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mko010 committed Feb 12, 2018
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Binary file added MatLab/interfaz.fig
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105 changes: 105 additions & 0 deletions MatLab/interfaz.m
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function varargout = interfaz(varargin)
% INTERFAZ MATLAB code for interfaz.fig
% INTERFAZ, by itself, creates a new INTERFAZ or raises the existing
% singleton*.
%
% H = INTERFAZ returns the handle to a new INTERFAZ or the handle to
% the existing singleton*.
%
% INTERFAZ('CALLBACK',hObject,eventData,handles,...) calls the local
% function named CALLBACK in INTERFAZ.M with the given input arguments.
%
% INTERFAZ('Property','Value',...) creates a new INTERFAZ or raises the
% existing singleton*. Starting from the left, property value pairs are
% applied to the GUI before interfaz_OpeningFcn gets called. An
% unrecognized property name or invalid value makes property application
% stop. All inputs are passed to interfaz_OpeningFcn via varargin.
%
% *See GUI Options on GUIDE's Tools menu. Choose "GUI allows only one
% instance to run (singleton)".
%
% See also: GUIDE, GUIDATA, GUIHANDLES

% Edit the above text to modify the response to help interfaz

% Last Modified by GUIDE v2.5 08-Feb-2018 14:51:57

% Begin initialization code - DO NOT EDIT
gui_Singleton = 1;
gui_State = struct('gui_Name', mfilename, ...
'gui_Singleton', gui_Singleton, ...
'gui_OpeningFcn', @interfaz_OpeningFcn, ...
'gui_OutputFcn', @interfaz_OutputFcn, ...
'gui_LayoutFcn', [] , ...
'gui_Callback', []);
if nargin && ischar(varargin{1})
gui_State.gui_Callback = str2func(varargin{1});
end

if nargout
[varargout{1:nargout}] = gui_mainfcn(gui_State, varargin{:});
else
gui_mainfcn(gui_State, varargin{:});
end
% End initialization code - DO NOT EDIT


% --- Executes just before interfaz is made visible.
function interfaz_OpeningFcn(hObject, eventdata, handles, varargin)
% This function has no output args, see OutputFcn.
% hObject handle to figure
% eventdata reserved - to be defined in a future version of MATLAB
% handles structure with handles and user data (see GUIDATA)
% varargin command line arguments to interfaz (see VARARGIN)

% Choose default command line output for interfaz
handles.output = hObject;

% Update handles structure
guidata(hObject, handles);

% UIWAIT makes interfaz wait for user response (see UIRESUME)
% uiwait(handles.figure1);


% --- Outputs from this function are returned to the command line.
function varargout = interfaz_OutputFcn(hObject, eventdata, handles)
% varargout cell array for returning output args (see VARARGOUT);
% hObject handle to figure
% eventdata reserved - to be defined in a future version of MATLAB
% handles structure with handles and user data (see GUIDATA)

% Get default command line output from handles structure
varargout{1} = handles.output;

% --------------------------------------------------------------------
function Untitled_1_Callback(hObject, eventdata, handles)
% hObject handle to Untitled_1 (see GCBO)
% eventdata reserved - to be defined in a future version of MATLAB
% handles structure with handles and user data (see GUIDATA)
points = [];
[x, y] = getpts;


% --- Executes on button press in load.
function load_Callback(hObject, eventdata, handles)
% hObject handle to load (see GCBO)
% eventdata reserved - to be defined in a future version of MATLAB
% handles structure with handles and user data (see GUIDATA)

[filename pathname] = uigetfile({'*.jpg';'*.bmp';'*.png'},'File Selector');
handles.myImage = strcat(pathname, filename);
axes(handles.image);
imshow(handles.myImage)
set(handles.edit1,'string',filename);
set(handles.edit2,'string',image);

% save the updated handles object
guidata(hObject,handles);


% --- Executes on button press in test.
function test_Callback(hObject, eventdata, handles)
% hObject handle to test (see GCBO)
% eventdata reserved - to be defined in a future version of MATLAB
% handles structure with handles and user data (see GUIDATA)
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151 changes: 151 additions & 0 deletions iDeep/iDeep.m
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function varargout = iDeep(varargin)
% IDEEP MATLAB code for iDeep.fig
% IDEEP, by itself, creates a new IDEEP or raises the existing
% singleton*.
%
% H = IDEEP returns the handle to a new IDEEP or the handle to
% the existing singleton*.
%
% IDEEP('CALLBACK',hObject,eventData,handles,...) calls the local
% function named CALLBACK in IDEEP.M with the given input arguments.
%
% IDEEP('Property','Value',...) creates a new IDEEP or raises the
% existing singleton*. Starting from the left, property value pairs are
% applied to the GUI before iDeep_OpeningFcn gets called. An
% unrecognized property name or invalid value makes property application
% stop. All inputs are passed to iDeep_OpeningFcn via varargin.
%
% *See GUI Options on GUIDE's Tools menu. Choose "GUI allows only one
% instance to run (singleton)".
%
% See also: GUIDE, GUIDATA, GUIHANDLES

% Edit the above text to modify the response to help iDeep

% Last Modified by GUIDE v2.5 09-Feb-2018 21:54:55

% Begin initialization code - DO NOT EDIT
gui_Singleton = 1;
gui_State = struct('gui_Name', mfilename, ...
'gui_Singleton', gui_Singleton, ...
'gui_OpeningFcn', @iDeep_OpeningFcn, ...
'gui_OutputFcn', @iDeep_OutputFcn, ...
'gui_LayoutFcn', [] , ...
'gui_Callback', []);
if nargin && ischar(varargin{1})
gui_State.gui_Callback = str2func(varargin{1});
end

if nargout
[varargout{1:nargout}] = gui_mainfcn(gui_State, varargin{:});
else
gui_mainfcn(gui_State, varargin{:});
end
% End initialization code - DO NOT EDIT


% --- Executes just before iDeep is made visible.
function iDeep_OpeningFcn(hObject, eventdata, handles, varargin)
% This function has no output args, see OutputFcn.
% hObject handle to figure
% eventdata reserved - to be defined in a future version of MATLAB
% handles structure with handles and user data (see GUIDATA)
% varargin command line arguments to iDeep (see VARARGIN)

% Choose default command line output for iDeep
handles.output = hObject;

% Update handles structure
guidata(hObject, handles);

% UIWAIT makes iDeep wait for user response (see UIRESUME)
% uiwait(handles.figure1);


% --- Outputs from this function are returned to the command line.
function varargout = iDeep_OutputFcn(hObject, eventdata, handles)
% varargout cell array for returning output args (see VARARGOUT);
% hObject handle to figure
% eventdata reserved - to be defined in a future version of MATLAB
% handles structure with handles and user data (see GUIDATA)

% Get default command line output from handles structure
varargout{1} = handles.output;


% --- Executes on selection change in popupmenu1.
function popupmenu1_Callback(hObject, eventdata, handles)
% hObject handle to popupmenu1 (see GCBO)
% eventdata reserved - to be defined in a future version of MATLAB
% handles structure with handles and user data (see GUIDATA)

% Hints: contents = cellstr(get(hObject,'String')) returns popupmenu1 contents as cell array
% contents{get(hObject,'Value')} returns selected item from popupmenu1


% --- Executes during object creation, after setting all properties.
function popupmenu1_CreateFcn(hObject, eventdata, handles)
% hObject handle to popupmenu1 (see GCBO)
% eventdata reserved - to be defined in a future version of MATLAB
% handles empty - handles not created until after all CreateFcns called

% Hint: popupmenu controls usually have a white background on Windows.
% See ISPC and COMPUTER.
if ispc && isequal(get(hObject,'BackgroundColor'), get(0,'defaultUicontrolBackgroundColor'))
set(hObject,'BackgroundColor','white');
end


% --- Executes on button press in pushbutton1.
function pushbutton1_Callback(hObject, eventdata, handles)
% hObject handle to pushbutton1 (see GCBO)
% eventdata reserved - to be defined in a future version of MATLAB
% handles structure with handles and user data (see GUIDATA)
[FileName,PathName] = uigetfile('*.mat','Select image');


% --- Executes on button press in pushbutton2.
function pushbutton2_Callback(hObject, eventdata, handles)
% hObject handle to pushbutton2 (see GCBO)
% eventdata reserved - to be defined in a future version of MATLAB
% handles structure with handles and user data (see GUIDATA)
[file,path] = uiputfile('*.mat','Save file name');

% --- Executes on button press in pushbutton3.
function pushbutton3_Callback(hObject, eventdata, handles)
% hObject handle to pushbutton3 (see GCBO)
% eventdata reserved - to be defined in a future version of MATLAB
% handles structure with handles and user data (see GUIDATA)
[FileName,PathName] = uigetfile('*.mat','Select network file');


% --- Executes on button press in pushbutton4.
function pushbutton4_Callback(hObject, eventdata, handles)
% hObject handle to pushbutton4 (see GCBO)
% eventdata reserved - to be defined in a future version of MATLAB
% handles structure with handles and user data (see GUIDATA)

[file,path] = uiputfile('*.mat','Save network');


% --- Executes on button press in pushbutton9.
function pushbutton9_Callback(hObject, eventdata, handles)
% hObject handle to pushbutton9 (see GCBO)
% eventdata reserved - to be defined in a future version of MATLAB
% handles structure with handles and user data (see GUIDATA)


% --- Executes on button press in pushbutton10.
function pushbutton10_Callback(hObject, eventdata, handles)
% hObject handle to pushbutton10 (see GCBO)
% eventdata reserved - to be defined in a future version of MATLAB
% handles structure with handles and user data (see GUIDATA)


% --- Executes on button press in checkbox1.
function checkbox1_Callback(hObject, eventdata, handles)
% hObject handle to checkbox1 (see GCBO)
% eventdata reserved - to be defined in a future version of MATLAB
% handles structure with handles and user data (see GUIDATA)

% Hint: get(hObject,'Value') returns toggle state of checkbox1
40 changes: 40 additions & 0 deletions iDeep/trainCNN.m
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function [net]=trainCNN(X,T)

% X=randn(32,32,1,5000);
% T=categorical(randn(5000,1)>0.5);
% [net]=trainCNN(X,T)

%parameter
s1=size(X); %X puede ser un vector de 32x32x1xN
s2=size(T); %T pueder un verto de Nx1

num_clases=length(unique(T(:)));

% Two class
% define network
ks=3; % kernel size (3x3)
numfilters=[32,64,128]; % cambiar a 128
layers = [imageInputLayer([s1(1) s1(2) 1]);
convolution2dLayer(ks,numfilters(1)); %16 filtros de 5x5
%batchNormalizationLayer();
reluLayer();
maxPooling2dLayer(2,'Stride',1);
convolution2dLayer(ks,numfilters(2)); %16 filtros de 5x5
%batchNormalizationLayer();
reluLayer();
maxPooling2dLayer(2,'Stride',1);
convolution2dLayer(ks,numfilters(3)); %16 filtros de 5x5
%batchNormalizationLayer();
reluLayer();
maxPooling2dLayer(2,'Stride',1);
fullyConnectedLayer(num_clases^2);
%dropoutLayer(0.5);
fullyConnectedLayer(num_clases);
softmaxLayer();
classificationLayer()];

options = trainingOptions('sgdm','MaxEpochs',5,'InitialLearnRate',0.01);
rng('default') % For reproducibility
[net,traininfo] = trainNetwork(X,categorical(single(T)),layers,options);


13 changes: 13 additions & 0 deletions iDeep/trainRF.m
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function [RF]=trainRF(X,T)

% X=randn(5000,32*32);
% T=randn(5000,1)>0.5;
% RF =trainRF(X,T);

%parameters
num_trees=50;

%train
tic
RF = TreeBagger(num_trees,X,T);
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