# recover from attack:
recover_crop(template_file='output/截屏攻击2.png',
output_file_name='output/截屏攻击2_还原.png',
loc=(x1, y1, x2, y2),
image_o_shape=image_o_shape)
bwm1 = WaterMark(password_wm=1, password_img=1)
wm_extract = bwm1.extract('output/截屏攻击2_还原.png', wm_shape=len_wm, mode='str')
print("截屏攻击，不知道攻击参数。提取结果：", wm_extract)
assert wm == wm_extract, '提取水印和原水印不一致'
# %% Vertical cut
r = 0.3
att.cut_att_width(input_filename='output/embedded.png',
output_file_name='output/横向裁剪攻击.png',
ratio=r)
att.anti_cut_att(input_filename='output/横向裁剪攻击.png',
output_file_name='output/横向裁剪攻击_填补.png',
origin_shape=ori_img_shape)
# 提取水印
bwm1 = WaterMark(password_wm=1, password_img=1)
wm_extract = bwm1.extract('output/横向裁剪攻击_填补.png', wm_shape=len_wm, mode='str')
print(f"横向裁剪攻击r={r}后的提取结果：", wm_extract)
assert wm == wm_extract, '提取水印和原水印不一致'
# %% horizontal cut
r = 0.4
att.cut_att_height(input_filename='output/embedded.png',
from blind_watermark import att
import numpy as np
# 一次横向裁剪打击
att.cut_att_width('output/打上水印的图.png', 'output/横向裁剪攻击.png', ratio=0.5)
att.anti_cut_att('output/横向裁剪攻击.png',
'output/横向裁剪攻击_填补.png',
origin_shape=(1200, 1920))
# %%提取水印
from blind_watermark import WaterMark
bwm1 = WaterMark(4399, 2333, 36, 20, wm_shape=(128, 128))
bwm1.extract("output/横向裁剪攻击_填补.png", "output/横向裁剪攻击_提取水印.png")
f'Crop attack\'s estimate parameters: x1={x1},y1={y1},x2={x2},y2={y2}. score={score}'
)
# recover from attack:
img_recovered = recover_crop(tem_img=img_attacked,
loc=(x1, y1, x2, y2),
image_o_shape=image_o_shape)
bwm1 = WaterMark(password_wm=1, password_img=1)
wm_extract = bwm1.extract(embed_img=embed_img, wm_shape=len_wm, mode='str')
print("截屏攻击，不知道攻击参数。提取结果：", wm_extract)
assert wm == wm_extract, '提取水印和原水印不一致'
# %% Vertical cut
r = 0.3
img_attacked = att.cut_att_width(input_img=embed_img, ratio=r)
img_recovered = att.anti_cut_att(input_img=img_attacked,
origin_shape=ori_img_shape)
# 提取水印
bwm1 = WaterMark(password_wm=1, password_img=1)
wm_extract = bwm1.extract(embed_img=img_recovered, wm_shape=len_wm, mode='str')
print(f"横向裁剪攻击r={r}后的提取结果：", wm_extract)
assert wm == wm_extract, '提取水印和原水印不一致'
# %% horizontal cut
r = 0.4
img_attacked = att.cut_att_height(input_img=embed_img, ratio=r)
img_recovered = att.anti_cut_att(input_img=img_attacked,
origin_shape=ori_img_shape)
# %%截屏攻击
loc = ((0.3, 0.1), (0.7, 0.9))
att.cut_att('output/embedded.png', 'output/截屏攻击.png', loc=loc)
bwm1 = WaterMark(password_wm=1, password_img=1)
wm_extract = bwm1.extract('output/截屏攻击.png', wm_shape=len_wm, mode='bit')
print("截屏攻击{loc}后的提取结果：".format(loc=loc), wm_extract)
assert np.all(wm == wm_extract), '提取水印和原水印不一致'
# %%
# 一次横向裁剪打击
r = 0.2
att.cut_att_width('output/embedded.png', 'output/横向裁剪攻击.png', ratio=r)
att.anti_cut_att('output/横向裁剪攻击.png',
'output/横向裁剪攻击_填补.png',
origin_shape=ori_img_shape)
# 提取水印
bwm1 = WaterMark(password_wm=1, password_img=1)
wm_extract = bwm1.extract('output/横向裁剪攻击_填补.png', wm_shape=len_wm, mode='bit')
print(f"横向裁剪攻击r={r}后的提取结果：", wm_extract)
assert np.all(wm == wm_extract), '提取水印和原水印不一致'
# %%一次纵向裁剪攻击
ratio = 0.2
att.cut_att_height('output/embedded.png', 'output/纵向裁剪攻击.png', ratio=ratio)
att.anti_cut_att('output/纵向裁剪攻击.png',
from blind_watermark import att
import numpy as np
# 一次横向裁剪打击
att.cut_att_width('output/打上水印的图.png', 'output/横向裁剪攻击.png')
att.anti_cut_att('output/横向裁剪攻击.png',
'output/横向裁剪攻击_填补.png',
origin_shape=(1200, 1920))
# %%提取水印
from blind_watermark import WaterMark
bwm1 = WaterMark(4399, 2333, 36, 20, wm_shape=(128, 128))
bwm1.extract("output/横向裁剪攻击_填补.png", "output/横向裁剪攻击_提取水印.png")