PharrellWANG

#!/bin/bash

################################################################################
###                       OpenCV3 Installation Script                        ###
################################################################################

### Dependencies
sudo apt-get update
sudo apt-get install -y build-essential git libgtk2.0-dev pkg-config \
                        python-numpy python-dev libavcodec-dev libavformat-dev \

PharrellWANG

#!/bin/bash

################################################################################
###                       OpenCV3 Installation Script                        ###
################################################################################

### Dependencies
sudo apt-get update
sudo apt-get install -y build-essential git libgtk2.0-dev pkg-config \
                        python-numpy python-dev libavcodec-dev libavformat-dev \

PharrellWANG

Enterprise: NJVYC-BMHX2-G77MM-4XJMR-6Q8QF
Professional: KBJFW-NXHK6-W4WJM-CRMQB-G3CDH

Keys are generic ones. These are the same from MSDN account. 


Product Key	: -6Q8QF
Validity	: Valid
Product ID	: 00369-90000-00000-AA703
Advanced ID	: XXXXX-03699-000-000000-00-1032-9200.0000-0672017

PharrellWANG

#!/bin/bash
# 
# Download the Large-scale CelebFaces Attributes (CelebA) Dataset
# from their Google Drive link.
# 
# CelebA: http://mmlab.ie.cuhk.edu.hk/projects/CelebA.html
# 
# Google Drive: https://drive.google.com/drive/folders/0B7EVK8r0v71pWEZsZE9oNnFzTm8

python3 get_drive_file.py 0B7EVK8r0v71pZjFTYXZWM3FlRnM celebA.zip

PharrellWANG

import tensorflow as tf
import numpy as np
import uuid

x = tf.placeholder(shape=[None, 3], dtype=tf.float32)
nn = tf.layers.dense(x, 3, activation=tf.nn.sigmoid)
nn = tf.layers.dense(nn, 5, activation=tf.nn.sigmoid)
encoded = tf.layers.dense(nn, 2, activation=tf.nn.sigmoid)
nn = tf.layers.dense(encoded, 5, activation=tf.nn.sigmoid)
nn = tf.layers.dense(nn, 3, activation=tf.nn.sigmoid)

PharrellWANG

from PIL import Image
import sys
import os
import math
import numpy as np

###########################################################################################
# script to generate moving mnist video dataset (frame by frame) as described in
# [1] arXiv:1502.04681 - Unsupervised Learning of Video Representations Using LSTMs
#     Srivastava et al

PharrellWANG

YouTube video stream format codes

Comprehensive list of YouTube format code itags

itag Code	Container	Content	Resolution	Bitrate	Range	VR / 3D
5	flv	audio/video	240p	-	-	-
6	flv	audio/video	270p	-	-	-
17	3gp	audio/video	144p	-	-	-
18	mp4	audio/video	360p	-	-	-
22	mp4	audio/video	720p	-	-	-

PharrellWANG

Keybase proof

I hereby claim:

• I am pharrellwang on github.
• I am aliwang (https://keybase.io/aliwang) on keybase.
• I have a public key ASB5ajalS_G-aneb_wQ9P-JKYyc7wIgtkMOfyRa8I_zntgo

To claim this, I am signing this object:

PharrellWANG

PharrellWANG

Install Zsh and Oh-my-zsh on CentOS 7

Based on this article

ALL INSTALLATIONS ASSUME YES WHEN PROMPTED, that's what -y does

This script can be copy paste to ssh as is. No hands installation. :-)

yum install zsh -y