Python Embedded示例

示例#1

文件： stego.py 项目： der-freddy/fromwmtostego

from scipy.signal import find_peaks
import bitarray
from embedded import Embedded
from scipy.signal import find_peaks

file = "44 Pianisten 01-Promenade.wav"

inp = "export"

path = os.path.join(inp, file)
pathtxt = os.path.join(inp, file + "_key.txt")

#path = 'export/44 Pianisten 01-Promenade.wav'
#pathtxt = 'export/44 Pianisten 01-Promenade.wav_key.txt'

cs = Embedded(path, None, None, 100, 8, pathtxt)

#print(cs.msg)

test = cs.ceps[4]

peaks, _ = find_peaks(test[0:44])

ceps_mean = np.mean(test[peaks])

#print(ceps_mean)

peaks, pros = find_peaks(test[0:44], height=ceps_mean, width=1)

#print(peaks)
#print(pros)

示例#2

文件： decode_demo.py 项目： der-freddy/fromwmtostego

import librosa as lro, matplotlib.pyplot as plt, math, librosa.display, numpy as np, bitarray, datetime, os
import random as rn
from audio import Audio
from message import Message
from scipy.signal import find_peaks
import bitarray
from embedded import Embedded

path = '/media/sf_X_DRIVE/Documents/repros/fromwmtostego/export/doku/decay/1_01/'

fig, axs = plt.subplots(3)

file = '44 Pianisten 01-Promenade.wav'
inp = inp = os.path.join(path, file)
pathtxt = os.path.join(path + "txt/", file + "_key.txt")
cs0 = Embedded(inp, None, None, 100, 8, pathtxt)

axs[0].plot(cs0.Ceps(cs0.y)[0:44], label='Echo Signal', color='red')
axs[0].set_title(file)
axs[0].set(ylabel='Magnitude')
axs[0].set_ylim(-0.2, 0.5)

file = '44 Pianisten 03-Promenade 2.wav'
inp = inp = os.path.join(path, file)
pathtxt = os.path.join(path + "txt/", file + "_key.txt")
cs1 = Embedded(inp, None, None, 100, 8, pathtxt)

axs[1].plot(cs1.Ceps(cs1.y)[0:44], label='Echo Signal', color='orange')
axs[1].set_title(file)
axs[1].set(ylabel='Magnitude')
axs[1].set_ylim(-0.2, 0.5)

示例#3

文件： stego_decode.py 项目： der-freddy/fromwmtostego

import librosa as lro, matplotlib.pyplot as plt, math, librosa.display, numpy as np, bitarray, datetime, os, scipy as sc
import random as rn
from audio import Audio
from message import Message
from scipy.signal import find_peaks
import bitarray
from embedded import Embedded

path = 'export/44 Pianisten 01-Promenade.wav'
pathtxt = 'export/44 Pianisten 01-Promenade.wav_key.txt'

cs = Embedded(path, None, None)

text_file = open(pathtxt, 'r')

keyseedtxt = text_file.read().split(';')

msglen = 8

keyseed = np.zeros(len(keyseedtxt), dtype=int)

for i in range(0, len(keyseedtxt)):
    keyseed[i] = keyseedtxt[i]

segsize = int(math.floor(cs.size / msglen))
seedlen = 100
sym = math.floor(segsize / seedlen)
hann = np.hanning(seedlen)
keysig = np.zeros(seedlen * sym)

id_p = np.where(keyseed == 1)

示例#4

文件： anal_peak.py 项目： der-freddy/fromwmtostego

from scipy.signal import find_peaks
import bitarray
from embedded import Embedded
from scipy.signal import find_peaks

file = "44 Pianisten 01-Promenade.wav"

inp = "export"

path = os.path.join(inp, file)
pathtxt = os.path.join(inp, file+"_key.txt")

#path = 'export/44 Pianisten 01-Promenade.wav'
#pathtxt = 'export/44 Pianisten 01-Promenade.wav_key.txt'

cs = Embedded(path, None, None, 100, 8, pathtxt)

#print(cs.msg)



i = 0

peaks = np.zeros(0)


for row in cs.ceps:
	
	peak, _ = find_peaks(row[10:44])

	ceps_mean = np.mean(row[peak+10])

示例#5

from scipy.signal import find_peaks
import bitarray
from embedded import Embedded
from scipy.signal import find_peaks

file = "44 Pianisten 01-Promenade.wav"

inp = "/media/sf_X_DRIVE/Documents/repros/fromwmtostego/export/test_data_03/01010101/"

path = os.path.join(inp, file)
pathtxt = os.path.join(inp, file+"_key.txt")

#path = 'export/44 Pianisten 01-Promenade.wav'
#pathtxt = 'export/44 Pianisten 01-Promenade.wav_key.txt'

cs = Embedded(path, None, None, 100, 8, pathtxt)

text_file = open(pathtxt, 'r')

keyseedtxt = text_file.read().split(';')

msglen = 8

keyseed = np.zeros(len(keyseedtxt), dtype=int)


for i in range(0, len(keyseedtxt)):
	keyseed[i] = keyseedtxt[i]

segsize = int(math.floor(cs.size/msglen))
seedlen = 100

示例#6

import librosa as lro, matplotlib.pyplot as plt, math, librosa.display, numpy as np, bitarray, datetime, os, scipy as sc, random
import random as rn
from audio import Audio
from message import Message
from scipy.signal import find_peaks
import bitarray
from embedded import Embedded
from scipy.signal import find_peaks

#file = "44 Pianisten 01-Promenade.wav"

ipath = '/media/sf_X_DRIVE/Documents/repros/fromwmtostego/export/doku/moving_window_newalgo/data/'

#path = 'export/44 Pianisten 01-Promenade.wav'
#pathtxt = 'export/44 Pianisten 01-Promenade.wav_key.txt'

text = ''

for file in os.listdir(ipath):

    print(file)
    inp = os.path.join(ipath, file)
    pathtxt = os.path.join(ipath + "txt/", file + "_key.txt")
    cs = Embedded(inp, None, None, 100, 8, pathtxt)
    print(cs.peaks)
    print(cs.msg)
    print('-------------------------------')

示例#7

文件： stego_random.py 项目： der-freddy/fromwmtostego

from message import Message
from scipy.signal import find_peaks
import bitarray
from embedded import Embedded

file = "44 Pianisten 01-Promenade.wav"

inp = "export"

path = os.path.join(inp, file)
pathtxt = os.path.join(inp, file + "_key.txt")

#path = 'export/44 Pianisten 01-Promenade.wav'
#pathtxt = 'export/44 Pianisten 01-Promenade.wav_key.txt'

cs = Embedded(path, None, None, 100, 8, pathtxt)

text_file = open(pathtxt, 'r')

keyseedtxt = text_file.read().split(';')

msglen = 8

keyseed = np.zeros(len(keyseedtxt), dtype=int)

for i in range(0, len(keyseedtxt)):
    keyseed[i] = keyseedtxt[i]

segsize = int(math.floor(cs.size / msglen))
seedlen = 100
sym = math.floor(segsize / seedlen)

示例#8

文件： random_decode.py 项目： der-freddy/fromwmtostego

import librosa as lro, matplotlib.pyplot as plt, math,librosa.display, numpy as np, bitarray, datetime, os
import random as rn
from audio import Audio
from message import Message
from scipy.signal import find_peaks
import bitarray
from embedded import Embedded

path = 'export/44 Pianisten 01-Promenade.wav'


cs = Embedded(path, None, None)

randomList = []

leng = 50
han = np.hanning(leng)

for i in range(0, 100):
    # any random numbers from 0 to 1000
	ran = rn.randint(0+i, cs.size-i)
	randomList.append(ran)

print(randomList)

arr = []

for i in randomList:
	win = cs.y[i:i+leng]*han
	arr = np.append(arr, win)

示例#9

import librosa as lro, matplotlib.pyplot as plt, math, librosa.display, numpy as np, bitarray, datetime, os
import random as rn
from audio import Audio
from message import Message
from scipy.signal import find_peaks
import bitarray
from embedded import Embedded

file = '44 Pianisten 01-Promenade.wav'
inp = 'export'
path = os.path.join(inp, file)
pathtxt = os.path.join(inp, file + "_key.txt")

cs = Embedded(path, None, None, 100, 8, pathtxt)

win = 2000
start = 165375
step = 50
j = 0
#arr = np.empty([100,int(start/step)], dtype=float)
arr = np.empty([int(start / step), win], dtype=float)
#print(arr[0,:])

for i in range(start, start + 1000, step):

    ceps = cs.Ceps(cs.y[i:i + win])
    print(ceps.size)
    arr[j, :] = ceps
    j = j + 1

ip = False

示例#10

文件： random_decode.py 项目： der-freddy/fromwmtostego

import librosa as lro, matplotlib.pyplot as plt, math, librosa.display, numpy as np, bitarray, datetime, os
import random as rn
from audio import Audio
from message import Message
from scipy.signal import find_peaks
import bitarray
from embedded import Embedded

file = '44 Pianisten 01-Promenade.wav'
inp = 'export'
path = os.path.join(inp, file)
pathtxt = os.path.join(inp, file + "_key.txt")

cs = Embedded(path, 5, 30, 100, 8, pathtxt)

leng = 100
han = np.hanning(leng)

for j in range(0, 100):

    randomList = []
    for i in range(0, 1000):
        # any random numbers from 0 to 1000
        ran = rn.randint(1, cs.size - leng)
        randomList.append(ran)

    randomList = np.sort(randomList)

    #print(randomList)

    arr = []