void LearnBlob(const FEATURE_DEFS_STRUCT &FeatureDefs, FILE* FeatureFile,
TBLOB* Blob, const DENORM& denorm,
const char* BlobText, const char* FontName) {
CHAR_DESC CharDesc;
ASSERT_HOST(FeatureFile != NULL);
CharDesc = ExtractBlobFeatures(FeatureDefs, denorm, Blob);
if (CharDesc == NULL) {
cprintf("LearnBLob: CharDesc was NULL. Aborting.\n");
return;
}
// label the features with a class name and font name
fprintf (FeatureFile, "\n%s %s ", FontName, BlobText);
// write micro-features to file and clean up
WriteCharDescription(FeatureDefs, FeatureFile, CharDesc);
FreeCharDescription(CharDesc);
} // LearnBlob
void LearnBlob(FILE* FeatureFile, TBLOB* Blob, TEXTROW* Row,
const char* BlobText, const char* FontName) {
CHAR_DESC CharDesc;
LINE_STATS LineStats;
EnterLearnMode;
GetLineStatsFromRow(Row, &LineStats);
CharDesc = ExtractBlobFeatures (Blob, &LineStats);
if (CharDesc == NULL) {
cprintf("LearnBLob: CharDesc was NULL. Aborting.\n");
return;
}
// label the features with a class name and font name
fprintf (FeatureFile, "\n%s %s ", FontName, BlobText);
// write micro-features to file and clean up
WriteCharDescription(FeatureFile, CharDesc);
FreeCharDescription(CharDesc);
} // LearnBlob
/*---------------------------------------------------------------------------*/
void
LearnBlob (const STRING& filename,
TBLOB * Blob, TEXTROW * Row, char BlobText[])
/*
** Parameters:
** Blob blob whose micro-features are to be learned
** Row row of text that blob came from
** BlobText text that corresponds to blob
** TextLength number of characters in blob
** Globals:
** imagefile base filename of the page being learned
** classify_font_name
** name of font currently being trained on
** Operation:
** Extract micro-features from the specified blob and append
** them to the appropriate file.
** Return: none
** Exceptions: none
** History: 7/28/89, DSJ, Created.
*/
#define TRAIN_SUFFIX ".tr"
{
static FILE *FeatureFile = NULL;
STRING Filename(filename);
CHAR_DESC CharDesc;
LINE_STATS LineStats;
EnterLearnMode;
GetLineStatsFromRow(Row, &LineStats);
CharDesc = ExtractBlobFeatures (Blob, &LineStats);
if (CharDesc == NULL) {
cprintf("LearnBLob: CharDesc was NULL. Aborting.\n");
return;
}
// If no fontname was set, try to extract it from the filename
char CurrFontName[32] = "";
strncpy(CurrFontName, static_cast<STRING>(classify_font_name).string(), 32);
/*
if (!strcmp(CurrFontName, "UnknownFont")) {
// filename is expected to be of the form [lang].[fontname].exp[num]
// The [lang], [fontname] and [num] fields should not have '.' characters.
const char *basename = strrchr(filename.string(), '/');
const char *firstdot = strchr(basename, '.');
const char *lastdot = strrchr(filename.string(), '.');
if (firstdot != lastdot && firstdot != NULL && lastdot != NULL) {
strncpy(CurrFontName, firstdot + 1, lastdot - firstdot - 1);
}
}
//*/
// if a feature file is not yet open, open it
// the name of the file is the name of the image plus TRAIN_SUFFIX
if (FeatureFile == NULL) {
Filename += TRAIN_SUFFIX;
FeatureFile = Efopen (Filename.string(), "w");
cprintf ("TRAINING ... Font name = %s\n", CurrFontName);
}
// label the features with a class name and font name
fprintf (FeatureFile, "\n%s %s ", CurrFontName, BlobText);
// write micro-features to file and clean up
WriteCharDescription(FeatureFile, CharDesc);
FreeCharDescription(CharDesc);
} // LearnBlob
