContours。我们可以使用 获得旋转的矩形，使用 获得cv2.minAreaRect四个角顶点cv2.boxPoints。要绘制矩形，我们可以使用cv2.drawContours或cv2.polylines。
Input ->Output
输入->输出
Code
代码
import cv2
import numpy as np
# Load image, convert to grayscale, Otsu's threshold for binary image
image = cv2.imread('1.jpg')
gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
thresh = cv2.threshold(gray, 0, 255, cv2.THRESH_BINARY_INV + cv2.THRESH_OTSU)[1]
# Find contours, find rotated rectangle, obtain four verticies, and draw
cnts = cv2.findContours(thresh, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
cnts = cnts[0] if len(cnts) == 2 else cnts[1]
rect = cv2.minAreaRect(cnts[0])
box = np.int0(cv2.boxPoints(rect))
cv2.drawContours(image, [box], 0, (36,255,12), 3) # OR
# cv2.polylines(image, [box], True, (36,255,12), 3)
cv2.imshow('image', image)
cv2.waitKey()
