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dwt_watermark.py
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dwt_watermark.py
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import math
import cv2
import numpy as np
import pywt
from attack import Attack
from watermark import Watermark
class DWT_Watermark(Watermark):
def __init__(self):
pass
def __gene_embed_space(self, vec):
shape = vec.shape
vec = vec.flatten()
combo_neg_idx = np.array(
[1 if vec[i] < 0 else 0 for i in range(len(vec))])
vec_pos = np.abs(vec)
int_part = np.floor(vec_pos)
frac_part = np.round(vec_pos - int_part, 2)
bi_int_part = []
for i in range(len(int_part)):
bi = list(bin(int(int_part[i]))[2:])
bie = [0] * (16 - len(bi))
bie.extend(bi)
bi_int_part.append(np.array(bie, dtype=np.uint16))
bi_int_part = np.array(bi_int_part)
sig = []
for i in range(len(bi_int_part)):
sig.append(bi_int_part[i][10])
sig = np.array(sig).reshape(shape)
return np.array(bi_int_part), frac_part.reshape(shape), combo_neg_idx.reshape(shape), sig
def __embed_sig(self, bi_int_part, frac_part, combo_neg_idx, signature):
shape = frac_part.shape
frac_part = frac_part.flatten()
combo_neg_idx = combo_neg_idx.flatten()
m = len(signature)
n = len(bi_int_part)
if m >= n:
for i in range(n):
bi_int_part[i][10] = signature[i]
if m < n:
rate = n//m
for i in range(m):
for j in range(rate):
bi_int_part[i + j * m][10] = signature[i]
em_int_part = []
for i in range(len(bi_int_part)):
s = '0b'
s += (''.join([str(j) for j in bi_int_part[i]]))
em_int_part.append(eval(s))
em_combo = np.array(em_int_part) + np.array(frac_part)
em_combo = np.array([-1 * em_combo[i] if combo_neg_idx[i] == 1 else em_combo[i]
for i in range(len(em_combo))]).reshape(shape)
return em_combo.reshape(shape)
def __extract_sig(self, ext_sig, siglen):
ext_sig = list(ext_sig.flatten())
m = len(ext_sig)
n = siglen
ext_sigs = []
if n > m:
ext_sigs.append(ext_sig + ([0] * (n-m)))
if n <= m:
rate = m//n
for i in range(rate):
ext_sigs.append(ext_sig[i * n: (i+1) * n])
return ext_sigs
def inner_embed(self, B, signature):
w, h = B.shape[:2]
LL, (HL, LH, HH) = pywt.dwt2(
np.array(B[:32 * (w // 32), :32 * (h // 32)]), 'haar')
LL_1, (HL_1, LH_1, HH_1) = pywt.dwt2(LL, 'haar')
LL_2, (HL_2, LH_2, HH_2) = pywt.dwt2(LL_1, 'haar')
LL_3, (HL_3, LH_3, HH_3) = pywt.dwt2(LL_2, 'haar')
LL_4, (HL_4, LH_4, HH_4) = pywt.dwt2(LL_3, 'haar')
bi_int_part, frac_part, combo_neg_idx, _ = self.__gene_embed_space(
HH_3)
HH_3 = self.__embed_sig(bi_int_part, frac_part,
combo_neg_idx, signature)
LL_3 = pywt.idwt2((LL_4, (HL_4, LH_4, HH_4)), 'haar')
LL_2 = pywt.idwt2((LL_3, (HL_3, LH_3, HH_3)), 'haar')
LL_1 = pywt.idwt2((LL_2, (HL_2, LH_2, HH_2)), 'haar')
LL = pywt.idwt2((LL_1, (HL_1, LH_1, HH_1)), 'haar')
B[:32 * (w // 32), :32 * (h // 32)
] = pywt.idwt2((LL, (HL, LH, HH)), 'haar')
return B
def inner_extract(self, B):
w, h = B.shape[:2]
LL, (HL, LH, HH) = pywt.dwt2(
B[:32 * (w // 32), :32 * (h // 32)], 'haar')
LL_1, (HL_1, LH_1, HH_1) = pywt.dwt2(LL, 'haar')
LL_2, (HL_2, LH_2, HH_2) = pywt.dwt2(LL_1, 'haar')
LL_3, (HL_3, LH_3, HH_3) = pywt.dwt2(LL_2, 'haar')
LL_4, (HL_4, LH_4, HH_4) = pywt.dwt2(LL_3, 'haar')
_, _, _, ori_sig = self.__gene_embed_space(HH_3)
sig = self.__extract_sig(ori_sig, self.sig_size**2)
return sig