function [ds2, elapsedTime]=stDsPredict(ds, opt, showPlot)
% ST (singing transcription) prediction on a given dataset
%
%	Usage:
%		ds2=stDsPredict(ds, opt)
%
%	Example:
%		%dsDir='d:/dataSet/public/MIR-ST500';
%		%ds=stDsRead(dsDir);
%		load mir-st010.mat	% load dataset
%		opt=stDsPredict('defaultOpt');
%		[ds2, time]=stDsPredict(ds, opt, 1);
%		fprintf('Elapsed time = %g sec\n', time);

if nargin<1, selfdemo; return; end
if ischar(ds) && strcmpi(ds, 'defaultOpt')    % Set the default options
	ds2=pv2note('defaultOpt');
	return
end
if nargin<2||isempty(opt), opt=feval(mfilename, 'defaultOpt'); end
if nargin<3, showPlot=0; end

myTic=tic;
dsCount=length(ds);
ds2=ds;
for i=1:dsCount
%	ds(i).noteGt=noteFileRead(ds(i).gtFile);	% Read the groundtruth file
%	fea=jsondecode(fileread(ds(i).feaFile));	% Read the feature file
	pv.pitch=ds(i).fea.vocal_pitch;
	pv.time=ds(i).fea.time;
	ds2(i).notePredicted=pv2note(pv, opt);	% Perform transcription
	if showPlot, fprintf('%d/%d: gtFile=%s, feaFile=%s\n', i, dsCount, ds(i).gtFile, ds(i).feaFile); end
end
elapsedTime=toc(myTic);		% Elapsed time

if showPlot
end
% ====== Self demo
function selfdemo
mObj=mFileParse(which(mfilename));
strEval(mObj.example);