void calculateFirstWindow( const Image& image ){
/*
Various window sizes have been used for Face Detection.
Commonly they range from 16x16 to 32x32.
24x24 generally provided the most stable detection.
*/
int window[24][24]; // 24 x 24 window
getWindow( image, window, 0, 0 );
// Calculate Haar Images
std::vector< std::vector< double > >
features = calculateHaarFeatures( window );
printFeatures( features ); // Output feature stats
}
Static void doMusic(void)
{
Char STR1[256], STR2[256];
Char STR4[256];
first_paragraph = true;
pmx_preamble_done = false;
bar_no = 1;
*repeat_sign = '\0';
must_respace = false;
must_restyle = false;
do {
final_paragraph = endOfInfile();
memcpy(orig_P, P, sizeof(paragraph));
if (para_len > 0 && !ignore_input && thisCase()) {
if (no_commands_yet) {
interpretCommands();
printFeatures(false);
one_beat = 64 / meterdenom;
full_bar = meternum * one_beat;
if (nvoices > standardPMXvoices) {
sprintf(STR4, "You have %s voices; standard PMX can only handle %s",
toString(STR1, nvoices), toString(STR2, standardPMXvoices));
warning(STR4, !print);
}
initMTX();
initUptext();
initStatus();
initLyrics();
no_commands_yet = false;
}
if (startsWithBracedWord(P[0]))
lyricsParagraph();
else {
musicParagraph();
first_paragraph = false;
writeRepeat(repeat_sign);
}
}
readParagraph(P, orig_line_no, ¶_len);
} while (para_len != 0);
}
/*
Calculate the Haar features each 24 x 24 window for the image.
Output the results.
*/
void calculateAllWindows( const Image& im ){
int rows = im.getNRows(),
cols = im.getNCols();
int window[24][24]; // 24 x 24 window
for( int h = 0; h < rows - 24; h++ ){
for( int w = 0; w < cols - 24; w++ ){
getWindow( im, window, h, w );
// Calculate Haar Images
std::vector< std::vector< double > >
features = calculateHaarFeatures( window );
printFeatures( features ); // Output feature stats
}
}
}
