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https://github.com/tesseract-ocr/tesseract.git
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821b151267
git-svn-id: https://tesseract-ocr.googlecode.com/svn/trunk@336 d0cd1f9f-072b-0410-8dd7-cf729c803f20
123 lines
4.7 KiB
C++
123 lines
4.7 KiB
C++
/******************************************************************************
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** Filename: blobclass.c
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** Purpose: High level blob classification and training routines.
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** Author: Dan Johnson
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** History: 7/21/89, DSJ, Created.
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**
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** (c) Copyright Hewlett-Packard Company, 1988.
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** Licensed under the Apache License, Version 2.0 (the "License");
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** you may not use this file except in compliance with the License.
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** You may obtain a copy of the License at
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** http://www.apache.org/licenses/LICENSE-2.0
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** Unless required by applicable law or agreed to in writing, software
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** distributed under the License is distributed on an "AS IS" BASIS,
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** WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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** See the License for the specific language governing permissions and
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** limitations under the License.
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******************************************************************************/
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/**----------------------------------------------------------------------------
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Include Files and Type Defines
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----------------------------------------------------------------------------**/
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#include "blobclass.h"
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#include "fxdefs.h"
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#include "extract.h"
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#include "efio.h"
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#include "callcpp.h"
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#include "chartoname.h"
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#include <math.h>
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#include <stdio.h>
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#include <signal.h>
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#define MAXFILENAME 80
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#define MAXMATCHES 10
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static const char kUnknownFontName[] = "UnknownFont";
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STRING_VAR(classify_font_name, kUnknownFontName,
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"Default font name to be used in training");
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/**----------------------------------------------------------------------------
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Global Data Definitions and Declarations
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----------------------------------------------------------------------------**/
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/* name of current image file being processed */
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extern char imagefile[];
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/**----------------------------------------------------------------------------
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Public Code
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----------------------------------------------------------------------------**/
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/*---------------------------------------------------------------------------*/
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void LearnBlob(const STRING& filename,
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TBLOB * Blob, TEXTROW * Row, const char* BlobText) {
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/*
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** Parameters:
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** Blob blob whose micro-features are to be learned
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** Row row of text that blob came from
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** BlobText text that corresponds to blob
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** TextLength number of characters in blob
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** Globals:
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** imagefile base filename of the page being learned
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** classify_font_name
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** name of font currently being trained on
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** Operation:
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** Extract micro-features from the specified blob and append
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** them to the appropriate file.
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** Return: none
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** Exceptions: none
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** History: 7/28/89, DSJ, Created.
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*/
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#define TRAIN_SUFFIX ".tr"
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static FILE *FeatureFile = NULL;
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STRING Filename(filename);
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// If no fontname was set, try to extract it from the filename
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STRING CurrFontName = classify_font_name;
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if (CurrFontName != kUnknownFontName) {
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// filename is expected to be of the form [lang].[fontname].exp[num]
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// The [lang], [fontname] and [num] fields should not have '.' characters.
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const char *basename = strrchr(filename.string(), '/');
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const char *firstdot = strchr(basename ? basename : filename.string(), '.');
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const char *lastdot = strrchr(filename.string(), '.');
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if (firstdot != lastdot && firstdot != NULL && lastdot != NULL) {
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strncpy(&CurrFontName[0], firstdot + 1, lastdot - firstdot - 1);
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CurrFontName[lastdot - firstdot - 1] = '\0';
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}
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}
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// if a feature file is not yet open, open it
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// the name of the file is the name of the image plus TRAIN_SUFFIX
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if (FeatureFile == NULL) {
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Filename += TRAIN_SUFFIX;
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FeatureFile = Efopen(Filename.string(), "w");
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cprintf("TRAINING ... Font name = %s\n", CurrFontName.string());
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}
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LearnBlob(FeatureFile, Blob, Row, BlobText, CurrFontName.string());
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} // LearnBlob
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void LearnBlob(FILE* FeatureFile, TBLOB* Blob, TEXTROW* Row,
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const char* BlobText, const char* FontName) {
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CHAR_DESC CharDesc;
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LINE_STATS LineStats;
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EnterLearnMode;
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GetLineStatsFromRow(Row, &LineStats);
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CharDesc = ExtractBlobFeatures (Blob, &LineStats);
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if (CharDesc == NULL) {
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cprintf("LearnBLob: CharDesc was NULL. Aborting.\n");
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return;
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}
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// label the features with a class name and font name
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fprintf (FeatureFile, "\n%s %s ", FontName, BlobText);
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// write micro-features to file and clean up
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WriteCharDescription(FeatureFile, CharDesc);
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FreeCharDescription(CharDesc);
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} // LearnBlob
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