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)