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ffmpeg

Converting Audio into Different Formats / Sample Rates

Minimal example: transcode from MP3 to WMA:
ffmpeg -i input.mp3 output.wma

You can get the list of supported formats with:
ffmpeg -formats

Convert WAV to MP3, mix down to mono (use 1 audio channel), set bit rate to 64 kbps and sample rate to 22050 Hz:

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install r-base

sudo add-apt-repository 'deb https://cloud.r-project.org/bin/linux/ubuntu xenial-cran35/'
sudo apt-key adv --keyserver keyserver.ubuntu.com --recv-keys E298A3A825C0D65DFD57CBB651716619E084DAB9
sudo apt update
sudo apt install r-base

install bigstatsr, bigsnpr

# open R

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[TOC]

clone

git clone -b v1.6.1 https://github.com/facebookresearch/faiss.git
cd faiss

requirement

install BLAS

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install kernel

document - https://jupyter.readthedocs.io/en/latest/install-kernel.html

0. switch to the env ready to install & install ipykernel in the env

source activate myenv
pip install ipykernel

1. add python2 kernel

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Install from apt

0. setup

python3 -V
apt update
sudo apt install software-properties-common
sudo add-apt-repository ppa:deadsnakes/ppa
apt update

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import sys
import numpy as np
import pandas as pd
from Trace import Trace
from AES import Sbox, Rcon

CipherCsv, TraceCsv = sys.argv[2], sys.argv[1]
all_trace_df = pd.read_csv("case1/Trace.csv", header=None)
all_cipher_df = pd.read_csv("case1/Ciphertext.csv", header=None)
cipher_state = all_cipher_df.values

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# -*- coding: utf-8 -*-

import tensorflow as tf
import numpy as np
import scipy.misc
import cv2
import facenet

image_size = 200 #don't need equal to real image size, but this value should not small than this
modeldir = '' #change to your model dir [https://drive.google.com/open?id=1EXPBSXwTaqrSC0OhUdXNmKSh9qJUQ55-]

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import tensorflow as tf
gpu_options = tf.GPUOptions(per_process_gpu_memory_fraction=0.3)
sess = tf.Session(config=tf.ConfigProto(gpu_options=gpu_options))

# keras
from keras.backend.tensorflow_backend import set_session
config = tf.ConfigProto()
config.gpu_options.per_process_gpu_memory_fraction = 0.1
#config.gpu_options.allow_growth=True
set_session(tf.Session(config=config))

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from keras.models import Model
from keras.layers import Dense, Embedding, Conv1D, multiply, GlobalMaxPool1D, Input, Reshape, Activation

class Malconv()
    
    def __init__(self, max_len=30000, win_size=500, vocab_size=257):
        inp = Input((max_len,))
        emb = Embedding(vocab_size, 8)(inp)
        
        conv1 = Conv1D(kernel_size = (win_size), filters = 128, strides=(win_size), padding='same')(emb)