opencv 图片旋转缩小透视变换和透视变换后坐标计算

旋转后图片完整显示：

def Rotate(pimg):
    angle = 45   w,h = pimg.size
    centerx = w / 2  centery = h / 2  w = w - 1  h = h - 1   x = 0  y = 0   x1 = x
    y1 = y
    x1t= int((x1 - centerx)*math.cos(angle) - (y1 - centery)*math.sin(angle) + centerx)
    y1t= int((x1 - centerx)*math.sin(angle) + (y1 - centery)*math.cos(angle) + centery)

    x2 = w
    y2 = 0  x2t= int((x2 - centerx)*math.cos(angle) - (y2 - centery)*math.sin(angle) + centerx)
    y2t= int((x2 - centerx)*math.sin(angle) + (y2 - centery)*math.cos(angle) + centery)

    x3 = 0  y3 = h
    x3t= int((x3 - centerx)*math.cos(angle) - (y3 - centery)*math.sin(angle) + centerx)
    y3t= int((x3 - centerx)*math.sin(angle) + (y3 - centery)*math.cos(angle) + centery)

    x4 = w
    y4 = h
    x4t= int((x4 - centerx)*math.cos(angle) - (y4 - centery)*math.sin(angle) + centerx)
    y4t= int((x4 - centerx)*math.sin(angle) + (y4 - centery)*math.cos(angle) + centery)


    minx = min(x1t, x2t, x3t, x4t)
    maxw = max(x1t, x2t, x3t, x4t)
    nw = maxw - (minx)

    miny = min(y1t, y2t, y3t, y4t)
    maxh = max(y1t, y2t, y3t, y4t)
    nh = maxh - (miny)

    pts1 = np.float32([[x1, y1], [x2, y2], [x3, y3], [x4, y4]])
    pts2 = np.float32(
        [[x1t - (minx), y1t - (miny)], [x2t - (minx), y2t - (miny)], [x3t - (minx), y3t - (miny)],  [x4t - (minx), y4t - (miny)]])

    M_rotate = cv2.getPerspectiveTransform(pts1, pts2)
    array = np.array(pimg)

    dst = cv2.warpPerspective(array, M_rotate, (nw, nh), flags=cv.CV_WARP_FILL_OUTLIERS+cv.CV_INTER_AREA)
    img = Image.fromarray(dst).convert("RGBA") return img

图片在(centerx,centery)旋转angle度后原图片的(x,y)点在新图上的(x1,y1)的计算：
    计算公式：      

x1=int((x1 - centerx)*math.cos(angle) - (y1 - centery)*math.sin(angle) + centerx) + (offsetX)
y1=int((x1 - centerx)*math.sin(angle) + (y1 - centery)*math.cos(angle) + centery) + (offsetY)

透视变换：

M = cv2.getPerspectiveTransform(pts1, pts2) 

dst = cv2.warpPerspective(array, M, (nw, nh), flags=cv.CV_WARP_FILL_OUTLIERS+cv.CV_INTER_AREA)

原图(x,y)透视变换后在新图上的坐标：

a = np.array([[x, y]], dtype='float32')
a = np.array([a])

dst = cv2.perspectiveTransform(a, M)
xy = dst[0][0].astype('int')