#!/usr/bin/env python3

import numpy as np
import scipy.ndimage.filters as filters
import scipy.ndimage.morphology as morphology


arr = np.array([[int(n) for n in line.strip()] for line in open("input.txt")])

# https://stackoverflow.com/questions/3986345/how-to-find-the-local-minima-of-a-smooth-multidimensional-array-in-numpy-efficie
neighborhood = morphology.generate_binary_structure(len(arr.shape), 1)
local_min = (filters.minimum_filter(arr, footprint=neighborhood) == arr)
local_max = (filters.maximum_filter(arr, footprint=neighborhood) == arr)
local_min_without_plateau = np.logical_and(local_min, np.logical_not(local_max))
local_min_locations = np.where(local_min_without_plateau)
local_min_values = arr[local_min_locations]

print(sum(local_min_values)+len(local_min_values))