##VGG16 model for Keras
This is the Keras model of the 16-layer network used by the VGG team in the ILSVRC-2014 competition.
It has been obtained by directly converting the Caffe model provived by the authors.
Details about the network architecture can be found in the following arXiv paper:
Very Deep Convolutional Networks for Large-Scale Image Recognition
K. Simonyan, A. Zisserman
| from Crypto.Cipher import AES | |
| from Crypto import Random | |
| BS = 16 | |
| pad = lambda s: s + (BS - len(s) % BS) * chr(BS - len(s) % BS) | |
| unpad = lambda s: s[0:-ord(s[-1])] | |
| class AESCipher: | |
| def __init__(self, key): |
| #http://pastebin.com/xGt6vv9R from yardenbar | |
| output { | |
| if [type] == "postfix" { | |
| elasticsearch { | |
| host => [ "ES_HOSTNAME" ] | |
| protocol => "transport" | |
| cluster => "elasticsearch" | |
| index => "postfix-%{+YYYY.MM.dd}" | |
| manage_template => true | |
| template_overwrite => true |
| #!/bin/zsh | |
| # pyenv install for CentOS 6.5 x86_64 | |
| yum install -y gcc gcc-c++ make git patch openssl-devel zlib-devel readline-devel sqlite-devel bzip2-devel | |
| git clone git://github.com/yyuu/pyenv.git ~/.pyenv | |
| export PATH="$HOME/.pyenv/bin:$PATH" | |
| eval "$(pyenv init -)" |