opencv 无损旋转后 坐标不知如何重新计算回来

如题，已有某个矩形坐标，无损旋转后，坐标不知道如何计算回来。
如下代码 希望sub_image2函数能重新标回坐标

# -*- coding: utf-8 -*-
import cv2, numpy as np
def sub_image(image, rect):
    shape = image.shape[1::-1]
    center = rect[0]
    width, height = rect[1]
    angle = rect[2]
    if width < height:
       width, height = rect[1][::-1]
       angle = 90 + angle
    matrix = cv2.getRotationMatrix2D(center=center, angle=angle, scale=1)
    image = cv2.warpAffine(src=image, M=matrix, dsize=shape)
    x = center[0] - width / 2
    y = center[1] - height / 2
    cv2.rectangle(image, (int(x), int(y)), (int(x + width), int(y + height)), (0, 0, 255), 2)
    cv2.imshow('有损的', image)
    cv2.waitKey()
    cv2.destroyAllWindows()
def sub_image2(image, rect):
    center = rect[0]
    width, height = rect[1]
    angle = rect[2]
    w, h = image.shape[1::-1]
    cX, cY = w // 2, h // 2
    if width < height:
       width, height = rect[1][::-1]
       angle = 90 + angle
    matrix = cv2.getRotationMatrix2D(center=(cX, cY), angle=angle, scale=1)
    cos = np.abs(matrix[0, 0])
    sin = np.abs(matrix[0, 1])
    # compute the new bounding dimensions of the image
    nW = int((h * sin) + (w * cos))
    nH = int((h * cos) + (w * sin))
    # adjust the rotation matrix to take into account translation
    matrix[0, 2] += (nW / 2) - cX
    matrix[1, 2] += (nH / 2) - cY
    image = cv2.warpAffine(src=image, M=matrix, dsize=(nW, nH))
    x = center[0] - width / 2  #值要是270 才能匹配上
    y = center[1] - height / 2  #值要是604  才能匹配上
    cv2.rectangle(image, (int(x), int(y)), (int(x + width), int(y + height)), (0, 0, 255), 2)
    cv2.imshow('无损的', image)
    cv2.waitKey()
    cv2.destroyAllWindows()
path = "C:\\Users\\sa\\Desktop\\car_img\\1\\4662975.jpg"   #记得不要有中文路径
sky = cv2.imread(path)
sub_image(sky, ((255.9073944091797, 512.5665893554688), (52.486114501953125, 129.72068786621094), -80.71644592285156))
sub_image2(sky, ((255.9073944091797, 512.5665893554688), (52.486114501953125, 129.72068786621094), -80.71644592285156))

4662975.jpg
opencv 无损旋转后 坐标不知如何重新计算回来

回答：

加一行代码就解决了

center = np.dot(matrix, list(center) + [1]) #旋转后重新计算矩形中心坐标

def sub_image2(image, rect):
    center = rect[0]
    width, height = rect[1]
    angle = rect[2]
    w, h = image.shape[1::-1]
    cX, cY = w // 2, h // 2
    if width < height:
       width, height = rect[1][::-1]
       angle = 90 + angle
    matrix = cv2.getRotationMatrix2D(center=(cX, cY), angle=angle, scale=1)
    cos = np.abs(matrix[0, 0])
    sin = np.abs(matrix[0, 1])
    # compute the new bounding dimensions of the image
    nW = int((h * sin) + (w * cos))
    nH = int((h * cos) + (w * sin))
    # adjust the rotation matrix to take into account translation
    matrix[0, 2] += (nW / 2) - cX
    matrix[1, 2] += (nH / 2) - cY
    image = cv2.warpAffine(src=image, M=matrix, dsize=(nW, nH))
    center = np.dot(matrix, list(center) + [1]) #旋转后重新计算矩形中心坐标
    x = center[0] - width / 2  #值要是270 才能匹配上
    y = center[1] - height / 2  #值要是604  才能匹配上
    cv2.rectangle(image, (int(x), int(y)), (int(x + width), int(y + height)), (0, 0, 255), 2)
    cv2.imshow('无损的', image)
    cv2.waitKey()
    cv2.destroyAllWindows()

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