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/*--------------------------------------------------------------
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Learn.cc -
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readlearnfiles - sources the tcl file to change learn files
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learn(char * tifffile, char * asciifile)
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Performs character learning by reading tiff and ascii translation
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Characters are partitioned into character groups as described
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in system.cc. See learn function for more details
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writeLearnedGroups(char * filename) Writes learned character to file
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readLearnedGroups(char * filename) Reads saved learned characters
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from file.
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---------------------------------------------------------------*/
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#include "tcl_interface.h"
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#include "system.h"
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#include "learn.h"
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#include "Page.h"
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#include "list.h"
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void readLearnFiles()
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/*--------------------------------------------------------------
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Primary Purpose: Sources learnfile.tcl where new learn files can be
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specified without recompiling **/
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{
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docommand("source learnfile.tcl");
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}
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bool whitespace(char c)
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// Returns TRUE if c is a whitespace charater (called by learn.cc)
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{
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if ( c == '\n' || c == '\t' || c == ' ') return TRUE;
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return FALSE;
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}
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bool blank(char * string)
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{
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if (string == NULL) return TRUE;
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int len = strlen(string);
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for(int c=0; c< len; c++)
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{
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if (!(whitespace(string[c])))
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return FALSE;
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}
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return TRUE;
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}
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void printLearnedGroups()
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{
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// Just print these guys out to make sure they are ok.
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for(unsigned int i = 0; i < NumCharGroups; i++)
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for(ListElement * ptr = LearnedGroups[i].first;
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ptr != NULL; ptr = ptr->next)
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{ Component * item = (Component *) ptr->item;
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printf("learned char %s, group %d\n", item->fasciiId,
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item->charGroup);
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}
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}
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int lengthNextWord(char * buffer,int offset, int buflength)
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{
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// counts things in '< >' as one character
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int count;
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for(int c=offset; c < buflength && !(whitespace(buffer[c])); c++)
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{
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if(buffer[c] == '<')
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{
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while((buffer[c] != '>') && (c < buflength))
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c++;
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count++;
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}
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else
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count++;
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}
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return count;
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}
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int learn(Component * comp, char * id, Confidence threshold)
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/*--------------------------------------------------------------
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Primary Purpose: Make a copy of this component and add it to
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LearnedGroups. id is ascii identification.
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Component will only be learned if confidence
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is below threshold or if id and asciiid dont match
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Arguments: comp - component to learn
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id - ascii identification
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threshold - confidence threshold for learning
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Return Value: 1 if component was learned, 0 otherwise
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Rev: 4/25/96
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---------------------------------------------------------------*/
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{
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Component * newcomp;
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if (comp->confid() < threshold || !(strcmp(comp->fasciiId, id)))
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{
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newcomp = comp->copy();
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delete newcomp->fasciiId;
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newcomp->fasciiId = new char[strlen(id)+1];
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strcpy(newcomp->fasciiId , id);
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LearnedGroups[newcomp->charGroup].Append(newcomp);
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return 1;
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}
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return 0;
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}
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void learn(char * tifFile, char * asciiFile, bool synchwords)
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/*--------------------------------------------------------------
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Primary Purpose: Learns from TIFF and ascii file. Groups learned
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characters by baseline into LearnedGroups and
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sets properties.
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Arguments: tiffFile name of a tiff file to learn from
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asciiFile name of an ascii translation file
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Effects: Assumes a one to one correspondence between each connected
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component on a line of the tif file and each character on the corresponding
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line of the ascii file.
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Rev: 4/26/96
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---------------------------------------------------------------------*/
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{
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Page * learnPage = new Page;
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initCharBitsSet();
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if(learnPage->readMap(tifFile) != VALID)
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{
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printf("Problem opening the learn image file (file doesn't exist?)\n");
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return;
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}
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learnPage->setLines();
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learnPage->extractComponents(MinHorizSeparation);
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learnPage->extractWords();
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learn(learnPage, asciiFile, synchwords);
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// delete learnPage;
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}
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void learn(Page * learnPage, char * asciiFile, bool synchWords)
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/*--------------------------------------------------------------
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Primary Purpose: Learns from a Page and an ascii file. Used from
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tcl user interface under File/Learn opation
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Groups learned
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characters by baseline into LearnedGroups and
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sets properties.
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Arguments: tiffFile name of a tiff file to learn from
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asciiFile name of an ascii translation file
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Effects: Assumes a one to one correspondence between each connected
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component on a line of the tif file and each character on the corresponding
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line of the ascii file.
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Rev: 4/26/96
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---------------------------------------------------------------*/
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{
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FILE * transFile;
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transFile = fopen(asciiFile,"r");
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if(!transFile)
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{
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printf("Could not open the ascii learn file");
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return;
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}
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if (LearnedGroups == NULL)
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LearnedGroups = new Components[NumCharGroups];
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int maxCharsPerLine = learnPage->bmap()->imageWidth() / MinLineSize;
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char buffer[maxCharsPerLine];
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int i = -1;
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int buflength=0;
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bool instring= FALSE;
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bool emptyLine;
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Components * components = NULL;
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Words * words;
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Component * item;
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double width, height = 0.0;
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int h;
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words = learnPage->words();
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int c = 0;
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Word * word;
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for (ListElement * ptr = words->first; ptr != NULL &&
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(i < learnPage->numLines()) ; ptr = ptr->next)
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{
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word = (Word *) ptr->item;
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// if new line get new text line
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if (word->characters[0] == '\n' || buflength == 0)
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{
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char * ok;
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do {
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ok =fgets(buffer, maxCharsPerLine, transFile);
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} while (ok && blank(buffer)); // skip blank lines.
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buflength= strlen(buffer);
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components = learnPage->line(++i);
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c =0;
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if (word->characters[0] == '\n') continue;
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}
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// skip over white space
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while(whitespace(buffer[c]) && c < buflength)c++;
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// Make sure we have an equal # of components characters
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if (synchWords &&
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(word->charCount == lengthNextWord(buffer,c,buflength)))
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{
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// skip over this word
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while(!(whitespace(buffer[c])) && c < buflength)
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c++;
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continue; // move on to the next word
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}
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for (int ch = 0; ch < word->charCount; ch++)
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{
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while(whitespace(buffer[c]) && c < buflength)c++;
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item = word->character[ch];
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if (c >= buflength) break;
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// Link string translation to component. Characters between
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// brackets are for one component.
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if(buffer[c] == '<' && !instring)
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{
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instring = TRUE;
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int startString = c;
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while(c++ < buflength && buffer[c] != '>');
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int endString = c+1;
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int stringSize = endString - startString;
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char newstring[stringSize+1];
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strncpy(newstring, &buffer[startString],stringSize);
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newstring[stringSize] = '\0';
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// learn if id's don't match or below threshold
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learn(item, newstring, ConfidenceThreshold);
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c++;
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instring = FALSE;
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}
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else
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{
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char newstring[2];
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newstring[0] = buffer[c++];
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newstring[1]= '\0';
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learn(item, newstring, ConfidenceThreshold);
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}
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LearnedGroups[item->charGroup].Append(item);
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//ptr->item = NULL; // Set to Null in page so it wont get
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// clobbered on delete
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h = item->lr().y() - item->ul().y();
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if (h > height) height = h;
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width = item->lr().x() - item->ul().x();
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if (height/width > MaxHWRatio)
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MaxHWRatio = height/width;
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if (h/width < MinHWRatio)
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MinHWRatio = h/width;
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if (width < MinWidth)
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MinWidth = (int) width;
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}
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}
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if (fgets(buffer, maxCharsPerLine, transFile))
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printf("Uh, oh. There are more characters to learn!\n");
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/* printf("Maximum height/width ratio = %f\n", MaxHWRatio); */
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/* printf("Minimum height/width ratio = %f\n", MinHWRatio); */
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// printLearnedGroups();
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}
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int writeLearnedGroups(char * filename)
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/*--------------------------------------------------------------
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Primary Purpose: Write Learned groups out to file for reading
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in by readLearnedGroups
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Arguments: filename to write learned chars to
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Return Value: 1 if successful 0 if not
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Effects: Writes contents of LearnedGroups array out to filename
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LearnedGroups is an array of lists of components that is decleared
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in system.cc and initialized by the learn() function.
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For each group writes the number of Components the group contains
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followed by the group data.
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Other learned values such as MinWidth MinHWRatio etc are written to
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the file as well.
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Constraints: LearnedGroups must be initialized and filled with learned
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chars before this function is invoked.
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Rev: 11/27 KM
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---------------------------------------------------------------*/
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{
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int status;
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FILE * outfile;
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assert(LearnedGroups != NULL);
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outfile = fopen(filename, "w");
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if (outfile == NULL)
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{
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printf("error openning %s \n", filename);
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return 0;
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}
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// Write global information about learned characters
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fwrite(&NumCharGroups, sizeof(NumCharGroups),1, outfile);
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fwrite(&MaxHWRatio, sizeof(MaxHWRatio),1, outfile);
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fwrite(&MinWidth, sizeof(MinWidth),1,outfile);
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fwrite(&MinHWRatio, sizeof(MinHWRatio),1,outfile);
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for(unsigned int i = 0; i < NumCharGroups; i++)
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{
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unsigned int numChars = LearnedGroups[i].length;
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// Write group number and number of characters
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fwrite(&i, sizeof(i), 1, outfile);
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status = fwrite(&numChars, sizeof(numChars),1,outfile);
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if (status == 0) return 0;
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for(ListElement * ptr = LearnedGroups[i].first;
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ptr != NULL; ptr = ptr->next)
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{
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Component * comp = (Component *) ptr->item;
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status = fwrite(comp, sizeof(Component),1,outfile);
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// printf("\tChar:%c status:%d \n", comp->asciiId(), status);
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int stringSize = strlen(comp->fasciiId) +1;
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status = fwrite(&stringSize, sizeof(stringSize),1,outfile);
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status = fwrite(comp->fasciiId, stringSize,1,outfile);
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for(int p = 0; p < numProperties; p++)
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{
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status = fwrite(&(comp->fproperty[p]),
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sizeof(Property),
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1, outfile);
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if (status == 0)
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{
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printf("Error writing properties of comp %c",
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comp->asciiId());
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return 0;
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}
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}
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}
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}
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status = fclose(outfile);
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if (status == -1) return 0;
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else return 1;
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}
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int readLearnedGroups(char * filename)
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/*--------------------------------------------------------------
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Primary Purpose: Read Learned groups from file that has been
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created by writeLearnedGroups
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Arguments: filename to read learned chars from
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Return Value: 1 if successful 0 if not
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Effects: Reads contents of filename into LearnedGroups array
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LearnedGroups is an array of lists of components that is decleared
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in system.cc and initialized here or in the learn() function.
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Constraints: LearnedGroups must not yet be initialized
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Rev: 11/27 KM
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---------------------------------------------------------------*/
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{
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int status;
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FILE * infile;
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unsigned int numGroups; // # of groups stored in file.
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initCharBitsSet();
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if(LearnedGroups == NULL)
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LearnedGroups = new Components[NumCharGroups];
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infile = fopen(filename, "r");
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if (infile == NULL)
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{
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printf("error openning %s \n", filename);
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return 0;
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}
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// Read Globals
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fread(&numGroups, sizeof(numGroups),1, infile);
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assert(numGroups == NumCharGroups);
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fread(&MaxHWRatio, sizeof(MaxHWRatio),1, infile);
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fread(&MinWidth, sizeof(MinWidth),1,infile);
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fread(&MinHWRatio, sizeof(MinHWRatio),1,infile);
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for(unsigned int i = 0; i < NumCharGroups; i++)
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{
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unsigned int groupnum;
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unsigned int numChars;
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fread(&groupnum, sizeof(groupnum), 1, infile);
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assert(groupnum == i);
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fread(&numChars, sizeof(numChars),1,infile);
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printf("\nReading group %d - %d characters\n",i,numChars);
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for(unsigned int c = 0; c< numChars; c++)
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{
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Component * comp = new Component;
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short int * savepropptr = comp->fproperty;
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status = fread(comp, sizeof(Component),1,infile);
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int stringSize;
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status = fread(&stringSize, sizeof(stringSize),1,infile);
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comp->fasciiId = new char[stringSize];
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status = fread(comp->fasciiId, stringSize,1,infile);
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comp->fproperty = savepropptr;
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for(int p = 0; p < numProperties; p++)
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{
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status = fread(&(comp->fproperty[p]), sizeof(Property),
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1, infile);
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if (status == 0)
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{
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printf("Error reading properties");
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return 0;
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}
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}
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// printf("\tChar:%c status:%d ", comp->asciiId(), status);
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// printVector(comp->properties(), numProperties);
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LearnedGroups[i].Append(comp);
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}
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}
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status = fclose(infile);
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if (status == -1) return 0;
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else return 1;
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}
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void testLearn()
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{
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438 |
learn("/amd/nfs/cochise/home/ee/cs169/fa95/class/cs169-ab/train.tif",
|
|
439 |
"/amd/nfs/cochise/home/ee/cs169/fa95class/cs169-ab/train.txt");
|
|
440 |
}
|
|
441 |
|
|
442 |
/*****************************************************************
|
|
443 |
FUNCTIONS BEYOND THIS POINT ARE FOR AVERAGING LEARNED CHARACTERS
|
|
444 |
AND ARE NOT CURRENTLY USED.
|
|
445 |
*******************************************************************/
|
|
446 |
|
|
447 |
void initLearnedChars()
|
|
448 |
/*--------------------------------------------------------------
|
|
449 |
Primary Purpose: Initializes learned character array. Sets asciiId
|
|
450 |
to array offset.
|
|
451 |
Rev: KM 11/6/95
|
|
452 |
---------------------------------------------------------------*/
|
|
453 |
{
|
|
454 |
LearnedChars = new Component[256];
|
|
455 |
|
|
456 |
for (int i=0; i < 256; i++)
|
|
457 |
{
|
|
458 |
LearnedChars[i].asciiId() = (char)i;
|
|
459 |
}
|
|
460 |
|
|
461 |
}
|
|
462 |
|
|
463 |
void oldlearn(char * tifFile, char * asciiFile)
|
|
464 |
/*--------------------------------------------------------------
|
|
465 |
Primary Purpose: builds property vectors for LearnedChars array
|
|
466 |
Arguments: tiffFile name of a tiff file to learn from
|
|
467 |
asciiFile name of an ascii translation file
|
|
468 |
Effects: Assumes a one to one correspondence between each connected
|
|
469 |
component on a line of the tif file and each character on the corresponding
|
|
470 |
line of the ascii file. For learned characters confidence is set
|
|
471 |
to the number of examples.
|
|
472 |
|
|
473 |
Rev: 11/6/95
|
|
474 |
---------------------------------------------------------------*/
|
|
475 |
{
|
|
476 |
FILE * transFile;
|
|
477 |
transFile = fopen(asciiFile,"r");
|
|
478 |
Page * learnPage = new Page;
|
|
479 |
initCharBitsSet();
|
|
480 |
learnPage->readMap(tifFile);
|
|
481 |
learnPage->setLines();
|
|
482 |
learnPage->extractComponents(MinHorizSeparation); /* why minlinesize? */
|
|
483 |
int maxCharsPerLine = learnPage->bmap()->imageWidth() / MinLineSize;
|
|
484 |
char buffer[maxCharsPerLine];
|
|
485 |
int i = 0;
|
|
486 |
int buflength;
|
|
487 |
bool emptyLine;
|
|
488 |
Components * components;
|
|
489 |
Component * item;
|
|
490 |
int count[256]; // a count of how many of each char have been encountered
|
|
491 |
int prop[256][numProperties]; // Character property sums. Need ints so that
|
|
492 |
// property sum does
|
|
493 |
// not exceed char boundaries
|
|
494 |
char id;
|
|
495 |
|
|
496 |
initLearnedChars();
|
|
497 |
for (i = 0; i < 256; i++)
|
|
498 |
{
|
|
499 |
count[i] = 0;
|
|
500 |
for (int p = 0; p < numProperties; p++)
|
|
501 |
prop[i][p] = 0;
|
|
502 |
}
|
|
503 |
i=0;
|
|
504 |
|
|
505 |
int offset;
|
|
506 |
while (i < learnPage->numLines() &&
|
|
507 |
fgets(buffer, maxCharsPerLine, transFile))
|
|
508 |
{
|
|
509 |
buflength = strlen(buffer);
|
|
510 |
components = learnPage->line(i++);
|
|
511 |
int c = 0;
|
|
512 |
for (ListElement* ptr = components->first; ptr != NULL;
|
|
513 |
ptr = ptr->next)
|
|
514 |
{
|
|
515 |
item = (Component *)(ptr->item);
|
|
516 |
// skip over white space
|
|
517 |
while(whitespace(buffer[c]) && c < buflength)c++;
|
|
518 |
if (c >= buflength)break;
|
|
519 |
id = buffer[c++];
|
|
520 |
count[id]++; // increment character count
|
|
521 |
for (offset=0; offset < numProperties; offset++)
|
|
522 |
prop[id][offset] += (item->properties())[offset];
|
|
523 |
LearnedChars[i].numBits() += item->numBits();
|
|
524 |
}
|
|
525 |
}
|
|
526 |
// now divide by count and put in Learned character
|
|
527 |
for(int j = 0; j < 256; j++)
|
|
528 |
{
|
|
529 |
if(count[j] > 0)
|
|
530 |
{
|
|
531 |
for (int offset=0; offset < numProperties; offset++)
|
|
532 |
prop[j][offset] /= count[j];
|
|
533 |
LearnedChars[j].numBits() /= count[j];
|
|
534 |
LearnedChars[j].confid() = count[j];
|
|
535 |
for (offset=0; offset < numProperties; offset++)
|
|
536 |
(LearnedChars[j].properties())[offset] = prop[j][offset];
|
|
537 |
// printf("%d occurrences of %c\n", count[j], (char)j);
|
|
538 |
printVector(LearnedChars[j].properties(), numProperties);
|
|
539 |
|
|
540 |
}
|
|
541 |
|
|
542 |
}
|
|
543 |
}
|
|
544 |
|
|
545 |
void oldtestLearn()
|
|
546 |
{
|
|
547 |
|
|
548 |
|
|
549 |
learn("train.tif", "train.txt");
|
|
550 |
if (ENABLE_USER_INTERFACE)
|
|
551 |
docommand(".main_window.display.work_space delete IMAGE_TAG");
|
|
552 |
}
|
|
553 |
|
|
554 |
|
|
555 |
|
|
556 |
|
|
557 |
|
|
558 |
|