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Writing in Python In this part, you'll write the code that implements the flood fill algorithm, identifys and changes the marked pixels. # Furthermore, blank pixels are ignored. To do this,you'll use any breadth first search algorithm. # The code is partially written below. DO NOT change the NAME or anything just complete the yellow highlighted part

Writing in Python In this part, you'll write the code that implements the flood fill algorithm, identifys and changes the marked pixels. # Furthermore, blank pixels are ignored. To do this,you'll use any breadth first search algorithm. # The code is partially written below. DO NOT change the NAME or anything just complete the yellow highlighted part

Database System Concepts
Database System Concepts
7th Edition
ISBN:9780078022159
Author:Abraham Silberschatz Professor, Henry F. Korth, S. Sudarshan
Publisher:Abraham Silberschatz Professor, Henry F. Korth, S. Sudarshan
Chapter1: Introduction
Section: Chapter Questions
Problem 1PE
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Writing in Python

In this part, you'll write the code that implements the flood fill algorithm, identifys and changes the marked pixels. # Furthermore, blank pixels are ignored. To do this,you'll use any breadth first search algorithm. # The code is partially written below.

DO NOT change the NAME or anything  just complete the yellow highlighted part

# Create a node - the datapoints within the graph class Node: def __init__(self, x, y): self.x = x self.y = y self.neighbours = list() # Start function - acts as a starting point for the flood fill algorithm def start(): # Sample image represented as 2D array of numbers image = [ [1,0,0,0,0], [1,1,0,1,0], [0,1,1,1,0], [0,1,1,1,1], [0,1,1,0,1] ] graph = Graph() print(graph.flood Fill(image, 2, 2, 2)) # DO NOT REMOVE THIS RETURN STATEMENT! return graph # The flood fill algorithm - flood fill algorithm using breadth first search class Graph: numberOfNonUniqueEdges = 0 visited=set() def floodFill(self, image, x, y, pixel): start Node(x, y) queue = list() queue.append(start) # Remember to add the x and y coordinates of newly discovered nodes to the visited set ### ### YOUR CODE HERE ### # Return the modified image represented as 2D array of numbers return image def neighbours(self, image, x, y, currentNode): U=y-1 D=y+1 L=x-1 R = x + 1 # An edge is valid if the pixel is newly discovered, i.e. an edge is created when the neighbour's pixel value is one. # Write the neighbours function to find the neighbours in four directions for a given pixel. # Append valid Node to the neighbours of the currentNode #Remember to do boundary checking ### ### YOUR CODE HERE ### ### DO NOT REMOVE THIS LINE ### self.numberOfNonUniqueEdges = self.numberOfNonUniqueEdges + len(currentNode.neighbours) ### ## ### ###### #### #### #### # Return the current node's (the pixel in question) neighbours, not always a maximum of four. # Call the start function return currentNode.neighbours graph = start() ●●●
Transcribed Image Text:# Create a node - the datapoints within the graph class Node: def __init__(self, x, y): self.x = x self.y = y self.neighbours = list() # Start function - acts as a starting point for the flood fill algorithm def start(): # Sample image represented as 2D array of numbers image = [ [1,0,0,0,0], [1,1,0,1,0], [0,1,1,1,0], [0,1,1,1,1], [0,1,1,0,1] ] graph = Graph() print(graph.flood Fill(image, 2, 2, 2)) # DO NOT REMOVE THIS RETURN STATEMENT! return graph # The flood fill algorithm - flood fill algorithm using breadth first search class Graph: numberOfNonUniqueEdges = 0 visited=set() def floodFill(self, image, x, y, pixel): start Node(x, y) queue = list() queue.append(start) # Remember to add the x and y coordinates of newly discovered nodes to the visited set ### ### YOUR CODE HERE ### # Return the modified image represented as 2D array of numbers return image def neighbours(self, image, x, y, currentNode): U=y-1 D=y+1 L=x-1 R = x + 1 # An edge is valid if the pixel is newly discovered, i.e. an edge is created when the neighbour's pixel value is one. # Write the neighbours function to find the neighbours in four directions for a given pixel. # Append valid Node to the neighbours of the currentNode #Remember to do boundary checking ### ### YOUR CODE HERE ### ### DO NOT REMOVE THIS LINE ### self.numberOfNonUniqueEdges = self.numberOfNonUniqueEdges + len(currentNode.neighbours) ### ## ### ###### #### #### #### # Return the current node's (the pixel in question) neighbours, not always a maximum of four. # Call the start function return currentNode.neighbours graph = start() ●●●
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