def generate(self):
# Select mutation operator.
rand_mutation_probability = random.uniform(0, 1)
if rand_mutation_probability >= MUTOPPROB:
mutation = 1
else:
mutation = 2
condition = True
counter_mutations = 0
while condition:
counter_mutations += 1
vector1, vector2 = mutation_manager.generate(
self.digit.xml_desc, mutation)
v1_xml_desc = vectorization_tools.create_svg_xml(vector1)
rasterized_digit1 = rasterization_tools.rasterize_in_memory(
v1_xml_desc)
v2_xml_desc = vectorization_tools.create_svg_xml(vector2)
rasterized_digit2 = rasterization_tools.rasterize_in_memory(
v2_xml_desc)
distance_inputs = get_distance(rasterized_digit1,
rasterized_digit2)
if distance_inputs != 0:
condition = False
first_digit = Digit(v1_xml_desc, EXPECTED_LABEL)
second_digit = Digit(v2_xml_desc, EXPECTED_LABEL)
first_digit.purified = rasterized_digit1
second_digit.purified = rasterized_digit2
return first_digit, second_digit, distance_inputs
def mutate(self, reference=None):
# Select mutation operator.
rand_mutation_probability = random.uniform(0, 1)
if rand_mutation_probability >= MUTOPPROB:
mutation = 1
else:
mutation = 2
condition = True
counter_mutations = 0
while condition:
counter_mutations += 1
mutant_vector = mutation_manager.mutate(self.digit.xml_desc,
mutation,
counter_mutations / 20)
mutant_xml_desc = vectorization_tools.create_svg_xml(mutant_vector)
rasterized_digit = rasterization_tools.rasterize_in_memory(
mutant_xml_desc)
distance_inputs = get_distance(self.digit.purified,
rasterized_digit)
if distance_inputs != 0:
if reference is not None:
distance_inputs = get_distance(reference.purified,
rasterized_digit)
if distance_inputs != 0:
condition = False
else:
condition = False
self.digit.xml_desc = mutant_xml_desc
self.digit.purified = rasterized_digit
return distance_inputs
def __init__(self, desc, label):
self.xml_desc = desc
self.expected_label = label
self.predicted_label = None
self.purified = rasterization_tools.rasterize_in_memory(self.xml_desc)
self.P_class = None
self.P_notclass = None
def mutate(self):
condition = True
counter_mutations = 0
while condition:
# Select mutation operator.
rand_mutation_probability = random.uniform(0, 1)
rand_mutation_prob = random.uniform(0, 1)
if rand_mutation_probability >= MUTOPPROB:
if rand_mutation_prob >= MUTOFPROB:
mutation = 1
else:
mutation = 2
else:
if rand_mutation_prob >= MUTOFPROB:
mutation = 3
else:
mutation = 4
counter_mutations += 1
mutant_vector = mutation_manager.mutate(self.digit.xml_desc, mutation, counter_mutations/20)
mutant_xml_desc = vectorization_tools.create_svg_xml(mutant_vector)
rasterized_digit = rasterization_tools.rasterize_in_memory(mutant_xml_desc)
distance_inputs = get_distance(self.digit.purified, rasterized_digit)
if (TSHD_TYPE == '0'):
if distance_inputs != 0:
condition = False
elif (TSHD_TYPE == '1'):
seed_image = DigitMutator.x_test[int(self.digit.seed)]
xml_desc = vectorization_tools.vectorize(seed_image)
seed = rasterization_tools.rasterize_in_memory(xml_desc)
distance_seed = get_distance(seed, rasterized_digit)
if distance_inputs != 0 and distance_seed <= DISTANCE and distance_seed != 0:
condition = False
elif (TSHD_TYPE == '2'):
seed = reshape(DigitMutator.x_test[int(self.digit.seed)])
distance_seed = get_distance(seed, rasterized_digit)
if distance_inputs != 0 and distance_seed <= DISTANCE_SEED and distance_seed != 0:
condition = False
self.digit.xml_desc = mutant_xml_desc
self.digit.purified = rasterized_digit
self.digit.predicted_label = None
self.digit.confidence = None
def apply_rast_tshd(image, seed, tshd_val):
seed_image = x_test[int(seed)]
xml_desc = vectorization_tools.vectorize(seed_image)
seed = rasterization_tools.rasterize_in_memory(xml_desc)
distance_seed = get_distance(seed, image)
print("RAST %s" % distance_seed)
if distance_seed < tshd_val:
return True
else:
return False
def __init__(self, desc, label, seed):
self.timestamp, self.elapsed_time = Timer.get_timestamps()
self.id = Digit.COUNT
self.run = RUN
self.seed = seed
# TODO
self.features = FEATURES
self.tool = "DeepHyperion"
self.xml_desc = desc
self.purified = rasterization_tools.rasterize_in_memory(self.xml_desc)
self.expected_label = label
self.predicted_label = None
self.confidence = None
Digit.COUNT += 1