Lei Mao leimao

In this article, I will share some of my experience on installing NVIDIA driver and CUDA on Linux OS. Here I mainly use Ubuntu as example. Comments for CentOS/Fedora are also provided as much as I can.

-ss 14:55 gives the timestamp where I want FFmpeg to start, as a duration string.
-t 5 says how much I want FFmpeg to decode, using the same duration syntax as for -ss.
-s 480x270 tells FFmpeg to resize the video output to 480 by 270 pixels.
-f image2 selects the output format, a series of still images — make sure there are leading zeros in filename.

##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

	# @Author: xiewenqian <int>
	# @Date: 2016-11-28T20:35:09+08:00
	# @Email: [email protected]
	# @Last modified by: int
	# @Last modified time: 2016-12-01T19:32:48+08:00


	import pandas as pd
	from pymongo import MongoClient

	# Create a simple TF Graph
	# By Omid Alemi - Jan 2017
	# Works with TF <r1.0

	import tensorflow as tf

	I = tf.placeholder(tf.float32, shape=[None,3], name='I') # input
	W = tf.Variable(tf.zeros_initializer(shape=[3,2]), dtype=tf.float32, name='W') # weights
	b = tf.Variable(tf.zeros_initializer(shape=[2]), dtype=tf.float32, name='b') # biases
	O = tf.nn.relu(tf.matmul(I, W) + b, name='O') # activation / output

	""" Trains an agent with (stochastic) Policy Gradients on Pong. Uses OpenAI Gym. """
	import numpy as np
	import cPickle as pickle
	import gym

	# hyperparameters
	H = 200 # number of hidden layer neurons
	batch_size = 10 # every how many episodes to do a param update?
	learning_rate = 1e-4
	gamma = 0.99 # discount factor for reward

	from pyspark.sql.types import StringType
	from pyspark.sql.functions import udf

	maturity_udf = udf(lambda age: "adult" if age >=18 else "child", StringType())

	df = spark.createDataFrame([{'name': 'Alice', 'age': 1}])
	df.withColumn("maturity", maturity_udf(df.age))

	df.show()

	#!/usr/bin/python
	import re
	import sys

	def removeComments(text):
	""" remove c-style comments.
	text: blob of text with comments (can include newlines)
	returns: text with comments removed
	"""
	pattern = r"""

Lei Mao leimao

Table of Contents

Install ImageMagick

Pull specific region of frames from video file w/ ffmpeg