/**
* This routine searches thru all of the prototypes in
* Class and returns the id of the proto which would provide
* the best approximation of Prototype. If no close
* approximation can be found, NO_PROTO is returned.
*
* @param Class class to search for matching old proto in
* @param NumMerged # of protos merged into each proto of Class
* @param Prototype new proto to find match for
*
* Globals: none
*
* @return Id of closest proto in Class or NO_PROTO.
* @note Exceptions: none
* @note History: Sat Nov 24 11:42:58 1990, DSJ, Created.
*/
int FindClosestExistingProto(CLASS_TYPE Class, int NumMerged[],
PROTOTYPE *Prototype) {
PROTO_STRUCT NewProto;
PROTO_STRUCT MergedProto;
int Pid;
PROTO Proto;
int BestProto;
FLOAT32 BestMatch;
FLOAT32 Match, OldMatch, NewMatch;
MakeNewFromOld (&NewProto, Prototype);
BestProto = NO_PROTO;
BestMatch = WORST_MATCH_ALLOWED;
for (Pid = 0; Pid < Class->NumProtos; Pid++) {
Proto = ProtoIn(Class, Pid);
ComputeMergedProto(Proto, &NewProto,
(FLOAT32) NumMerged[Pid], 1.0, &MergedProto);
OldMatch = CompareProtos(Proto, &MergedProto);
NewMatch = CompareProtos(&NewProto, &MergedProto);
Match = MIN(OldMatch, NewMatch);
if (Match > BestMatch) {
BestProto = Pid;
BestMatch = Match;
}
}
return BestProto;
} /* FindClosestExistingProto */
/*---------------------------------------------------------------------------*/
int FindClosestExistingProto(CLASS_TYPE Class, int NumMerged[],
PROTOTYPE *Prototype) {
/*
** Parameters:
** Class class to search for matching old proto in
** NumMerged[] # of protos merged into each proto of Class
** Prototype new proto to find match for
** Globals: none
** Operation: This routine searches thru all of the prototypes in
** Class and returns the id of the proto which would provide
** the best approximation of Prototype. If no close
** approximation can be found, NO_PROTO is returned.
** Return: Id of closest proto in Class or NO_PROTO.
** Exceptions: none
** History: Sat Nov 24 11:42:58 1990, DSJ, Created.
*/
PROTO_STRUCT NewProto;
PROTO_STRUCT MergedProto;
int Pid;
PROTO Proto;
int BestProto;
FLOAT32 BestMatch;
FLOAT32 Match, OldMatch, NewMatch;
MakeNewFromOld (&NewProto, Prototype);
BestProto = NO_PROTO;
BestMatch = WORST_MATCH_ALLOWED;
for (Pid = 0; Pid < Class->NumProtos; Pid++) {
Proto = ProtoIn(Class, Pid);
ComputeMergedProto(Proto, &NewProto,
(FLOAT32) NumMerged[Pid], 1.0, &MergedProto);
OldMatch = CompareProtos(Proto, &MergedProto);
NewMatch = CompareProtos(&NewProto, &MergedProto);
Match = MIN(OldMatch, NewMatch);
if (Match > BestMatch) {
BestProto = Pid;
BestMatch = Match;
}
}
return BestProto;
} /* FindClosestExistingProto */
/*---------------------------------------------------------------------------*/
int main (int argc, char **argv) {
/*
** Parameters:
** argc number of command line arguments
** argv array of command line arguments
** Globals: none
** Operation:
** This program reads in a text file consisting of feature
** samples from a training page in the following format:
**
** FontName CharName NumberOfFeatureTypes(N)
** FeatureTypeName1 NumberOfFeatures(M)
** Feature1
** ...
** FeatureM
** FeatureTypeName2 NumberOfFeatures(M)
** Feature1
** ...
** FeatureM
** ...
** FeatureTypeNameN NumberOfFeatures(M)
** Feature1
** ...
** FeatureM
** FontName CharName ...
**
** The result of this program is a binary inttemp file used by
** the OCR engine.
** Return: none
** Exceptions: none
** History: Fri Aug 18 08:56:17 1989, DSJ, Created.
** Mon May 18 1998, Christy Russson, Revistion started.
*/
char *PageName;
FILE *TrainingPage;
FILE *OutFile;
LIST CharList;
CLUSTERER *Clusterer = NULL;
LIST ProtoList = NIL;
LABELEDLIST CharSample;
PROTOTYPE *Prototype;
LIST ClassList = NIL;
int Cid, Pid;
PROTO Proto;
PROTO_STRUCT DummyProto;
BIT_VECTOR Config2;
MERGE_CLASS MergeClass;
INT_TEMPLATES IntTemplates;
LIST pCharList, pProtoList;
char Filename[MAXNAMESIZE];
tesseract::Classify classify;
ParseArguments (argc, argv);
if (InputUnicharsetFile == NULL) {
InputUnicharsetFile = kInputUnicharsetFile;
}
if (OutputUnicharsetFile == NULL) {
OutputUnicharsetFile = kOutputUnicharsetFile;
}
if (!unicharset_training.load_from_file(InputUnicharsetFile)) {
fprintf(stderr, "Failed to load unicharset from file %s\n"
"Building unicharset for mftraining from scratch...\n",
InputUnicharsetFile);
unicharset_training.clear();
// Space character needed to represent NIL classification.
unicharset_training.unichar_insert(" ");
}
if (InputFontInfoFile != NULL) {
FILE* f = fopen(InputFontInfoFile, "r");
if (f == NULL) {
fprintf(stderr, "Failed to load font_properties\n");
} else {
int italic, bold, fixed, serif, fraktur;
while (!feof(f)) {
FontInfo fontinfo;
fontinfo.name = new char[1024];
fontinfo.properties = 0;
if (fscanf(f, "%1024s %i %i %i %i %i\n", fontinfo.name,
&italic, &bold, &fixed, &serif, &fraktur) != 6)
continue;
fontinfo.properties =
(italic << 0) +
(bold << 1) +
(fixed << 2) +
(serif << 3) +
(fraktur << 4);
if (!classify.get_fontinfo_table().contains(fontinfo)) {
classify.get_fontinfo_table().push_back(fontinfo);
} else {
fprintf(stderr, "Font %s already defined\n", fontinfo.name);
return 1;
}
}
fclose(f);
}
}
while ((PageName = GetNextFilename(argc, argv)) != NULL) {
printf ("Reading %s ...\n", PageName);
char *short_name = strrchr(PageName, '/');
if (short_name == NULL)
short_name = PageName;
else
++short_name;
// filename is expected to be of the form [lang].[fontname].exp[num].tr
// If it is, then set short_name to be the [fontname]. Otherwise it is just
// the file basename with the .tr extension removed.
char *font_dot = strchr(short_name, '.');
char *exp_dot = (font_dot != NULL) ? strstr(font_dot, ".exp") : NULL;
if (font_dot != NULL && exp_dot != NULL && font_dot != exp_dot) {
short_name = new_dup(font_dot + 1);
short_name[exp_dot - font_dot - 1] = '\0';
} else {
short_name = new_dup(short_name);
int len = strlen(short_name);
if (!strcmp(short_name + len - 3, ".tr"))
short_name[len - 3] = '\0';
}
int fontinfo_id;
FontInfo fontinfo;
fontinfo.name = short_name;
fontinfo.properties = 0; // Not used to lookup in the table
if (!classify.get_fontinfo_table().contains(fontinfo)) {
fontinfo_id = classify.get_fontinfo_table().push_back(fontinfo);
printf("%s has no defined properties.\n", short_name);
} else {
fontinfo_id = classify.get_fontinfo_table().get_id(fontinfo);
// Update the properties field
fontinfo = classify.get_fontinfo_table().get(fontinfo_id);
delete[] short_name;
}
TrainingPage = Efopen (PageName, "r");
CharList = ReadTrainingSamples (TrainingPage);
fclose (TrainingPage);
//WriteTrainingSamples (Directory, CharList);
pCharList = CharList;
iterate(pCharList) {
//Cluster
CharSample = (LABELEDLIST) first_node (pCharList);
// printf ("\nClustering %s ...", CharSample->Label);
Clusterer = SetUpForClustering(CharSample, PROGRAM_FEATURE_TYPE);
Config.MagicSamples = CharSample->SampleCount;
ProtoList = ClusterSamples(Clusterer, &Config);
CleanUpUnusedData(ProtoList);
//Merge
MergeInsignificantProtos(ProtoList, CharSample->Label,
Clusterer, &Config);
if (strcmp(test_ch, CharSample->Label) == 0)
DisplayProtoList(test_ch, ProtoList);
ProtoList = RemoveInsignificantProtos(ProtoList, ShowSignificantProtos,
ShowInsignificantProtos,
Clusterer->SampleSize);
FreeClusterer(Clusterer);
MergeClass = FindClass (ClassList, CharSample->Label);
if (MergeClass == NULL) {
MergeClass = NewLabeledClass (CharSample->Label);
ClassList = push (ClassList, MergeClass);
}
Cid = AddConfigToClass(MergeClass->Class);
MergeClass->Class->font_set.push_back(fontinfo_id);
pProtoList = ProtoList;
iterate (pProtoList) {
Prototype = (PROTOTYPE *) first_node (pProtoList);
// see if proto can be approximated by existing proto
Pid = FindClosestExistingProto(MergeClass->Class,
MergeClass->NumMerged, Prototype);
if (Pid == NO_PROTO) {
Pid = AddProtoToClass (MergeClass->Class);
Proto = ProtoIn (MergeClass->Class, Pid);
MakeNewFromOld (Proto, Prototype);
MergeClass->NumMerged[Pid] = 1;
}
else {
MakeNewFromOld (&DummyProto, Prototype);
ComputeMergedProto (ProtoIn (MergeClass->Class, Pid), &DummyProto,
(FLOAT32) MergeClass->NumMerged[Pid], 1.0,
ProtoIn (MergeClass->Class, Pid));
MergeClass->NumMerged[Pid] ++;
}
Config2 = MergeClass->Class->Configurations[Cid];
AddProtoToConfig (Pid, Config2);
}
FreeProtoList (&ProtoList);
}
FreeTrainingSamples (CharList);
}
//WriteMergedTrainingSamples(Directory,ClassList);
WriteMicrofeat(Directory, ClassList);
SetUpForFloat2Int(ClassList);
IntTemplates = classify.CreateIntTemplates(TrainingData,
unicharset_training);
strcpy (Filename, "");
if (Directory != NULL) {
strcat (Filename, Directory);
strcat (Filename, "/");
}
strcat (Filename, "inttemp");
#ifdef __UNIX__
OutFile = Efopen (Filename, "w");
#else
OutFile = Efopen (Filename, "wb");
#endif
classify.WriteIntTemplates(OutFile, IntTemplates, unicharset_training);
fclose (OutFile);
strcpy (Filename, "");
if (Directory != NULL) {
strcat (Filename, Directory);
strcat (Filename, "/");
}
strcat (Filename, "pffmtable");
// Now create pffmtable.
WritePFFMTable(IntTemplates, Filename);
// Write updated unicharset to a file.
if (!unicharset_training.save_to_file(OutputUnicharsetFile)) {
fprintf(stderr, "Failed to save unicharset to file %s\n",
OutputUnicharsetFile);
exit(1);
}
printf ("Done!\n"); /**/
FreeLabeledClassList (ClassList);
return 0;
} /* main */
