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git-svn-id: https://tesseract-ocr.googlecode.com/svn/trunk@1063 d0cd1f9f-072b-0410-8dd7-cf729c803f20
158 lines
5.1 KiB
C++
158 lines
5.1 KiB
C++
/**********************************************************************
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* File: cube_reco_context.h
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* Description: Declaration of the Cube Recognition Context 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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// The CubeRecoContext class abstracts the Cube OCR Engine. Typically a process
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// (or a thread) would create one CubeRecoContext object per language.
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// The CubeRecoContext object also provides methods to get and set the
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// different attribues of the Cube OCR Engine.
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#ifndef CUBE_RECO_CONTEXT_H
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#define CUBE_RECO_CONTEXT_H
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#include <string>
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#include "neural_net.h"
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#include "lang_model.h"
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#include "classifier_base.h"
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#include "feature_base.h"
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#include "char_set.h"
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#include "word_size_model.h"
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#include "char_bigrams.h"
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#include "word_unigrams.h"
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namespace tesseract {
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class Tesseract;
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class TessdataManager;
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class CubeRecoContext {
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public:
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// Reading order enum type
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enum ReadOrder {
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L2R,
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R2L
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};
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// Instantiate using a Tesseract object
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CubeRecoContext(Tesseract *tess_obj);
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~CubeRecoContext();
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// accessor functions
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inline const string & Lang() const { return lang_; }
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inline CharSet *CharacterSet() const { return char_set_; }
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const UNICHARSET *TessUnicharset() const { return tess_unicharset_; }
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inline CharClassifier *Classifier() const { return char_classifier_; }
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inline WordSizeModel *SizeModel() const { return word_size_model_; }
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inline CharBigrams *Bigrams() const { return char_bigrams_; }
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inline WordUnigrams *WordUnigramsObj() const { return word_unigrams_; }
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inline TuningParams *Params() const { return params_; }
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inline LangModel *LangMod() const { return lang_mod_; }
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// the reading order of the language
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inline ReadOrder ReadingOrder() const {
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return ((lang_ == "ara") ? R2L : L2R);
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}
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// does the language support case
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inline bool HasCase() const {
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return (lang_ != "ara" && lang_ != "hin");
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}
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inline bool Cursive() const {
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return (lang_ == "ara");
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}
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inline bool HasItalics() const {
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return (lang_ != "ara" && lang_ != "hin");
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}
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inline bool Contextual() const {
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return (lang_ == "ara");
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}
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// RecoContext runtime flags accessor functions
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inline bool SizeNormalization() const { return size_normalization_; }
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inline bool NoisyInput() const { return noisy_input_; }
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inline bool OOD() const { return lang_mod_->OOD(); }
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inline bool Numeric() const { return lang_mod_->Numeric(); }
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inline bool WordList() const { return lang_mod_->WordList(); }
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inline bool Punc() const { return lang_mod_->Punc(); }
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inline bool CaseSensitive() const {
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return char_classifier_->CaseSensitive();
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}
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inline void SetSizeNormalization(bool size_normalization) {
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size_normalization_ = size_normalization;
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}
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inline void SetNoisyInput(bool noisy_input) {
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noisy_input_ = noisy_input;
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}
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inline void SetOOD(bool ood_enabled) {
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lang_mod_->SetOOD(ood_enabled);
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}
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inline void SetNumeric(bool numeric_enabled) {
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lang_mod_->SetNumeric(numeric_enabled);
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}
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inline void SetWordList(bool word_list_enabled) {
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lang_mod_->SetWordList(word_list_enabled);
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}
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inline void SetPunc(bool punc_enabled) {
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lang_mod_->SetPunc(punc_enabled);
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}
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inline void SetCaseSensitive(bool case_sensitive) {
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char_classifier_->SetCaseSensitive(case_sensitive);
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}
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inline tesseract::Tesseract *TesseractObject() const {
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return tess_obj_;
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}
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// Returns the path of the data files
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bool GetDataFilePath(string *path) const;
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// Creates a CubeRecoContext object using a tesseract object. Data
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// files are loaded via the tessdata_manager, and the tesseract
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// unicharset is provided in order to map Cube's unicharset to
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// Tesseract's in the case where the two unicharsets differ.
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static CubeRecoContext *Create(Tesseract *tess_obj,
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TessdataManager *tessdata_manager,
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UNICHARSET *tess_unicharset);
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private:
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bool loaded_;
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string lang_;
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CharSet *char_set_;
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UNICHARSET *tess_unicharset_;
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WordSizeModel *word_size_model_;
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CharClassifier *char_classifier_;
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CharBigrams *char_bigrams_;
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WordUnigrams *word_unigrams_;
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TuningParams *params_;
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LangModel *lang_mod_;
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Tesseract *tess_obj_; // CubeRecoContext does not own this pointer
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bool size_normalization_;
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bool noisy_input_;
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// Loads and initialized all the necessary components of a
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// CubeRecoContext. See .cpp for more details.
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bool Load(TessdataManager *tessdata_manager,
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UNICHARSET *tess_unicharset);
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};
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}
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#endif // CUBE_RECO_CONTEXT_H
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