You are an expert in writing code in many different languages. Your goal is to perform code completion for the following code, keeping in mind the rest of the code and the file meta data.
    Metadata details:
    filename: dbFnEvaluateMatchingHistoMarginals.m
    path of file: ./repos/Image-Harmonization-Dataset-iHarmony4/Lalonde and Efros/colorStatistics/mycode
    
    the code of the file until where you have to start completion: %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% function dbFnEvaluateMatchingHistoMarginals(annotation, dbPath, outputBasePath, varargin)
%   Evaluates whether an image matches its expected color distributions
%   (1st and 2nd order). Based solely on histogram comparison.
% 
% Input parameters:
%
%   - varargin: Possible values:
%     - 'Recompute':
%       - 0: (default) will not compute the histogram when results are
%         already available. 
%       - 1: will re-compute histogram no matter what
%
% Output parameters:
%
%    
%
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
function dbFnEvaluateMatchingHistoMarginals(annotation, dbPath, outputBasePath, varargin)%%
% load tmp.mat;
 
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% Copyright 2006-2007 Jean-Francois Lalonde
% Carnegie Mellon University
% Do not distribute
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%

%% Initialize
addpath ../../3rd_party/parseArgs;
addpath ../../3rd_party/color;
addpath ../../3rd_party/LabelMeToolbox/;
addpath ../database;
addpath ../histogram;
addpath ../xml;

nbBinsMarginal1stOrder = 256;
nbBinsMarginal2ndOrder = 128;
nbBinsPairwise1stOrder = 64;
nbBinsPairwise2ndOrder = 32;

% read arguments
defaultArgs = struct('ColorSpace', [], ...
    'Histo1stOrderMarginal', [], ...
    'Histo2ndOrderMarginal', [], ...
    'Histo1stOrderPairwise', [], ...
    'Histo2ndOrderPairwise', []);
args = parseargs(defaultArgs, varargin{:});

% read the image and the xml information
imgPath = fullfile(dbPath, annotation.image.folder, annotation.image.filename);
img = imread(imgPath);

[pathstr, fileName, ext, versn] = fileparts(annotation.image.filename);
xmlPath = fullfile(outputBasePath, annotation.image.folder, sprintf('%s.xml', fileName));
imgInfo = readStructFromXML(xmlPath);

% make sure the image isn't too big. Resize to 256x256
img = imresize(img, [256,256], 'bilinear');

if strcmp(args.ColorSpace, 'lab')
    % convert the image to the L*a*b* color space (if asked by the user)
    fprintf('Converting to L*a*b*...');
    img = rgb2lab(img);
    
    % L = [0 100]
    % a = [-100 100]
    % b = [-100 100]
    mins = [0 -100 -100];
    maxs = [100 100 100];
    type = 1;
  
elseif strcmp(args.ColorSpace, 'rgb')
    mins = [0 0 0];
    maxs = [255 255 255];
    type = 2;

elseif strcmp(args.ColorSpace, 'hsv')
    % convert the image to the HSV color space
    fprint
    
function dbFnEvaluateMatchingHistoMarginals(annotation, dbPath, outputBasePath, varargin)
%   Evaluates whether an image matches its expected color distributions
%   (1st and 2nd order). Based solely on histogram comparison.
% 
% Input parameters:
%
%   - varargin: Possible values:
%     - 'Recompute':
%       - 0: (default) will not compute the histogram when results are
%         already available. 
%       - 1: will re-compute histogram no matter what
%
% Output parameters:
%
%    
%
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
function dbFnEvaluateMatchingHistoMarginals(annotation, dbPath, outputBasePath, varargin)%%
% load tmp.mat;
 
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% Copyright 2006-2007 Jean-Francois Lalonde
% Carnegie Mellon University
% Do not distribute
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%

%% Initialize
addpath ../../3rd_party/parseArgs;
addpath ../../3rd_party/color;
addpath ../../3rd_party/LabelMeToolbox/;
addpath ../database;
addpath ../histogram;
addpath ../xml;

nbBinsMarginal1stOrder = 256;
nbBinsMarginal2ndOrder = 128;
nbBinsPairwise1stOrder = 64;
nbBinsPairwise2ndOrder = 32;

% read arguments
defaultArgs = struct('ColorSpace', [], ...
    'Histo1stOrderMarginal', [], ...
    'Histo2ndOrderMarginal', [], ...
    'Histo1stOrderPairwise', [], ...
    'Histo2ndOrderPairwise', []);
args = parseargs(defaultArgs, varargin{:});

% read the image and the xml information
imgPath = fullfile(dbPath, annotation.image.folder, annotation.image.filename);
img = imread(imgPath);

[pathstr, fileName, ext, versn] = fileparts(annotation.image.filename);
xmlPath = fullfile(outputBasePath, annotation.image.folder, sprintf('%s.xml', fileName));
imgInfo = readStructFromXML(xmlPath);

% make sure the image isn't too big. Resize to 256x256
img = imresize(img, [256,256], 'bilinear');

if strcmp(args.ColorSpace, 'lab')
    % convert the image to the L*a*b* color space (if asked by the user)
    fprintf('Converting to L*a*b*...');
    img = rgb2lab(img);
    
    % L = [0 100]
    % a = [-100 100]
    % b = [-100 100]
    mins = [0 -100 -100];
    maxs = [100 100 100];
    type = 1;
  
elseif strcmp(args.ColorSpace, 'rgb')
    mins = [0 0 0];
    maxs = [255 255 255];
    type = 2;

elseif strcmp(args.ColorSpace, 'hsv')
    % convert the image to the HSV color space
    fprintf('Converting to HSV...');
    img = rgb2hsv(img);
    
    mins = [0 0 0];
    maxs = [1 1 1];
    type = 3;

else
    error('Color Space %s unsupported!', args.ColorSpace);
end