/*---------------------------------------------------------------------------*/
void ReadTrainingSamples (
FILE *File,
LIST* TrainingSamples)
/*
** Parameters:
** File open text file to read samples from
** Globals: none
** Operation:
** This routine reads training samples from a file and
** places them into a data structure which organizes the
** samples by FontName and CharName. It then returns this
** data structure.
** Return: none
** Exceptions: none
** History: Fri Aug 18 13:11:39 1989, DSJ, Created.
** Tue May 17 1998 simplifications to structure, illiminated
** font, and feature specification levels of structure.
*/
{
char unichar[UNICHAR_LEN + 1];
LABELEDLIST CharSample;
FEATURE_SET FeatureSamples;
CHAR_DESC CharDesc;
int Type, i;
while (fscanf (File, "%s %s", FontName, unichar) == 2) {
CharSample = FindList (*TrainingSamples, unichar);
if (CharSample == NULL) {
CharSample = NewLabeledList (unichar);
*TrainingSamples = push (*TrainingSamples, CharSample);
}
CharDesc = ReadCharDescription (File);
Type = ShortNameToFeatureType(PROGRAM_FEATURE_TYPE);
FeatureSamples = CharDesc->FeatureSets[Type];
for (int feature = 0; feature < FeatureSamples->NumFeatures; ++feature) {
FEATURE f = FeatureSamples->Features[feature];
for (int dim =0; dim < f->Type->NumParams; ++dim)
f->Params[dim] += UniformRandomNumber(-MINSD, MINSD);
}
CharSample->List = push (CharSample->List, FeatureSamples);
CharSample->SampleCount++;
for (i = 0; i < CharDesc->NumFeatureSets; i++)
if (Type != i)
FreeFeatureSet(CharDesc->FeatureSets[i]);
free (CharDesc);
}
} // ReadTrainingSamples
/*---------------------------------------------------------------------------*/
LIST ReadTrainingSamples (
FILE *File)
/*
** Parameters:
** File open text file to read samples from
** Globals: none
** Operation:
** This routine reads training samples from a file and
** places them into a data structure which organizes the
** samples by FontName and CharName. It then returns this
** data structure.
** Return: none
** Exceptions: none
** History: Fri Aug 18 13:11:39 1989, DSJ, Created.
** Tue May 17 1998 simplifications to structure, illiminated
** font, and feature specification levels of structure.
*/
{
char unichar[UNICHAR_LEN + 1];
LABELEDLIST CharSample;
FEATURE_SET FeatureSamples;
LIST TrainingSamples = NIL;
CHAR_DESC CharDesc;
int Type, i;
while (fscanf (File, "%s %s", CTFontName, unichar) == 2) {
if (!unicharset_training.contains_unichar(unichar)) {
unicharset_training.unichar_insert(unichar);
if (unicharset_training.size() > MAX_NUM_CLASSES) {
cprintf("Error: Size of unicharset of mftraining is "
"greater than MAX_NUM_CLASSES\n");
exit(1);
}
}
CharSample = FindList (TrainingSamples, unichar);
if (CharSample == NULL) {
CharSample = NewLabeledList (unichar);
TrainingSamples = push (TrainingSamples, CharSample);
}
CharDesc = ReadCharDescription (File);
Type = ShortNameToFeatureType(PROGRAM_FEATURE_TYPE);
FeatureSamples = CharDesc->FeatureSets[Type];
for (int feature = 0; feature < FeatureSamples->NumFeatures; ++feature) {
FEATURE f = FeatureSamples->Features[feature];
for (int dim =0; dim < f->Type->NumParams; ++dim)
f->Params[dim] += dim == MFDirection ?
UniformRandomNumber(-MINSD_ANGLE, MINSD_ANGLE) :
UniformRandomNumber(-MINSD, MINSD);
}
CharSample->List = push (CharSample->List, FeatureSamples);
CharSample->SampleCount++;
for (i = 0; i < CharDesc->NumFeatureSets; i++)
if (Type != i)
FreeFeatureSet(CharDesc->FeatureSets[i]);
free (CharDesc);
}
return (TrainingSamples);
} /* ReadTrainingSamples */