erogol

function [images, images_RGB] = readDataFromPath(DataPath, image_size)
% Reads the image content of the given rootpath. Assumes that we have a
% root folder includes sub folder for each class of images

images = {};
images_RGB = {};
root_dir = dir(DataPath);
root_dir = root_dir([root_dir.isdir]);
folder_names = {root_dir.name};
root_dir = root_dir(~ismember(folder_names,{'.','..'}))

erogol

function im_array=gridsplit(im,grid_x,grid_y,width_fact,height_fact,left_extra,right_extra,top_extra,bottom_extra)
%Crops a grid of images out of one image
%   im_array=gridsplit(im,...) returns an image array im_array that has
%   size (MxNxPxR) in which M the width, N the height, P the channel and R
%   the amount of images destilled from the grid. So it puts all the 
%   gridparts in R which has size (grid_x*grid_y)
%   You get the idea. Otherwise more info on: www.timzaman.nl
%  
%   grid_x       = Amount of horizontal patches
%   grid_y       = Amount of vertical patches

erogol

function[binary_codes,G_vecs] = WTA_kernel_binary(X,G_vecs,G, K)
% G is number of permutation vectors
% K is the insterest span

if size(G_vecs,1) == 0
        G_vec = zeros(G,size(X,2));
        for i = 1:G 
                G_vecs(i,:) = randperm(size(X,2),size(X,2));
        end
end

erogol

function[ROOT_DIR] = read_dir(PATH)
ROOT_DIR = dir(PATH);
% video_names = ls(fullfile(PATH,'*.mp4'));
file_names = {ROOT_DIR.name};
ROOT_DIR = ROOT_DIR(~ismember(file_names,{'.','..'}));

erogol

%
% Normalize data columnwise to reduce different unit's effect
%

function[X_norm, val] = normalize_data(X,val)

% if ~exist('va','var')
%     [val,ind] = max(X,[],1);
% end
% X_norm = bsxfun(@rdivide, X, val);

erogol

function[X_norm, mu, sigma] = zscore_normalize_data(X, mu, sigma)
X_norm=bsxfun(@minus,X,mu);
X_norm=bsxfun(@rdivide,X_norm,sigma);

erogol

import urllib2
from BeautifulSoup import BeautifulSoup
import pdb
import os
import htmlentitydefs
from BeautifulSoup import BeautifulStoneSoup
import HTMLParser
import cgi

erogol

'''
This code stupidly take the lined list of movie names, suppossely scraped from imdb
and download them as a first instance of YouTube. It also converts the downloaded video mp4
to avi version to be processed in Matlab.

erogol - [email protected]


It needs;
Beautifulsoup 	: easy_install BeautifulSoup -- for scraping

erogol

function mix = gmm(dim, ncentres, covar_type, ppca_dim)
%GMM	Creates a Gaussian mixture model with specified architecture.
%
%	Description
%	 MIX = GMM(DIM, NCENTRES, COVARTYPE) takes the dimension of the space
%	DIM, the number of centres in the mixture model and the type of the
%	mixture model, and returns a data structure MIX. The mixture model
%	type defines the covariance structure of each component  Gaussian:
%	  'spherical' = single variance parameter for each component: stored as a vector
%	  'diag' = diagonal matrix for each component: stored as rows of a matrix

erogol

function [varargout] = rdir(rootdir,varargin)
% Lists the files in a directory and its sub directories. 
% 
% function [D] = rdir(ROOT,TEST)
%
% Recursive directory listing.
%
% ROOT is the directory starting point and includes the 
% wildcard specification.
% The function returns a structure D similar to the one