Example #1
0
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;
  }

  if (ValidCharDescription(FeatureDefs, CharDesc)) {
    // label the features with a class name and font name
    fprintf(FeatureFile, "\n%s %s\n", FontName, BlobText);

    // write micro-features to file and clean up
    WriteCharDescription(FeatureDefs, FeatureFile, CharDesc);
  } else {
    tprintf("Blob learned was invalid!\n");
  }
  FreeCharDescription(CharDesc);

}                                // LearnBlob
/*---------------------------------------------------------------------------*/
void
LearnBlob (TBLOB * Blob, TEXTROW * Row, char BlobText[], int TextLength)
/*
 **      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
 **              FontName        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 MAXFILENAME     80
#define MAXCHARNAME     20
#define MAXFONTNAME     20
#define TRAIN_SUFFIX    ".tr"
{
  static FILE *FeatureFile = NULL;
  char Filename[MAXFILENAME];
  char CharName[MAXCHARNAME];
  CHAR_DESC CharDesc;
  LINE_STATS LineStats;

  EnterLearnMode;

  // throw out blobs which do not represent only one character
  if (TextLength != 1)
    return;

  GetLineStatsFromRow(Row, &LineStats); 

  CharDesc = ExtractBlobFeatures (Blob, &LineStats);

  // 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) {
    strcpy(Filename, imagefile); 
    strcat(Filename, TRAIN_SUFFIX); 
    FeatureFile = Efopen (Filename, "w");

    cprintf ("TRAINING ... Font name = %s.\n", FontName);
  }

  // get the name of the character for this blob
  chartoname (CharName, BlobText[0], "");

  // label the features with a class name and font name
  fprintf (FeatureFile, "\n%s %s ", FontName, CharName);

  // write micro-features to file and clean up
  WriteCharDescription(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
Example #4
0
/*---------------------------------------------------------------------------*/
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