import matplotlib.pyplot as plt
import matplotlib.image as img
import numpy as np

native = img.imread('native.jpg')
dlss = img.imread('dlss.jpg')
fsr = img.imread('fsr.jpg')

x_start, x_end, y_start, y_end = 0,1000,800,1960
mse_of_section = lambda z: np.mean((z[y_start:y_end, x_start:x_end] - native[y_start:y_end, x_start:x_end])**2)

print('Native - DLSS MSE: ' + str(mse_of_section(dlss)))
print('Native - FSR MSE: ' + str(mse_of_section(fsr)))

for img,img_name in zip([native, dlss, fsr], ['native', 'dlss', 'fsr']):
    plt.figure()
    plt.imshow(img[y_start:y_end, x_start:x_end])
    plt.savefig(f'cropped_{img_name}.png')
    plt.close()