def test_with_location_of_image_as_argument(self):
messages_to_hide = ["Hello World!"]
for message in messages_to_hide:
outputBytes = io.BytesIO()
bytes_image = lsbset.hide(
"./tests/sample-files/20160505T130442.jpg", message,
generators.identity())
bytes_image.save(outputBytes, "PNG")
outputBytes.seek(0)
clear_message = lsbset.reveal(outputBytes, generators.identity())
self.assertEqual(message, clear_message)
def test_with_too_long_message(self):
with open("./tests/sample-files/lorem_ipsum.txt") as f:
message = f.read()
message += message * 2
with self.assertRaises(Exception):
lsbset.hide("./tests/sample-files/Lenna.png", message,
generators.identity())
def test_with_too_long_message(self):
with open("./tests/sample-files/lorem_ipsum.txt") as f:
message = f.read()
message += message*2
with self.assertRaises(Exception):
lsbset.hide("./tests/sample-files/Lenna.png", message,
generators.identity())
def test_identity(self):
"""Test the identity generator.
"""
self.assertEqual(
tuple(itertools.islice(generators.identity(), 15)),
(0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14),
)
def test_hide_and_reveal_with_bad_generator(self):
message_to_hide = "Hello World!"
secret = lsbset.hide("./tests/sample-files/Lenna.png", message_to_hide,
generators.eratosthenes())
secret.save("./image.png")
with self.assertRaises(IndexError):
clear_message = lsbset.reveal("./image.png", generators.identity())
def test_hide_and_reveal_with_bad_generator(self):
message_to_hide = "Hello World!"
secret = lsbset.hide("./tests/sample-files/Lenna.png", message_to_hide,
generators.eratosthenes())
secret.save("./image.png")
with self.assertRaises(IndexError):
clear_message = lsbset.reveal("./image.png", generators.identity())
path_output = '{}output'.format(path)
fname = 'cat.2.png'
z = eda.JointImageAnalyser(path_cover + fname, path_stego + fname)
# plot cover and stego images side by side.
z.plot_images()
# plot difference between cover and stego images.
z.plot_difference()
# plot colour channels of cover and stego images.
z.plot_rgb_components()
# Reveal and show hidden image
z.reveal_image(generators.identity(), show=True)
# Plot wavelet decomposition for a colour channel
eda.plot_wavelet_decomposition(z.I[:, :, 0])
# generate set of histogram/kde plots
eda.generate_feature_distplots(
filepath_train='{}data/features/train_lenna_identity.csv'.format(path),
path_output=path_output,
normalise=False
)
# generate set of histograms
eda.generate_feature_histograms(
filepath_train='{}data/features/train_lenna_identity.csv'.format(path),
path_output=path_output,
