def start_Genetic_Algorithm(st, goal):
startBlock = st
destBlock = goal
# to increase accuracy, increase "iterations"
chromosomeSize = 20
iterations = 10
pop = population(20, True, startBlock, destBlock, chromosomeSize)
print("Initial distance (Before Genetic Algorithm): ",
pop.getFittest().getDistance())
pop = GA.evolvePopulation(pop)
for i in range(iterations):
pop = GA.evolvePopulation(pop)
return pop
def __init__(self, name, message, number):
#Encryption of plain text
messageUtf = message.encode('utf-8')
key = Fernet.generate_key()
print("The key generated for this encryption is: ", key)
print()
time.sleep(1)
cipher_suite = Fernet(key)
cipher_text = cipher_suite.encrypt(messageUtf)
plain_text = cipher_suite.decrypt(cipher_text)
data = cipher_text.decode('utf-8')
data = data + '~'
cipher = []
for i in data:
cipher.append(ord(i))
qwerty = cipher[:]
#Extract pixel
img = Image.open(name)
arr = array(img)
row = len(arr)
column = len(arr[0])
testing = row
testing1 = column
print('Initializing the initial population ')
time.sleep(1)
chromosomes = [None] * (row * column)
index = 0
#Initialise chromosomes with pixel values
for x in range(column):
for y in range(row):
chromosomes[index] = Chromosome(index, arr[y][x][0],
arr[y][x][1], arr[y][x][2], -1,
y, x, -1)
index += 1
print("Starting the genetic algorithm...")
time.sleep(1)
geneticAlgoritm = GA(cipher, len(chromosomes))
for i in range(len(cipher)):
geneticAlgoritm.initializePopulation(chromosomes)
pop = geneticAlgoritm.evolvePopulation()
chroms = pop.getAllChromosome()
for j in range(len(chroms)):
chromosomes[j] = chroms[j]
print("Genetic algorithm has completed execution..")
time.sleep(1)
print("Started burning the data into the image")
time.sleep(1.5)
if len(cipher) > (row * column):
print('The image will not be able to accomodate the data')
print("Try with some other image")
else:
print('The image will be able to accomodate the data')
time.sleep(1.5)
i = 0
j = 0
k = 0
a = arr[:]
count = 0
for i in range(row):
for j in range(column):
for k in range(len(chromosomes)):
if chromosomes[k].getX() == i and chromosomes[k].getY(
) == j:
a[i][j][0] = chromosomes[k].getGene(0)
a[i][j][1] = chromosomes[k].getGene(1)
a[i][j][2] = chromosomes[k].getGene(2)
print('We have now completed building the new image...')
time.sleep(1)
final_img = Image.fromarray(a)
final_img.save('final' + str(number) + '.png')
print(
'The image has been saved as final.png in the same folder as this program.'
)
print()
print()
time.sleep(1.5)
print('Visual cryptography algorithm has started to run')
time.sleep(1.5)
objVisual = visual_cryptography("final" + str(number) + ".png",
number)
keyVisual = objVisual.encrypt()
print()
print("Generating the pixel index table....")
time.sleep(1.5)
pitTable = []
for i in range(len(cipher)):
pitTable.append(Pit())
pitTableIndex = 0
for i in range(len(cipher)):
for j in range(len(chromosomes)):
if chromosomes[j].getSolutionId() == i:
test = chromosomes[j].getAllGenes()
minDxs = getMinDx(chromosomes[j].getAllGenes(),
cipher[i])
pitTable[pitTableIndex] = Pit(chromosomes[j].getX(),
chromosomes[j].getY(),
minDxs)
pitTableIndex += 1
for i in range(len(pitTable)):
f = open("pit1" + str(number) + ".csv", 'a')
f.write(pitTable[i].toString() + "\n")
f.close()
print('The Pixel Index Table file has been generated.')
print('The key for decryption of the visual cryptography is: ',
keyVisual)
time.sleep(1.5)
print('The key for decryption of message is: ', key.decode('utf-8'))
time.sleep(1.5)
pass1 = "" + keyVisual
pass2 = "" + key.decode('utf-8')
file = open('Passwords' + str(number), 'w')
file.write(pass1)
file.write('~')
file.write(pass2)
print(
'The keys for decryption are stored in Passwords file in the same folder as this code.'
)
#Initialize a TourManager object and add cities to its list of destinations
tourmanager = TourManager()
for i in range(len(cities)):
tourmanager.addCity(cities[i])
start_time = time.time()
#Init a population of individual tours
pop = Population(tourmanager, len(cities), True)
#print intitual distance
print("Initial distance: " + str(pop.getFittest().getDistance()))
#Evolve population for 100 generations
ga = GA(tourmanager)
pop = ga.evolvePopulation(pop)
for i in range(0, 100):
pop = ga.evolvePopulation(pop)
#Final results
finalDist = str(pop.getFittest().getDistance())
#Returns a tour object
bestTour = pop.getFittest()
print("Finished!")
print("Final distance: " + finalDist)
print("Time to calculate best tour:")
print(time.time() - start_time)
print("Best tour:")
print(bestTour)
#Write to file
