def embed_specific(self, image, image_file, watermark=None):
i_width = image.shape[0]
i_height = image.shape[1]
wm = watermark
wm_width = wm.shape[0]
wm_height = wm.shape[1]
if not (wm_width == i_width / 2 and wm_height == i_height / 2):
raise WmError("Watermark size must be half of image size. For now.")
ir, ig, ib = self.split_image(image)
img = self.split_image(wm)
dcts_wm = self.rgb_to_dct(*img)
dwts_i = self.rgb_to_dwt(ir, ig, ib)
for color in range(3):
dct = dcts_wm[color]
hh = TwoDimensionalDCT.forward(dwts_i[color][1][2])
for j in range(len(dct)):
for k in range(len(dct[0])):
hh[j][k] += dct[j][k] * self.alpha
ihh = TwoDimensionalDCT.inverse(hh)
hh = dwts_i[color][1][2]
for j in range(len(dct)):
for k in range(len(dct[0])):
hh[j][k] = ihh[j][k]
rgb = self.dwt_to_rgb(*dwts_i)
img = self.join_image(*rgb)
return img
def embed_specific(self, image, image_file, watermark=None):
# Compute DCT
f_dct = TwoDimensionalDCT.forward(image)
# Sort DCT
size_dct = int(f_dct.__len__()*self.watermark_size_percentage)
sorted_dct_indexes = f_dct.ravel().argsort()[-size_dct:]
sorted_dct_indexes = (numpy.unravel_index(indx, f_dct.shape) for indx in sorted_dct_indexes)
sorted_unraveled = [(f_dct[indx], indx) for indx in sorted_dct_indexes]
nbits = numpy.random.normal(self.mu, self.sigma, size_dct)
# Construct the Watermark
for i in range(len(nbits)):
f_dct[sorted_unraveled[i][1]] += self.alpha * nbits[i]
self.export_image(sorted_unraveled, image_file, nbits)
inverse = TwoDimensionalDCT.inverse(f_dct)
return inverse
def test_dct_solid_gray(self):
dct = TwoDimensionalDCT.forward(self.solid_gray)
for channel in range(3):
self.assertTrue(self.closeEnough(dct[0][0][channel], 800))
for channel in range(3):
for i in range(len(dct)):
for j in range(len(dct[i])):
if i != 0 and j != 0:
self.assertTrue(self.closeEnough(dct[i][j][channel], 0))
def extract_specific(self, image, watermark):
f_dct = TwoDimensionalDCT.forward(image)
w = self.load_watermark(watermark)
xi = []
xo = []
for entry in w:
xo.append( entry[self.INSERTED_WATERMARK_VALUE_KEY] )
xi.append( (f_dct[tuple(entry[self.INDEX_KEY])] - entry[self.ORIGINAL_VALUE_KEY]) /\
(self.alpha))
return None, Metrics.gamma(xi, xo)
def extract_specific(self, image, watermark):
wm = self.open_image(watermark)
RED, GREEN, BLUE = (0,1,2)
image_rgb = self.split_image(image)
wm_rgb = self.split_image(wm)
image_dwt = list(self.rgb_to_dwt(*image_rgb))
wm_dwt = list(self.rgb_to_dwt(*wm_rgb))
for color in range(3):
dct_image_dwt = TwoDimensionalDCT.forward(image_dwt[color][1][2])
dct_wm_dwt = TwoDimensionalDCT.forward(wm_dwt[color][1][2])
for i in range(len(image_dwt[RED][1][2])):
for j in range(len(image_dwt[RED][1][2][0])):
dct_image_dwt[i][j] = (dct_wm_dwt[i][j] - dct_image_dwt[i][j])/self.alpha
for i in range(len(image_dwt[RED][1][2])):
for j in range(len(image_dwt[RED][1][2][0])):
image_dwt[color][1][2][i][j] = dct_image_dwt[i][j]
return self.join_image(*self.dct_to_rgb(image_dwt[RED][1][2], image_dwt[GREEN][1][2], image_dwt[BLUE][1][2])), 0
def dct_to_rgb(self, cr, cg, cb):
return TwoDimensionalDCT.inverse(cr), TwoDimensionalDCT.inverse(cg), TwoDimensionalDCT.inverse(cb)
def rgb_to_dct(self, r, g, b):
return TwoDimensionalDCT.forward(r), TwoDimensionalDCT.forward(g), TwoDimensionalDCT.forward(b)
def test_idct_close_values(self):
img = TwoDimensionalDCT.inverse(TwoDimensionalDCT.forward(self.close_values))
self._test_inverse(img, self.close_values)
def test_idct_solid_gray(self):
img = TwoDimensionalDCT.inverse(TwoDimensionalDCT.forward(self.solid_gray))
self._test_inverse(img, self.solid_gray)
def test_dct_close_values(self):
dct = TwoDimensionalDCT.forward(self.close_values)
self.assertTrue(self.closeEnough(dct[0][0][0], 407))