Flood fill algorithm
Problem Statement
An image is represented by a 2-D array of integers, each integer representing the pixel value of the image.
Given a coordinate (sr, sc) representing the starting pixel (row and column) of the flood fill, and a pixel value newColor, "flood fill" the image.
To perform a "flood fill", consider the starting pixel, plus any pixels connected 4-directionally to the starting pixel of the same color as the starting pixel, plus any pixels connected 4-directionally to those pixels (also with the same color as the starting pixel), and so on. Replace the color of all of the aforementioned pixels with the newColor.
Example 1:
Input: image = {{1,1,1},{1,1,0},{1,0,1}},
sr = 1, sc = 1, newColor = 2.
Output: {{2,2,2},{2,2,0},{2,0,1}}
Explanation: From the center of the image
(with position (sr, sc) = (1, 1)), all
pixels connected by a path of the same color
as the starting pixel are colored with the new
color.Note the bottom corner is not colored 2,
because it is not 4-directionally connected to
the starting pixel.
Your Task:
You don't need to read or print anything. Your task is to complete the function floodFill() which takes image, sr, sc and newColor as input parameter and returns the image after flood filling.
Expected Time Compelxity: O(nm)
Expected Space Complexity: O(nm)
Constraints:
1 <= n <= m <= 100
0 <= pixel values <= 10
0 <= sr <= (n-1)
0 <= sc <= (m-1)
Approach
just use implicit bfs/dfs and keep track of colors for the thing. We are allowed to modify the matrix itself here, best practice is to not modify the source data.
Solution
from collections import deque
# Snippet created by sameer 21-08-2023
def valid_neighbors(x, y, graph):
m, n = len(graph), len(graph[0])
delta = [(-1,0),(0,-1),(0,1),(1,0)]
neighbors = []
for dx,dy in delta:
r, c = x + dx, y + dy
if 0<=r<m and 0<=c<n:
neighbors.append((r,c))
return neighbors
def bfs_impl(matrix, vertex, newColor):
sr, sc = vertex
source_color = matrix[sr][sc]
matrix[sr][sc] = newColor
q = deque()
q.append(vertex)
while q:
x, y = q.popleft()
for r, c in valid_neighbors(x, y, matrix):
if matrix[r][c] != newColor and matrix[r][c] == source_color:
q.append((r, c))
matrix[r][c] = newColor
class Solution:
def floodFill(self, image, sr, sc, newColor):
bfs_impl(image, (sr, sc), newColor)
return image