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seam_carving.py
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seam_carving.py
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#!/usr/bin/python
# -*- coding: utf-8 -*-
# CS4102 Spring 2022 -- Unit C Programming
#################################
# Collaboration Policy: You are encouraged to collaborate with up to 3 other
# students, but all work submitted must be your own independently written
# solution. List the computing ids of all of your collaborators in the comment
# at the top of your java or python file. Do not seek published or online
# solutions for any assignments. If you use any published or online resources
# (which may not include solutions) when completing this assignment, be sure to
# cite them. Do not submit a solution that you are unable to explain orally to a
# member of the course staff.
#################################
# Your Computing ID: rjl4sw
# Collaborators:
# Sources: Introduction to Algorithms, Cormen
#################################
import math
def findDistance(pix1, pix2):
r = pix2[0] - pix1[0]
g = pix2[1] - pix1[1]
b = pix2[2] - pix1[2]
return math.sqrt(r ** 2 + b ** 2 + g ** 2)
def seamLister(row, weight, col):
image = range(1, row)
for pixel in image:
min_value = math.inf
min_column = 0
if seam_list[pixel - 1] == 0:
for y in range(0, 2):
if weight[pixel][seam_list[pixel - 1] + y] < min_value:
min_value = weight[pixel][seam_list[pixel - 1] + y]
min_column = seam_list[pixel - 1] + y
elif seam_list[pixel - 1] == col - 1:
for y in range(-1, 1):
if weight[pixel][seam_list[pixel - 1] + y] < min_value:
min_value = weight[pixel][seam_list[pixel - 1] + y]
min_column = seam_list[pixel - 1] + y
else:
for y in range(-1, 2):
if weight[pixel][seam_list[pixel - 1] + y] < min_value:
min_value = weight[pixel][seam_list[pixel - 1] + y]
min_column = seam_list[pixel - 1] + y
seam_list.append(min_column)
def createMap(image):
row = len(image)
col = len(image[0])
e = [[0 for i in range(col)] for j in range(row)]
for i in range(row):
for j in range(col):
if i == 0 and (j == 0 or j == col - 1) or i == row - 1 \
and (j == 0 or j == col - 1):
if i == 0 and j == 0:
for x in range(i, i + 2):
for y in range(j, j + 2):
e[i][j] += findDistance(image[i][j],
image[x][y]) / 3
elif i == 0 and j == col - 1:
for x in range(i, i + 2):
for y in range(j - 1, j + 1):
e[i][j] += findDistance(image[i][j],
image[x][y]) / 3
elif i == row - 1 and j == 0:
for x in range(i - 1, i + 1):
for y in range(j, j + 2):
e[i][j] += findDistance(image[i][j],
image[x][y]) / 3
else:
for x in range(i - 1, i + 1):
for y in range(j - 1, j + 1):
e[i][j] += findDistance(image[i][j],
image[x][y]) / 3
elif j == 0 or j == col - 1 or i == 0 or i == row - 1:
if j == 0:
for x in range(i - 1, i + 2):
for y in range(j, j + 2):
e[i][j] += findDistance(image[i][j],
image[x][y]) / 5
elif j == col - 1:
for x in range(i - 1, i + 2):
for y in range(j - 1, j + 1):
e[i][j] += findDistance(image[i][j],
image[x][y]) / 5
elif i == 0:
for x in range(i, i + 2):
for y in range(j - 1, j + 2):
e[i][j] += findDistance(image[i][j],
image[x][y]) / 5
else:
for x in range(i - 1, i + 1):
for y in range(j - 1, j + 2):
e[i][j] += findDistance(image[i][j],
image[x][y]) / 5
else:
for x in range(i - 1, i + 2):
for y in range(j - 1, j + 2):
e[i][j] += findDistance(image[i][j],
image[x][y]) / 8
return e
class SeamCarving:
def __init__(self):
return
# This method is the one you should implement. It will be called to perform
# the seam carving. You may create any additional data structures as fields
# in this class or write any additional methods you need.
#
# @return the seam's weight
def run(self, image):
x = createMap(image)
row = len(x)
col = len(x[0])
weight = [[0 for i in range(col)] for j in range(row)]
global seam_list
seam_list = [0]
lowest = math.inf
index = 0
if len(image) == 1 or len(image[0]) == 1:
if len(image) == 1 and len(image[0]) == 1:
return math.sqrt(image[0][0][0] ** 2 + image[0][0][1]
** 2 + image[0][0][2] ** 2)
elif len(image[0]) == 1:
for g in range(len(image) - 1):
seam_list.append(0)
sum = findDistance(image[len(image) - 1][0],
image[len(image) - 2][0])
for w in range(len(image) - 2, -1, -1):
if w == 0:
sum += findDistance(image[w][0],
image[w+ 1][0])
else:
sum += 1 / 2 * findDistance(image[w][0],
image[w - 1][0]) \
+ findDistance(image[w][0], image[w + 1][0])
return sum
else:
case = [0 for k in range(len(image[0]))]
for q in range(len(image[0])):
if q == 0:
case[q] += findDistance(image[0][q],
image[0][q + 1])
elif q == len(image[0]) - 1:
case[q] += findDistance(image[0][q],
image[0][q - 1])
else:
case[q] += 1 / 2 * findDistance(image[0][q],
image[0][q - 1])
case[q] += 1 / 2 * findDistance(image[0][q],
image[0][q + 1])
mv = case[0]
index = 0
for r in range(1, len(case)):
if case[r] < mv:
mv = case[r]
index = r
seam_list[0] = index
return mv
for a in range(col):
weight[row - 1][a] = x[row - 1][a]
for r in range(row - 2, -1, -1):
for c in range(col):
if c == 0:
weight[r][c] = min(weight[r + 1][c] + x[r][c],
weight[r + 1][c + 1] + x[r][c])
elif c == col - 1:
weight[r][c] = min(weight[r + 1][c - 1] + x[r][c],
weight[r + 1][c] + x[r][c])
else:
weight[r][c] = min(weight[r + 1][c - 1] + x[r][c],
weight[r + 1][c] + x[r][c],
weight[r + 1][c+ 1] + x[r][c])
for x in range(col):
if weight[0][x] < lowest:
lowest = weight[0][x]
index = x
seam_list[0] = index
seamLister(row, weight, col)
return lowest
# Get the seam, in order from top to bottom, where the top-left corner of the
# image is denoted (0,0).
#
# Since the y-coordinate (row) is determined by the order, only return the x-coordinate
#
# @return the ordered list of x-coordinates (column number) of each pixel in the seam
# as an array
def getSeam(self):
return seam_list