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c46e773758
It is not necessary to check for null pointers. Remove also unneeded delete operations and add missing delete operations in cube/bmp_8.cpp. Simplify also a conditional statement in cube/cube_object.cpp. Signed-off-by: Stefan Weil <sw@weilnetz.de>
284 lines
8.1 KiB
C++
284 lines
8.1 KiB
C++
/**********************************************************************
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* File: cube_object.cpp
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* Description: Implementation of the Cube Object Class
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* Author: Ahmad Abdulkader
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* Created: 2007
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*
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* (C) Copyright 2008, Google Inc.
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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 <math.h>
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#include "cube_object.h"
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#include "cube_utils.h"
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#include "word_list_lang_model.h"
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namespace tesseract {
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CubeObject::CubeObject(CubeRecoContext *cntxt, CharSamp *char_samp) {
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Init();
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char_samp_ = char_samp;
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cntxt_ = cntxt;
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}
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CubeObject::CubeObject(CubeRecoContext *cntxt, Pix *pix,
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int left, int top, int wid, int hgt) {
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Init();
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char_samp_ = CubeUtils::CharSampleFromPix(pix, left, top, wid, hgt);
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own_char_samp_ = true;
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cntxt_ = cntxt;
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}
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// Data member initialization function
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void CubeObject::Init() {
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char_samp_ = NULL;
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own_char_samp_ = false;
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alt_list_ = NULL;
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srch_obj_ = NULL;
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deslanted_alt_list_ = NULL;
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deslanted_srch_obj_ = NULL;
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deslanted_ = false;
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deslanted_char_samp_ = NULL;
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beam_obj_ = NULL;
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deslanted_beam_obj_ = NULL;
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cntxt_ = NULL;
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}
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// Cleanup function
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void CubeObject::Cleanup() {
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delete alt_list_;
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alt_list_ = NULL;
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delete deslanted_alt_list_;
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deslanted_alt_list_ = NULL;
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}
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CubeObject::~CubeObject() {
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if (own_char_samp_ == true) {
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delete char_samp_;
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char_samp_ = NULL;
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}
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delete srch_obj_;
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srch_obj_ = NULL;
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delete deslanted_srch_obj_;
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deslanted_srch_obj_ = NULL;
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delete beam_obj_;
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beam_obj_ = NULL;
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delete deslanted_beam_obj_;
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deslanted_beam_obj_ = NULL;
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delete deslanted_char_samp_;
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deslanted_char_samp_ = NULL;
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Cleanup();
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}
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/**
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* Actually do the recognition using the specified language mode. If none
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* is specified, the default language model in the CubeRecoContext is used.
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* @return the sorted list of alternate answers
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* @param word_mode determines whether recognition is done as a word or a phrase
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*/
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WordAltList *CubeObject::Recognize(LangModel *lang_mod, bool word_mode) {
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if (char_samp_ == NULL) {
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return NULL;
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}
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// clear alt lists
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Cleanup();
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// no specified language model, use the one in the reco context
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if (lang_mod == NULL) {
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lang_mod = cntxt_->LangMod();
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}
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// normalize if necessary
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if (cntxt_->SizeNormalization()) {
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Normalize();
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}
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// assume not de-slanted by default
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deslanted_ = false;
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// create a beam search object
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if (beam_obj_ == NULL) {
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beam_obj_ = new BeamSearch(cntxt_, word_mode);
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if (beam_obj_ == NULL) {
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fprintf(stderr, "Cube ERROR (CubeObject::Recognize): could not construct "
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"BeamSearch\n");
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return NULL;
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}
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}
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// create a cube search object
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if (srch_obj_ == NULL) {
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srch_obj_ = new CubeSearchObject(cntxt_, char_samp_);
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if (srch_obj_ == NULL) {
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fprintf(stderr, "Cube ERROR (CubeObject::Recognize): could not construct "
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"CubeSearchObject\n");
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return NULL;
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}
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}
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// run a beam search against the tesslang model
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alt_list_ = beam_obj_->Search(srch_obj_, lang_mod);
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// deslant (if supported by language) and re-reco if probability is low enough
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if (cntxt_->HasItalics() == true &&
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(alt_list_ == NULL || alt_list_->AltCount() < 1 ||
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alt_list_->AltCost(0) > CubeUtils::Prob2Cost(kMinProbSkipDeslanted))) {
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if (deslanted_beam_obj_ == NULL) {
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deslanted_beam_obj_ = new BeamSearch(cntxt_);
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if (deslanted_beam_obj_ == NULL) {
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fprintf(stderr, "Cube ERROR (CubeObject::Recognize): could not "
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"construct deslanted BeamSearch\n");
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return NULL;
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}
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}
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if (deslanted_srch_obj_ == NULL) {
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deslanted_char_samp_ = char_samp_->Clone();
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if (deslanted_char_samp_ == NULL) {
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fprintf(stderr, "Cube ERROR (CubeObject::Recognize): could not "
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"construct deslanted CharSamp\n");
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return NULL;
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}
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if (deslanted_char_samp_->Deslant() == false) {
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return NULL;
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}
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deslanted_srch_obj_ = new CubeSearchObject(cntxt_, deslanted_char_samp_);
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if (deslanted_srch_obj_ == NULL) {
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fprintf(stderr, "Cube ERROR (CubeObject::Recognize): could not "
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"construct deslanted CubeSearchObject\n");
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return NULL;
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}
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}
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// run a beam search against the tesslang model
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deslanted_alt_list_ = deslanted_beam_obj_->Search(deslanted_srch_obj_,
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lang_mod);
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// should we use de-slanted altlist?
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if (deslanted_alt_list_ != NULL && deslanted_alt_list_->AltCount() > 0) {
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if (alt_list_ == NULL || alt_list_->AltCount() < 1 ||
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deslanted_alt_list_->AltCost(0) < alt_list_->AltCost(0)) {
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deslanted_ = true;
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return deslanted_alt_list_;
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}
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}
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}
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return alt_list_;
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}
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/**
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* Recognize the member char sample as a word
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*/
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WordAltList *CubeObject::RecognizeWord(LangModel *lang_mod) {
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return Recognize(lang_mod, true);
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}
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/**
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* Recognize the member char sample as a phrase
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*/
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WordAltList *CubeObject::RecognizePhrase(LangModel *lang_mod) {
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return Recognize(lang_mod, false);
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}
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/**
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* Computes the cost of a specific string. This is done by performing
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* recognition of a language model that allows only the specified word
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*/
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int CubeObject::WordCost(const char *str) {
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WordListLangModel *lang_mod = new WordListLangModel(cntxt_);
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if (lang_mod == NULL) {
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return WORST_COST;
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}
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if (lang_mod->AddString(str) == false) {
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delete lang_mod;
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return WORST_COST;
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}
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// run a beam search against the single string wordlist model
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WordAltList *alt_list = RecognizeWord(lang_mod);
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delete lang_mod;
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int cost = WORST_COST;
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if (alt_list != NULL) {
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if (alt_list->AltCount() > 0) {
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cost = alt_list->AltCost(0);
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}
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}
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return cost;
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}
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// Recognizes a single character and returns the list of results.
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CharAltList *CubeObject::RecognizeChar() {
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if (char_samp_ == NULL) return NULL;
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CharAltList* alt_list = NULL;
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CharClassifier *char_classifier = cntxt_->Classifier();
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ASSERT_HOST(char_classifier != NULL);
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alt_list = char_classifier->Classify(char_samp_);
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return alt_list;
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}
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// Normalize the input word bitmap to have a minimum aspect ratio
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bool CubeObject::Normalize() {
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// create a cube search object
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CubeSearchObject *srch_obj = new CubeSearchObject(cntxt_, char_samp_);
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if (srch_obj == NULL) {
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return false;
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}
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// Perform over-segmentation
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int seg_cnt = srch_obj->SegPtCnt();
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// Only perform normalization if segment count is large enough
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if (seg_cnt < kMinNormalizationSegmentCnt) {
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delete srch_obj;
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return true;
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}
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// compute the mean AR of the segments
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double ar_mean = 0.0;
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for (int seg_idx = 0; seg_idx <= seg_cnt; seg_idx++) {
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CharSamp *seg_samp = srch_obj->CharSample(seg_idx - 1, seg_idx);
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if (seg_samp != NULL && seg_samp->Width() > 0) {
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ar_mean += (1.0 * seg_samp->Height() / seg_samp->Width());
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}
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}
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ar_mean /= (seg_cnt + 1);
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// perform normalization if segment AR is too high
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if (ar_mean > kMinNormalizationAspectRatio) {
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// scale down the image in the y-direction to attain AR
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CharSamp *new_samp = char_samp_->Scale(char_samp_->Width(),
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2.0 * char_samp_->Height() / ar_mean,
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false);
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if (new_samp != NULL) {
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// free existing char samp if owned
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if (own_char_samp_) {
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delete char_samp_;
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}
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// update with new scaled charsamp and set ownership flag
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char_samp_ = new_samp;
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own_char_samp_ = true;
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}
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}
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delete srch_obj;
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return true;
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}
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}
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