Harsha K N harshkn

OpenCV Video Writer on Mac OS X

duplicates = multiple editions

Pre-reqs:

Have Python 3 installed. On macOS, this could be installed from homebrew or even via standard Python 3.6 downloaded installer from https://www.python.org/download. On Linux, just use your package manager.
On macOS:
- Install XCode from the Mac App Store (or install the XCode command line utils).
- Have homebrew installed
On Linux:

	typedef struct circular_buffer
	{
	void *buffer; // data buffer
	void *buffer_end; // end of data buffer
	size_t capacity; // maximum number of items in the buffer
	size_t count; // number of items in the buffer
	size_t sz; // size of each item in the buffer
	void *head; // pointer to head
	void *tail; // pointer to tail
	} circular_buffer;

	"""Example of adaptive Lasso to produce event sparser solutions

	Adaptive lasso consists in computing many Lasso with feature
	reweighting. It's also known as iterated L1.
	"""
	# Authors: Alexandre Gramfort <[email protected]>
	#
	# License: BSD (3-clause)

	import numpy as np

	function [Theta] = glasso(S,rho)
	[n,p] = size(S);
	max_iterations = 100;
	t = 1e-4;
	convergence_value = t * meanabs(S - diag(diag(S)));

	% initialise
	W_old = S + rho*eye(p);
	W = W_old;

	import os
	import numpy as np
	from matplotlib import pyplot as plt
	from time import time

	from foxhound import activations
	from foxhound import updates
	from foxhound import inits
	from foxhound.theano_utils import floatX, sharedX

	"""
	Minimal character-level Vanilla RNN model. Written by Andrej Karpathy (@karpathy)
	BSD License
	"""
	import numpy as np

	# data I/O
	data = open('input.txt', 'r').read() # should be simple plain text file
	chars = list(set(data))
	data_size, vocab_size = len(data), len(chars)

	#!/bin/sh

	command="${*}"
	printf "Initialized REPL for `%s`\n" "$command"
	printf "%s> " "$command"
	read -r input
	while [ "$input" != "" ];
	do
	eval "$command $input"
	printf "%s> " "$command"