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import numpy as np
import itertools


VALUES = {
    (4, 4): [8736, 24024, 48048, 72072, 82368, ],
    (4, 5): [25296, 94860, 265608, 575484, 986544, ],
    (4, 6): [58520, 277970, 1000692, 2835294, 6480672, ],
    (4, 7): [117000, 672750, 2960100, 10360350, 29601000, ],
    (4, 8): [211120, 1425060, 7410312, 30876300, 105861600, ],
    (5, 4): [25296, 94860, 265608, 575484, 986544, ],
    (5, 5): [70840, 354200, 1345960, 4037880, 9806280, ],
    (5, 6): [160524, 1003275, 4815720, 18460260, 58017960, ],
    (5, 7): [316448, 2373360, 13765488, 64238944, 247778784, ],
    (5, 8): [565212, 4945605, 33630114, 184965627, 845557152, ],
    (6, 4): [58520, 277970, 1000692, 2835294, 6480672, ],
    (6, 5): [160524, 1003275, 4815720, 18460260, 58017960, ],
    (6, 6): [359040, 2782560, 16695360, 80694240, 322776960, ],
    (6, 7): [701480, 6488690, 46718568, 272524980, 1323692760, ],
    (6, 8): [1244760, 13381170, 112401828, 768079158, 4389023760, ],
    (7, 4): [117000, 672750, 2960100, 10360350, 29601000, ],
    (7, 5): [316448, 2373360, 13765488, 64238944, 247778784, ],
    (7, 6): [701480, 6488690, 46718568, 272524980, 1323692760, ],
    (7, 7): [1362060, 14982660, 128850876, 901956132, 5282885916, ],
    (7, 8): [2405988, 30676347, 306763470, 2505235005, 17178754320, ],
    (8, 4): [211120, 1425060, 7410312, 30876300, 105861600, ],
    (8, 5): [565212, 4945605, 33630114, 184965627, 845557152, ],
    (8, 6): [1244760, 13381170, 112401828, 768079158, 4389023760, ],
    (8, 7): [2405988, 30676347, 306763470, 2505235005, 17178754320, ],
    (8, 8): [4235840, 62478640, 724752224, 6885146128, 55081169024, ]
}


def read_board(n, m):
    board = np.zeros((n, m))

    for i in range(n):
        line = input()
        for j, l in enumerate(line):
            if l == 'O':
                board[i, j] = 1
    
    return board



def calculate(pawns, end_position, n, m, parity):
    sum = 0
    # print(parity)
    sum_of_position = 0
    position_coutner = 0

    test_sum = 0
    for pawn in end_position:
        row, col = pawn//m, pawn%m
        test_sum += row
        test_sum += col
    if test_sum % 2 != parity:
        return 0

    for pawn in end_position:
        row, col = pawn//m, pawn%m
        if row + 1 < n and (row+1)*m + col not in end_position:
            sum_of_position += 1
        if row > 0 and (row-1)*m + col not in end_position:
            sum_of_position += 1
        if col > 0 and row*m + col - 1 not in end_position:
            sum_of_position += 1
        if col + 1 < m and row*m + col + 1 not in end_position:
            sum_of_position += 1
    

    if (n, m) in VALUES and pawns > 3:
        return sum_of_position/VALUES[(n, m)][pawns-4]
    
    for i, position in enumerate((itertools.combinations(list(range(n*m)), pawns))):
        test_sum = 0
        for pawn in position:
            row, col = pawn//m, pawn%m
            test_sum += row
            test_sum += col
        if test_sum % 2 != parity:
            continue
        for pawn in position:
            row, col = pawn//m, pawn%m
            if row + 1 < n and (row+1)*m + col not in position:
                sum += 1
            if row > 0 and (row-1)*m + col not in position:
                sum += 1
            if col > 0 and row*m + col - 1 not in position:
                sum += 1
            if col + 1 < m and row*m + col + 1 not in position:
                sum += 1
        # if i%100_000_000 == 0:
            # print(i)

    return sum_of_position/sum



def positions_to_values(l, n, m):
    result = []
    for elem in l:
        result.append(elem[0]*m + elem[1])
    return tuple(sorted(result))



def main():
    n, m = (int(x) for x in input().split())
    board = read_board(n, m)
    input()
    end_position = read_board(n, m)
    end_position = positions_to_values(np.array(np.where(end_position == 1)).T, n, m)
    starting_positions = np.array(np.where(board == 1)).T
    
    probabilities = {
        positions_to_values(starting_positions, n, m): 1
    }

    # print(probabilities)
    parity = np.sum(np.where(board == 1))%2
    # print(len(simulate(probabilities, 16_000, n, m, end_position)))
    print(f"{calculate(len(np.where(board == 1)[0]), end_position, n, m, parity):.15f}")


if __name__ == '__main__':
    main()
    # print(calculate(6, 0, 8, 8, 1))