# 实现图像从圆形到矩形的转变，需要用到opencv中的cv.ploarToCart
#cv.polarToCart(magnitude, angle, x=None, y=None, angleInDegrees=None)
#返回x, y（笛卡尔坐标的x, y）
#-*-coding:utf-8-*-
import cv2 as cv
import numpy as np
def polar(I,center,r,theta=(90,450),rstep=1.0,thetastep = 360.0/(180*8)):
# 图像灰度处理
gray= cv.cvtColor(I, cv.COLOR_BGR2GRAY)
# 得到距离的最小、最大范围
minr, maxr= r
# 角度的最小范围
mintheta, maxtheta= theta
# 输出图像的高、宽
H= int((maxr-minr)/rstep)+1
W= int((maxtheta-mintheta)/thetastep)+1
O= 125 * np.ones((H, W), gray.dtype)
# 极坐标变换
r= np.linspace(minr, maxr, H)
r= np.tile(r, (W,1))
r= np.transpose(r)
theta= np.linspace(mintheta, maxtheta, W)
theta= np.tile(theta, (H,1))
x, y= cv.polarToCart(r,theta,angleInDegrees=True)
# 最近邻插值
for iin range(H):
for jin range(W):
px= int(round(x[i][j])+ cx)
py= int(round(y[i][j])+ cy)
if((px>= 0 and px<=w-1)and (py>=0 and py<=h-1)):
O[i][j]= gray[py][px]
return O
if __name__== "__main__":
print("---------------Hello python ------------")
filename= ("polar.jpg")
src= cv.imread(filename)
# cv.namedWindow("input image", cv.WINDOW_AUTOSIZE)
# cv.imshow("input image", src)
# 图像的宽、高
h, w= src.shape[:2]
# 极坐标中心
cx, cy= w/2, h/2
# 标出图像中心点
cv.circle(src, (int(cx),int(cy)),10, (255,0.0,0),3)
O= polar(src, (cx, cy), (50,400))
# 旋转
O= cv.flip(O,0)
O1= cv.cvtColor(O, cv.COLOR_GRAY2BGR)
cv.imshow("src", src)
cv.imshow("O", O)
cv.imshow("O1", O1)
cv.waitKey(0)
cv.destroyAllWindows()
