leetcode 661. Image Smoother

Given a 2D integer matrix M representing the gray scale of an image, you need to design a smoother to make the gray scale of each cell becomes the average gray scale (rounding down) of all the 8 surrounding cells and itself. If a cell has less than 8 surrounding cells, then use as many as you can.

Example 1:

Input:
[[1,1,1],
 [1,0,1],
 [1,1,1]]
Output:
[[0, 0, 0],
 [0, 0, 0],
 [0, 0, 0]]
Explanation:
For the point (0,0), (0,2), (2,0), (2,2): floor(3/4) = floor(0.75) = 0
For the point (0,1), (1,0), (1,2), (2,1): floor(5/6) = floor(0.83333333) = 0
For the point (1,1): floor(8/9) = floor(0.88888889) = 0

Note:

The value in the given matrix is in the range of [0, 255].
The length and width of the given matrix are in the range of [1, 150].
不修改M：

class Solution(object):
    def imageSmoother(self, M):
        """
        :type M: List[List[int]]
        :rtype: List[List[int]]
        """
        row = len(M)
        col = len(M[0])
        R = [[0 for i in range(col)] for j in range(row)]
        
        def get_avg(M, i, j):
            diff_pos = [(0, 1), (0, -1), (1, 0), (-1, 0), (1, 1), (1, -1), (-1, 1), (-1, -1)]
            s = M[i][j]
            l = 1           
            for x,y in diff_pos:
                if 0<=i+x<row and 0<=j+y<col:
                    s += M[i+x][j+y]
                    l += 1            
            return s//l
        
        for i in xrange(0, row):
            for j in xrange(0, col):
                R[i][j] = get_avg(M, i, j)
        return R

修改M：

class Solution(object):
    def imageSmoother(self, M):
        """
        :type M: List[List[int]]
        :rtype: List[List[int]]
        """
        row = len(M)
        col = len(M[0])
                
        def get_avg(M, i, j):
            s = l = 0          
            for x in xrange(-1, 2):
                for y in xrange(-1, 2):
                    if 0<=i+x<row and 0<=j+y<col:
                        s += (M[i+x][j+y] & 0xff)
                        l += 1            
            return (s//l) <<8
        
        for i in xrange(0, row):
            for j in xrange(0, col):
                M[i][j] += get_avg(M, i, j)
        
        for i in xrange(0, row):
            for j in xrange(0, col):
                M[i][j] >>= 8
        return M