cbires.m

function varargout = cbires(varargin)
% CBIRES MATLAB code for cbires.fig
%      CBIRES, by itself, creates a new CBIRES or raises the existing
%      singleton*.
%
%      H = CBIRES returns the handle to a new CBIRES or the handle to
%      the existing singleton*.
%
%      CBIRES('CALLBACK',hObject,eventData,handles,...) calls the local
%      function named CALLBACK in CBIRES.M with the given input arguments.
%
%      CBIRES('Property','Value',...) creates a new CBIRES or raises the
%      existing singleton*.  Starting from the left, property value pairs are
%      applied to the GUI before cbires_OpeningFcn gets called.  An
%      unrecognized property name or invalid value makes property application
%      stop.  All inputs are passed to cbires_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 cbires

% Last Modified by GUIDE v2.5 23-May-2013 22:01:15

% Begin initialization code - DO NOT EDIT
gui_Singleton = 1;
gui_State = struct('gui_Name',       mfilename, ...
    'gui_Singleton',  gui_Singleton, ...
    'gui_OpeningFcn', @cbires_OpeningFcn, ...
    'gui_OutputFcn',  @cbires_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 cbires is made visible.
function cbires_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 cbires (see VARARGIN)

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

% Update handles structure
guidata(hObject, handles);

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


% --- Outputs from this function are returned to the command line.
function varargout = cbires_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 button press in btn_BrowseImage.
function btn_BrowseImage_Callback(hObject, eventdata, handles)
% hObject    handle to btn_BrowseImage (see GCBO)
% eventdata  reserved - to be defined in a future version of MATLAB
% handles    structure with handles and user data (see GUIDATA)

[query_fname, query_pathname] = uigetfile('*.jpg; *.png; *.bmp', 'Select query image');

if (query_fname ~= 0)
    query_fullpath = strcat(query_pathname, query_fname);
    imgInfo = imfinfo(query_fullpath);
    [pathstr, name, ext] = fileparts(query_fullpath); % fiparts returns char type
    
    if ( strcmp(lower(ext), '.jpg') == 1 || strcmp(lower(ext), '.png') == 1 ...
            || strcmp(lower(ext), '.bmp') == 1 )
        
        queryImage = imread( fullfile( pathstr, strcat(name, ext) ) );
%         handles.queryImage = queryImage;
%         guidata(hObject, handles);
        
        % extract query image features
        queryImage = imresize(queryImage, [384 256]);
        if (strcmp(imgInfo.ColorType, 'truecolor') == 1)
            hsvHist = hsvHistogram(queryImage);
            autoCorrelogram = colorAutoCorrelogram(queryImage);
            color_moments = colorMoments(queryImage);
            % for gabor filters we need gary scale image
            img = double(rgb2gray(queryImage))/255;
            [meanAmplitude, msEnergy] = gaborWavelet(img, 4, 6); % 4 = number of scales, 6 = number of orientations
            wavelet_moments = waveletTransform(queryImage, imgInfo.ColorType);
            % construct the queryImage feature vector
            queryImageFeature = [hsvHist autoCorrelogram color_moments meanAmplitude msEnergy wavelet_moments str2num(name)];
        elseif (strcmp(imgInfo.ColorType, 'grayscale') == 1)
            grayHist = imhist(queryImage);
            grayHist = grayHist/sum(grayHist);
            grayHist = grayHist(:)';
            color_moments = [mean(mean(queryImage)) std(std(double(queryImage)))];
            [meanAmplitude, msEnergy] = gaborWavelet(queryImage, 4, 6); % 4 = number of scales, 6 = number of orientations
            wavelet_moments = waveletTransform(queryImage, imgInfo.ColorType);
            % construct the queryImage feature vector
            queryImageFeature = [grayHist color_moments meanAmplitude msEnergy wavelet_moments str2num(name)];
        end
        
        % update handles
        handles.queryImageFeature = queryImageFeature;
        handles.img_ext = ext;
        handles.folder_name = pathstr;
        guidata(hObject, handles);
        helpdlg('Proceed with the query by executing the green button!');
        
        % Clear workspace
        clear('query_fname', 'query_pathname', 'query_fullpath', 'pathstr', ...
            'name', 'ext', 'queryImage', 'hsvHist', 'autoCorrelogram', ...
            'color_moments', 'img', 'meanAmplitude', 'msEnergy', ...
            'wavelet_moments', 'queryImageFeature', 'imgInfo');
    else
        errordlg('You have not selected the correct file type');
    end
else
    return;
end


% --- Executes on selection change in popupmenu_DistanceFunctions.
function popupmenu_DistanceFunctions_Callback(hObject, eventdata, handles)
% hObject    handle to popupmenu_DistanceFunctions (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 popupmenu_DistanceFunctions contents as cell array
%        contents{get(hObject,'Value')} returns selected item from popupmenu_DistanceFunctions

handles.DistanceFunctions = get(handles.popupmenu_DistanceFunctions, 'Value');
guidata(hObject, handles);


% --- Executes during object creation, after setting all properties.
function popupmenu_DistanceFunctions_CreateFcn(hObject, eventdata, handles)
% hObject    handle to popupmenu_DistanceFunctions (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 selection change in popupmenu_NumOfReturnedImages.
function popupmenu_NumOfReturnedImages_Callback(hObject, eventdata, handles)
% hObject    handle to popupmenu_NumOfReturnedImages (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 popupmenu_NumOfReturnedImages contents as cell array
%        contents{get(hObject,'Value')} returns selected item from popupmenu_NumOfReturnedImages

handles.numOfReturnedImages = get(handles.popupmenu_NumOfReturnedImages, 'Value');
guidata(hObject, handles);


% --- Executes during object creation, after setting all properties.
function popupmenu_NumOfReturnedImages_CreateFcn(hObject, eventdata, handles)
% hObject    handle to popupmenu_NumOfReturnedImages (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 btnExecuteQuery.
function btnExecuteQuery_Callback(hObject, eventdata, handles)
% hObject    handle to btnExecuteQuery (see GCBO)
% eventdata  reserved - to be defined in a future version of MATLAB
% handles    structure with handles and user data (see GUIDATA)

% check for image query
if (~isfield(handles, 'queryImageFeature'))
    errordlg('Please select an image first, then choose your similarity metric and num of returned images!');
    return;
end

% check for dataset existence
if (~isfield(handles, 'imageDataset'))
    errordlg('Please load a dataset first. If you dont have one then you should consider creating one!');
    return;
end

% set variables
if (~isfield(handles, 'DistanceFunctions') && ~isfield(handles, 'numOfReturnedImages'))
    metric = get(handles.popupmenu_DistanceFunctions, 'Value');
    numOfReturnedImgs = get(handles.popupmenu_NumOfReturnedImages, 'Value');
elseif (~isfield(handles, 'DistanceFunctions') || ~isfield(handles, 'numOfReturnedImages'))
    if (~isfield(handles, 'DistanceFunctions'))
        metric = get(handles.popupmenu_DistanceFunctions, 'Value');
        numOfReturnedImgs = handles.numOfReturnedImages;
    else
        metric = handles.DistanceFunctions;
        numOfReturnedImgs = get(handles.popupmenu_NumOfReturnedImages, 'Value');
    end
else
    metric = handles.DistanceFunctions;
    numOfReturnedImgs = handles.numOfReturnedImages;
end

if (metric == 1)
    L1(numOfReturnedImgs, handles.queryImageFeature, handles.imageDataset.dataset, handles.folder_name, handles.img_ext);
elseif (metric == 2 || metric == 3 || metric == 4 || metric == 5 || metric == 6  || metric == 7 || metric == 8 || metric == 9 || metric == 10 || metric == 11)
    L2(numOfReturnedImgs, handles.queryImageFeature, handles.imageDataset.dataset, metric, handles.folder_name, handles.img_ext);
else
    relativeDeviation(numOfReturnedImgs, handles.queryImageFeature, handles.imageDataset.dataset, handles.folder_name, handles.img_ext);
end


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

% check for image query
if (~isfield(handles, 'queryImageFeature'))
    errordlg('Please select an image first!');
    return;
end

% check for dataset existence
if (~isfield(handles, 'imageDataset'))
    errordlg('Please load a dataset first. If you dont have one then you should consider creating one!');
    return;
end

numOfReturnedImgs = get(handles.popupmenu_NumOfReturnedImages, 'Value');
metric = get(handles.popupmenu_DistanceFunctions, 'Value');

% call svm function passing as parameters the numOfReturnedImgs, queryImage and the dataset
[~, ~, cmat] = svm(numOfReturnedImgs, handles.imageDataset.dataset, handles.queryImageFeature, metric, handles.folder_name, handles.img_ext);

% plot confusion matrix
opt = confMatPlot('defaultOpt');
opt.className = {
    'Africa', 'Beach', 'Monuments', ...
    'Buses', 'Dinosaurs', 'Elephants', ...
    'Flowers', 'Horses', 'Mountains', ...
    'Food'
    };
opt.mode = 'both';
figure('Name', 'Confusion Matrix');
confMatPlot(cmat, opt);
xlabel('Confusion Matrix');



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

if (~isfield(handles, 'imageDataset'))
    errordlg('Please select a dataset first!');
    return;
end

% set variables
numOfReturnedImgs = 20;
database = handles.imageDataset.dataset;
metric =  get(handles.popupmenu_DistanceFunctions, 'Value');

precAndRecall = zeros(2, 10);

for k = 1:15
    randImgName = randi([0 999], 1);
    randStrName = int2str(randImgName);
    randStrName = strcat('images\', randStrName, '.jpg');
    randQueryImg = imread(randStrName);
    
    % extract query image features
    queryImage = imresize(randQueryImg, [384 256]);
    hsvHist = hsvHistogram(queryImage);
    autoCorrelogram = colorAutoCorrelogram(queryImage);
    color_moments = colorMoments(queryImage);
    % for gabor filters we need gary scale image
    img = double(rgb2gray(queryImage))/255;
    [meanAmplitude, msEnergy] = gaborWavelet(img, 4, 6); % 4 = number of scales, 6 = number of orientations
    wavelet_moments = waveletTransform(queryImage, imgInfo.ColorType);
    % construct the queryImage feature vector
    queryImageFeature = [hsvHist autoCorrelogram color_moments meanAmplitude msEnergy wavelet_moments randImgName];
    
    disp(['Random Image = ', num2str(randImgName), '.jpg']);
    [precision, recall] = svm(numOfReturnedImgs, database, queryImageFeature, metric);
    precAndRecall(1, k) = precision;
    precAndRecall(2, k) = recall;
end

figure;
plot(precAndRecall(2, :), precAndRecall(1, :), '--mo');
xlabel('Recall'), ylabel('Precision');
title('Precision and Recall');
legend('Recall & Precision', 'Location', 'NorthWest');


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

% select image directory
folder_name = uigetdir(pwd, 'Select the directory of images');
if ( folder_name ~= 0 )
    handles.folder_name = folder_name;
    guidata(hObject, handles);
else
    return;
end


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

if (~isfield(handles, 'folder_name'))
    errordlg('Please select an image directory first!');
    return;
end

% construct folder name foreach image type
pngImagesDir = fullfile(handles.folder_name, '*.png');
jpgImagesDir = fullfile(handles.folder_name, '*.jpg');
bmpImagesDir = fullfile(handles.folder_name, '*.bmp');

% calculate total number of images
num_of_png_images = numel( dir(pngImagesDir) );
num_of_jpg_images = numel( dir(jpgImagesDir) );
num_of_bmp_images = numel( dir(bmpImagesDir) );
totalImages = num_of_png_images + num_of_jpg_images + num_of_bmp_images;

jpg_files = dir(jpgImagesDir);
png_files = dir(pngImagesDir);
bmp_files = dir(bmpImagesDir);

if ( ~isempty( jpg_files ) || ~isempty( png_files ) || ~isempty( bmp_files ) )
    % read jpg images from stored folder name
    % directory and construct the feature dataset
    jpg_counter = 0;
    png_counter = 0;
    bmp_counter = 0;
    oldHisv = 0;
    oldautoCorrelogram = 0;
    for k = 1:totalImages
        
        if ( (num_of_jpg_images - jpg_counter) > 0)
            imgInfoJPG = imfinfo( fullfile( handles.folder_name, jpg_files(jpg_counter+1).name ) );
            if ( strcmp( lower(imgInfoJPG.Format), 'jpg') == 1 )
                % read images
                sprintf('%s \n', jpg_files(jpg_counter+1).name)
                % extract features
                image = imread( fullfile( handles.folder_name, jpg_files(jpg_counter+1).name ) );
                [pathstr, name, ext] = fileparts( fullfile( handles.folder_name, jpg_files(jpg_counter+1).name ) );
                image = imresize(image, [384 256]);
            end
            
            jpg_counter = jpg_counter + 1;
            
        elseif ( (num_of_png_images - png_counter) > 0)
            imgInfoPNG = imfinfo( fullfile( handles.folder_name, png_files(png_counter+1).name ) );
            if ( strcmp( lower(imgInfoPNG.Format), 'png') == 1 )
                % read images
                sprintf('%s \n', png_files(png_counter+1).name)
                % extract features
                image = imread( fullfile( handles.folder_name, png_files(png_counter+1).name ) );
                [pathstr, name, ext] = fileparts( fullfile( handles.folder_name, png_files(png_counter+1).name ) );
                image = imresize(image, [384 256]);
            end
            
            png_counter = png_counter + 1;
            
        elseif ( (num_of_bmp_images - bmp_counter) > 0)
            imgInfoBMP = imfinfo( fullfile( handles.folder_name, bmp_files(bmp_counter+1).name ) );
            if ( strcmp( lower(imgInfoBMP.Format), 'bmp') == 1 )
                % read images
                sprintf('%s \n', bmp_files(bmp_counter+1).name)
                % extract features
                image = imread( fullfile( handles.folder_name, bmp_files(bmp_counter+1).name ) );
                handle = image(image);
                imgmodel = imagemodel(handle);
                str = getImageType(imgmodel);
                disp([str])
                return;

                [pathstr, name, ext] = fileparts( fullfile( handles.folder_name, bmp_files(bmp_counter+1).name ) );
                image = imresize(image, [384 256]);
            end
            
            bmp_counter = bmp_counter + 1;
            
        end
        
        switch (ext)
            case '.jpg'
                imgInfo = imgInfoJPG;
            case '.png'
                imgInfo = imgInfoPNG;
            case '.bmp'
                imgInfo = imgInfoBMP;
        end
        
        if (strcmp(imgInfo.ColorType, 'grayscale') == 1)
            grayHist = imhist(image);
            grayHist = grayHist/sum(grayHist);
            grayHist = grayHist(:)';
            color_moments = [mean(mean(image)) std(std(double(image)))];
            [meanAmplitude, msEnergy] = gaborWavelet(image, 4, 6); % 4 = number of scales, 6 = number of orientations
            wavelet_moments = waveletTransform(image, imgInfo.ColorType);
            % construct the dataset
            set = [grayHist color_moments meanAmplitude msEnergy wavelet_moments];
        elseif (strcmp(imgInfo.ColorType, 'truecolor') == 1)
            hsvHist = 0;
            try
                hsvHist = hsvHistogram(image);
                autoCorrelogram = colorAutoCorrelogram(image);
                oldHisv = hsvHist;
                oldautoCorrelogram = autoCorrelogram;
            catch
                hsvHist = oldHisv;
                autoCorrelogram = oldautoCorrelogram;
            end
            color_moments = colorMoments(image);
            % for gabor filters we need gray scale image
            img = double(rgb2gray(image))/255;
            [meanAmplitude, msEnergy] = gaborWavelet(img, 4, 6); % 4 = number of scales, 6 = number of orientations
            wavelet_moments = waveletTransform(image, imgInfo.ColorType);
            % construct the dataset
            set = [hsvHist autoCorrelogram color_moments meanAmplitude msEnergy wavelet_moments];
        end

        % add to the last column the name of image file we are processing at
        % the moment
        dataset(k, :) = [set str2num(name)];
        
        % clear workspace
        clear('image', 'img', 'hsvHist', 'autoCorrelogram', 'color_moments', ...
            'gabor_wavelet', 'wavelet_moments', 'set', 'imgInfoJPG', 'imgInfoPNG', ...
            'imgInfoGIF', 'imgInfo');
    end
    
    % prompt to save dataset
    uisave('dataset', 'dataset1');
    % save('dataset.mat', 'dataset', '-mat');
    clear('dataset', 'jpg_counter', 'png_counter', 'bmp_counter');
end


% --- Executes on button press in btn_LoadDataset.
function btn_LoadDataset_Callback(hObject, eventdata, handles)
% hObject    handle to btn_LoadDataset (see GCBO)
% eventdata  reserved - to be defined in a future version of MATLAB
% handles    structure with handles and user data (see GUIDATA)
[fname, pthname] = uigetfile('*.mat', 'Select the Dataset');
if (fname ~= 0)
    dataset_fullpath = strcat(pthname, fname);
    [pathstr, name, ext] = fileparts(dataset_fullpath);
    if ( strcmp(lower(ext), '.mat') == 1)
        filename = fullfile( pathstr, strcat(name, ext) );
        handles.imageDataset = load(filename);
        guidata(hObject, handles);
        % make dataset visible from workspace
        % assignin('base', 'database', handles.imageDataset.dataset);
        helpdlg('Dataset loaded successfuly!');
    else
        errordlg('You have not selected the correct file type');
    end
else
    return;
end