percentage += percentPart
messageIndex += 1
else:
#print('ilk ife giremedi')
index += 1
pixelValues = image[i, j]
#print('Changed pixel values:', pixelValues)
print("100% complete")
print("writtenBits:", writtenBits)
print('You hid', bitsMessageSize, 'bits')
cv2.imwrite('hidden.bmp', image)
#Calculating the metrics
print('MSE:', round(sewar.mse(originalImage, image), 5))
print('PSNR:', round(sewar.psnr(originalImage, image), 5))
print('UIQI:', round(sewar.uqi(originalImage, image), 5))
(ssimValue, csValue) = sewar.ssim(originalImage, image)
print('SSIM:', round(ssimValue, 5))
numpy_horizontal = np.hstack((originalImage, image))
cv2.namedWindow("Original vs Hidden", cv2.WINDOW_NORMAL)
cv2.imshow('Original vs Hidden', numpy_horizontal)
cv2.waitKey()
#Plotting histograms
color = ('b', 'g', 'r')
plt.figure(figsize=(11, 5))
plt.subplot(1, 2, 1)
for i, col in enumerate(color):
def test_gray_const(self):
mse = sewar.mse(self.read('gry'), self.read('gry_const'))
self.assertTrue(abs(mse - 2016.476768) < self.eps)
def test_color(self):
mse = sewar.mse(self.read('clr'), self.read('clr'))
self.assertTrue(mse == 0.0)
def test_color_const(self):
mse = sewar.mse(self.read('clr'), self.read('clr_const'))
self.assertTrue(abs(mse - 2302.953958) < self.eps)
def test_gray_noise(self):
mse = sewar.mse(self.read('gry'), self.read('gry_noise'))
self.assertTrue(abs(mse - 2025.913940) < self.eps)
def test_color_noise(self):
mse = sewar.mse(self.read('clr'), self.read('clr_noise'))
print(mse)
self.assertTrue(abs(mse - 2391.465875) < self.eps)
def test_gray(self):
mse = sewar.mse(self.read('gry'), self.read('gry'))
self.assertTrue(mse == 0.0)
def mse(image_sr, image_hr):
return sewar.mse(image_hr, image_sr)