%matplotlib inline
from skimage import feature
from skimage import data
from skimage import transform

import matplotlib.pyplot as plt

image = data.chelsea()

def shift(xy):
    xy[:, 1] -= 30
    return xy
    
image_shifted = transform.warp(image, inverse_map=shift)

f, (ax0, ax1) = plt.subplots(1, 2)
ax0.imshow(image)
ax1.imshow(image_shifted)

out = feature.match_template(image, image_shifted, pad_input=True)

import numpy as np
np.array(image.shape)//2. - np.unravel_index(out.argmax(), image.shape)