我正在使用两个 Windows 操作系统测试以下代码，一个在 64 位上，一个在 32 位上。两台机器都安装了 Python 2.7 和来自 Unofficial Windows Binaries for Python Extension Packages 的 openCV
opencv-python-2.4.3.win32-py2.7.exe = 32 bit
opencv-python-2.4.3.win-amd64-py2.7.exe = 64 bit
在64位中拟合椭圆的结果是
(center, size, angle)
((560030.1875, 6362089.0), (21.186540603637695, 56.54529571533203), 176.27346801757812)
在32位中拟合椭圆的结果是
(center, size, angle)
((560030.625, 6362066.5), (10.480490684509277, 17.20206642150879), 144.34889221191406)
我用于测试的代码如下:
import numpy as np
import cv
points = [(560036.4495758876, 6362071.890493258),
(560036.4495758876, 6362070.890493258),
(560036.9495758876, 6362070.890493258),
(560036.9495758876, 6362070.390493258),
(560037.4495758876, 6362070.390493258),
(560037.4495758876, 6362064.890493258),
(560036.4495758876, 6362064.890493258),
(560036.4495758876, 6362063.390493258),
(560035.4495758876, 6362063.390493258),
(560035.4495758876, 6362062.390493258),
(560034.9495758876, 6362062.390493258),
(560034.9495758876, 6362061.390493258),
(560032.9495758876, 6362061.390493258),
(560032.9495758876, 6362061.890493258),
(560030.4495758876, 6362061.890493258),
(560030.4495758876, 6362061.390493258),
(560029.9495758876, 6362061.390493258),
(560029.9495758876, 6362060.390493258),
(560029.4495758876, 6362060.390493258),
(560029.4495758876, 6362059.890493258),
(560028.9495758876, 6362059.890493258),
(560028.9495758876, 6362059.390493258),
(560028.4495758876, 6362059.390493258),
(560028.4495758876, 6362058.890493258),
(560027.4495758876, 6362058.890493258),
(560027.4495758876, 6362058.390493258),
(560026.9495758876, 6362058.390493258),
(560026.9495758876, 6362057.890493258),
(560025.4495758876, 6362057.890493258),
(560025.4495758876, 6362057.390493258),
(560023.4495758876, 6362057.390493258),
(560023.4495758876, 6362060.390493258),
(560023.9495758876, 6362060.390493258),
(560023.9495758876, 6362061.890493258),
(560024.4495758876, 6362061.890493258),
(560024.4495758876, 6362063.390493258),
(560024.9495758876, 6362063.390493258),
(560024.9495758876, 6362064.390493258),
(560025.4495758876, 6362064.390493258),
(560025.4495758876, 6362065.390493258),
(560025.9495758876, 6362065.390493258),
(560025.9495758876, 6362065.890493258),
(560026.4495758876, 6362065.890493258),
(560026.4495758876, 6362066.890493258),
(560026.9495758876, 6362066.890493258),
(560026.9495758876, 6362068.390493258),
(560027.4495758876, 6362068.390493258),
(560027.4495758876, 6362068.890493258),
(560027.9495758876, 6362068.890493258),
(560027.9495758876, 6362069.390493258),
(560028.4495758876, 6362069.390493258),
(560028.4495758876, 6362069.890493258),
(560033.4495758876, 6362069.890493258),
(560033.4495758876, 6362070.390493258),
(560033.9495758876, 6362070.390493258),
(560033.9495758876, 6362070.890493258),
(560034.4495758876, 6362070.890493258),
(560034.4495758876, 6362071.390493258),
(560034.9495758876, 6362071.390493258),
(560034.9495758876, 6362071.890493258),
(560036.4495758876, 6362071.890493258)]
x = np.array(points)[:,0]
y = np.array(points)[:,1]
PointArray2D32f = cv.CreateMat(1, len(points), cv.CV_32FC2)
for (i, (x, y)) in enumerate(points):
PointArray2D32f[0, i] = (x, y)
# Fits ellipse to current contour.
(center, size, angle) = cv.FitEllipse2(PointArray2D32f)
print (center, size, angle)
最佳答案
拟合椭圆通常是通过随机过程完成的，因为有很多自由度。您可能会看到不同的结果，因为算法根本不是确定性的。
OpenCV 用于拟合椭圆的算法是 Randomized Hough Transform .
关于Python 2.7 和 OpenCV 使用 64 位和 32 位的不同结果，可能的错误？，我们在Stack Overflow上找到一个类似的问题： https://stackoverflow.com/questions/13646267/