def get_laplacian_pyramid_layer(img, n):
    gi = img
    for i in range(n):
        gi_prev = gi
        gi = cv2.pyrDown(gi_prev)
    pyrup = cv2.pyrUp(gi)
    return cv2.addWeighted(gi_prev, 1.5, pyrup, -0.5, 0)

def get_laplacian_pyramid_layer(img, n):
'''Returns the n-th layer of the laplacian pyramid'''
    currImg, i = img, 0
    while i < n: # and currImg.size > max_level (83)
        down, up = new_empty_img(img.shape), new_empty_img(img.shape)
        down = cv2.pyrDown(img)
        up = cv2.pyrUp(down, dstsize=currImg.shape)
        lap = currImg - up
        currImg = down
        i += 1
    return lap

up.shape[1]-down.shape[1]*2 == up.shape[1] %2 and up.shape[0]-down.shape[0]*2 == up.shape[0] %2

down = cv2.pyrDown(img)

down = cv2.pyrDown(currImg)

down = cv2.pyrDown(img)

up = cv2.pyrUp(down, dstsize=currImg.shape)
...
currImg = down

up = cv2.pyrUp(down, dstsize=currImg.shape)

up = cv2.pyrUp(down, dstsize=(currImg.shape[1],currImg.shape[0])