evaluate_metrics_dt1.m

function evaluate_metrics_dt1(output_folder_name,params)
% 
% INPUT:
%   OUTPUT_FOLDER_NAME: name of the folder where the denoised images are
%   stored.
%   TEST_INDICES: indices of the images.E.g., test_indices = 1:18
%   PREPROCESS: function handle to run over the image before further
%   processing.
%   
% OUTPUT:
%   computed metric values are stored in an Excel file into the output
%   folder. Also, a table is shown to the user.
% 
% USAGE:
%   benchmark_bm4d_dt1
%   evaluate_metrics_dt1("benchmark_bm4d_dt1",1)
% 
% 

test_indices = params.test_indices;

% assert(size(params.frame_numbers,1) == length(test_indices))

if isfield(params,'preprocess')
    preprocess = params.preprocess;
else
    preprocess = -1;
end


% **
% Settings
% ** 

addpath('./Metrics')

dataset_path = './Datasets/dt1_Bioptigen_SDOCT/';

% output images will be saved here:
result_path = fullfile('./Results/',output_folder_name);

rois_path = './Metrics/rois_for_dt1/';

background_indices = [1]; % indices of ROIs which are background regions

N_images = length(test_indices); % Number of output images

column_names={'PSNR','SSIM','MSR','CNR','ENL','TP','EP'};
N_metrics = length(column_names); % PSNR, SSIM, MSR, CNR, ENL


% pre-allocating memory for creating a table of measures.
metric_values=zeros(N_images,N_metrics);% #images by #quality measures & time
row_names=cell(N_images,1);


% **
% loop over all outputs/results
% **

whandle = waitbar(0,'Please wait...');
for ii = 1:N_images
    waitbar(ii / N_images)
    
    img_number = test_indices(ii);
    
    % **
    % Read data
    % **
    
    % read ground-truth and noisy image
    strnumber = num2str(img_number);
    
    input_path = fullfile(dataset_path,strnumber);
    imn = double(imread(fullfile(input_path,'test.tif')));
    Truth= double(imread(fullfile(input_path,'average.tif')));
    
    imn = make_size_even(imn);
    Truth = make_size_even(Truth);   
        
    % read the output/denoised image
    output_filename = sprintf('%0.2d.tif',img_number);
    try
        im_out_path = fullfile(result_path,output_filename);
        im_out = double(imread(im_out_path));
    catch
        msg = 'The file does not exist:';
        close(whandle)
        error('INPUT ERROR: \n %s\n%s',msg,im_out_path)
    end

    % load ROIs
    posfname=[rois_path sprintf('%0.2d',img_number)];
    load(posfname,'pos');
    
    [roi,~] = get_roi_pos(im_out,pos);
    
    
    if ~isnumeric(preprocess)
        Truth = preprocess(Truth);
        im_out = preprocess(im_out);
    end
    
    % **
    % Compute Metrics
    % **
    
    [PSNR,SSIM]=comp_psnr_ssim(Truth ,im_out);
    
    [MSR,CNR,ENL] = comp_MSR_CNR_ENL(roi,background_indices);
    
    TP = comp_TP(im_out,imn,pos,background_indices);
    EP = comp_EP(im_out,imn,pos,background_indices);
     
    
    metric_values(ii,:) = [PSNR,SSIM,MSR,CNR,ENL,TP,EP];
    
    
    row_names{ii} = output_filename;
    
end
close(whandle) 

% Add the average row
dim = 1;
metric_values(ii+1,:) = mean(metric_values(1:N_images,:),dim);
row_names{ii+1} = 'Avg.';


% **
% Save the metric results in a table and store it in a excel file
% **

assert(size(metric_values,2) == (length(column_names)),...
    "metric results does not compatible with the number of columns")


table_results = array2table(metric_values);
table_results.Properties.VariableNames = column_names;
table_results.Properties.RowNames = row_names;
table_results.Properties.DimensionNames{1} = 'ImageNumber';

excel_file_path = fullfile(result_path,strcat(output_folder_name,'.xlsx'));


% The 1st way: Create a new file
% writetable(table_results,excel_file_path,...
%     'Sheet',1,'Range','B2',...
%     'WriteRowNames',true,...
%     'FileType','spreadsheet')
% 
% The 2nd way: Append to the current file
writetable(table_results,excel_file_path,...
    'Sheet',1,...
    'WriteRowNames',true,...
    'FileType','spreadsheet','WriteMode','Append')


fprintf('\nThe numerical results are stored in:\n%s\n',excel_file_path);

% **
% draw a table
% **

fh=figure;
columns_formats=repmat({'short g'},1,numel(column_names));

ui_table_obj = ...
    uitable('Parent', fh,...
    'Data', metric_values,...
    'RowName',row_names,...
    'ColumnName', column_names,...
    'ColumnFormat', columns_formats,...
    'Units','normalized','Position',[0 0 1 1]);
ui_table_obj.FontSize=12;
fh.Name=[output_folder_name];% figure title