/usr/include/tesseract/pageres.h is in libtesseract-dev 3.02.01-6.
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* File: pageres.h (Formerly page_res.h)
* Description: Results classes used by control.c
* Author: Phil Cheatle
* Created: Tue Sep 22 08:42:49 BST 1992
*
* (C) Copyright 1992, Hewlett-Packard Ltd.
** Licensed under the Apache License, Version 2.0 (the "License");
** you may not use this file except in compliance with the License.
** You may obtain a copy of the License at
** http://www.apache.org/licenses/LICENSE-2.0
** Unless required by applicable law or agreed to in writing, software
** distributed under the License is distributed on an "AS IS" BASIS,
** WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
** See the License for the specific language governing permissions and
** limitations under the License.
*
**********************************************************************/
#ifndef PAGERES_H
#define PAGERES_H
#include "blobs.h"
#include "boxword.h"
#include "elst.h"
#include "genericvector.h"
#include "normalis.h"
#include "ocrblock.h"
#include "ocrrow.h"
#include "params_training_featdef.h"
#include "ratngs.h"
#include "rejctmap.h"
#include "seam.h"
#include "werd.h"
namespace tesseract {
struct FontInfo;
class Tesseract;
}
using tesseract::FontInfo;
static const inT16 kBlamerBoxTolerance = 5;
// Enum for expressing the source of error.
// Note: Please update kIncorrectResultReasonNames when modifying this enum.
enum IncorrectResultReason {
// The text recorded in best choice == truth text
IRR_CORRECT,
// Either: Top choice is incorrect and is a dictionary word (language model
// is unlikely to help correct such errors, so blame the classifier).
// Or: the correct unichar was not included in shortlist produced by the
// classifier at all.
IRR_CLASSIFIER,
// Chopper have not found one or more splits that correspond to the correct
// character bounding boxes recorded in BlamerBundle::truth_word.
IRR_CHOPPER,
// Classifier did include correct unichars for each blob in the correct
// segmentation, however its rating could have been too bad to allow the
// language model to pull out the correct choice. On the other hand the
// strength of the language model might have been too weak to favor the
// correct answer, this we call this case a classifier-language model
// tradeoff error.
IRR_CLASS_LM_TRADEOFF,
// Page layout failed to produce the correct bounding box. Blame page layout
// if the truth was not found for the word, which implies that the bounding
// box of the word was incorrect (no truth word had a similar bounding box).
IRR_PAGE_LAYOUT,
// SegSearch heuristic prevented one or more blobs from the correct
// segmentation state to be classified (e.g. the blob was too wide).
IRR_SEGSEARCH_HEUR,
// The correct segmentaiton state was not explored because of poor SegSearch
// pain point prioritization. We blame SegSearch pain point prioritization
// if the best rating of a choice constructed from correct segmentation is
// better than that of the best choice (i.e. if we got to explore the correct
// segmentation state, language model would have picked the correct choice).
IRR_SEGSEARCH_PP,
// Same as IRR_CLASS_LM_TRADEOFF, but used when we only run chopper on a word,
// and thus use the old language model (permuters).
// TODO(antonova): integrate the new language mode with chopper
IRR_CLASS_OLD_LM_TRADEOFF,
// If there is an incorrect adaptive template match with a better score than
// a correct one (either pre-trained or adapted), mark this as adaption error.
IRR_ADAPTION,
// split_and_recog_word() failed to find a suitable split in truth.
IRR_NO_TRUTH_SPLIT,
// Truth is not available for this word (e.g. when words in corrected content
// file are turned into ~~~~ because an appropriate alignment was not found.
IRR_NO_TRUTH,
// The text recorded in best choice != truth text, but none of the above
// reasons are set.
IRR_UNKNOWN,
IRR_NUM_REASONS
};
// Blamer-related information to determine the source of errors.
struct BlamerBundle {
static const char *IncorrectReasonName(IncorrectResultReason irr);
BlamerBundle() : truth_has_char_boxes(false),
incorrect_result_reason(IRR_CORRECT),
lattice_data(NULL) { ClearResults(); }
~BlamerBundle() { delete[] lattice_data; }
void ClearResults() {
norm_truth_word.DeleteAllBoxes();
norm_box_tolerance = 0;
if (!NoTruth()) incorrect_result_reason = IRR_CORRECT;
debug = "";
segsearch_is_looking_for_blame = false;
best_correctly_segmented_rating = WERD_CHOICE::kBadRating;
correct_segmentation_cols.clear();
correct_segmentation_rows.clear();
best_choice_is_dict_and_top_choice = false;
delete[] lattice_data;
lattice_data = NULL;
lattice_size = 0;
}
void CopyTruth(const BlamerBundle &other) {
truth_has_char_boxes = other.truth_has_char_boxes;
truth_word = other.truth_word;
truth_text = other.truth_text;
incorrect_result_reason =
(other.NoTruth() ? other.incorrect_result_reason : IRR_CORRECT);
}
void CopyResults(const BlamerBundle &other) {
norm_truth_word = other.norm_truth_word;
norm_box_tolerance = other.norm_box_tolerance;
incorrect_result_reason = other.incorrect_result_reason;
segsearch_is_looking_for_blame = other.segsearch_is_looking_for_blame;
best_correctly_segmented_rating =other.best_correctly_segmented_rating;
correct_segmentation_cols = other.correct_segmentation_cols;
correct_segmentation_rows = other.correct_segmentation_rows;
best_choice_is_dict_and_top_choice =
other.best_choice_is_dict_and_top_choice;
if (other.lattice_data != NULL) {
lattice_data = new char[other.lattice_size];
memcpy(lattice_data, other.lattice_data, other.lattice_size);
lattice_size = other.lattice_size;
} else {
lattice_data = NULL;
}
}
BlamerBundle(const BlamerBundle &other) {
this->CopyTruth(other);
this->CopyResults(other);
}
const char *IncorrectReason() const;
bool NoTruth() const {
return (incorrect_result_reason == IRR_NO_TRUTH ||
incorrect_result_reason == IRR_PAGE_LAYOUT);
}
void SetBlame(IncorrectResultReason irr,
const STRING &msg, const WERD_CHOICE *choice, bool debug) {
this->incorrect_result_reason = irr;
this->debug = this->IncorrectReason();
this->debug += " to blame: ";
this->FillDebugString(msg, choice, &(this->debug));
if (debug) tprintf("SetBlame(): %s", this->debug.string());
}
// Appends choice and truth details to the given debug string.
void FillDebugString(const STRING &msg, const WERD_CHOICE *choice,
STRING *debug);
// Set to true when bounding boxes for individual unichars are recorded.
bool truth_has_char_boxes;
// The true_word (in the original image coordinate space) contains ground
// truth bounding boxes for this WERD_RES.
tesseract::BoxWord truth_word;
// Same as above, but in normalized coordinates
// (filled in by WERD_RES::SetupForRecognition()).
tesseract::BoxWord norm_truth_word;
// Tolerance for bounding box comparisons in normalized space.
int norm_box_tolerance;
// Contains ground truth unichar for each of the bounding boxes in truth_word.
GenericVector<STRING> truth_text;
// The reason for incorrect OCR result.
IncorrectResultReason incorrect_result_reason;
// Debug text associated with the blame.
STRING debug;
// Misadaption debug information (filled in if this word was misadapted to).
STRING misadaption_debug;
// Variables used by the segmentation search when looking for the blame.
// Set to true while segmentation search is continued after the usual
// termination condition in order to look for the blame.
bool segsearch_is_looking_for_blame;
// Best rating for correctly segmented path
// (set and used by SegSearch when looking for blame).
float best_correctly_segmented_rating;
// Vectors populated by SegSearch to indicate column and row indices that
// correspond to blobs with correct bounding boxes.
GenericVector<int> correct_segmentation_cols;
GenericVector<int> correct_segmentation_rows;
// Set to true if best choice is a dictionary word and
// classifier's top choice.
bool best_choice_is_dict_and_top_choice;
// Serialized segmentation search lattice.
char *lattice_data;
int lattice_size; // size of lattice_data in bytes
// Information about hypotheses (paths) explored by the segmentation search.
tesseract::ParamsTrainingBundle params_training_bundle;
};
/* Forward declarations */
class BLOCK_RES;
ELISTIZEH (BLOCK_RES) CLISTIZEH (BLOCK_RES)
class
ROW_RES;
ELISTIZEH (ROW_RES)
class WERD_RES;
ELISTIZEH (WERD_RES)
/*************************************************************************
* PAGE_RES - Page results
*************************************************************************/
class PAGE_RES { // page result
public:
inT32 char_count;
inT32 rej_count;
BLOCK_RES_LIST block_res_list;
BOOL8 rejected;
// Updated every time PAGE_RES_IT iterating on this PAGE_RES moves to
// the next word. This pointer is not owned by PAGE_RES class.
WERD_CHOICE **prev_word_best_choice;
// Sums of blame reasons computed by the blamer.
GenericVector<int> blame_reasons;
// Debug information about all the misadaptions on this page.
// Each BlamerBundle contains an index into this vector, so that words that
// caused misadaption could be marked. However, since words could be
// deleted/split/merged, the log is stored on the PAGE_RES level.
GenericVector<STRING> misadaption_log;
inline void Init() {
char_count = 0;
rej_count = 0;
rejected = FALSE;
prev_word_best_choice = NULL;
blame_reasons.init_to_size(IRR_NUM_REASONS, 0);
}
PAGE_RES() { Init(); } // empty constructor
PAGE_RES(BLOCK_LIST *block_list, // real blocks
WERD_CHOICE **prev_word_best_choice_ptr);
~PAGE_RES () { // destructor
}
};
/*************************************************************************
* BLOCK_RES - Block results
*************************************************************************/
class BLOCK_RES:public ELIST_LINK {
public:
BLOCK * block; // real block
inT32 char_count; // chars in block
inT32 rej_count; // rejected chars
inT16 font_class; //
inT16 row_count;
float x_height;
BOOL8 font_assigned; // block already
// processed
BOOL8 bold; // all bold
BOOL8 italic; // all italic
ROW_RES_LIST row_res_list;
BLOCK_RES() {
} // empty constructor
BLOCK_RES(BLOCK *the_block); // real block
~BLOCK_RES () { // destructor
}
};
/*************************************************************************
* ROW_RES - Row results
*************************************************************************/
class ROW_RES:public ELIST_LINK {
public:
ROW * row; // real row
inT32 char_count; // chars in block
inT32 rej_count; // rejected chars
inT32 whole_word_rej_count; // rejs in total rej wds
WERD_RES_LIST word_res_list;
ROW_RES() {
} // empty constructor
ROW_RES(ROW *the_row); // real row
~ROW_RES() { // destructor
}
};
/*************************************************************************
* WERD_RES - Word results
*************************************************************************/
enum CRUNCH_MODE
{
CR_NONE,
CR_KEEP_SPACE,
CR_LOOSE_SPACE,
CR_DELETE
};
// WERD_RES is a collection of publicly accessible members that gathers
// information about a word result.
class WERD_RES : public ELIST_LINK {
public:
// Which word is which?
// There are 3 coordinate spaces in use here: a possibly rotated pixel space,
// the original image coordinate space, and the BLN space in which the
// baseline of a word is at kBlnBaselineOffset, the xheight is kBlnXHeight,
// and the x-middle of the word is at 0.
// In the rotated pixel space, coordinates correspond to the input image,
// but may be rotated about the origin by a multiple of 90 degrees,
// and may therefore be negative.
// In any case a rotation by denorm.block()->re_rotation() will take them
// back to the original image.
// The other differences between words all represent different stages of
// processing during recognition.
// ---------------------------INPUT-------------------------------------
// The word is the input C_BLOBs in the rotated pixel space.
// word is NOT owned by the WERD_RES unless combination is true.
// All the other word pointers ARE owned by the WERD_RES.
WERD* word; // Input C_BLOB word.
// -------------SETUP BY SetupFor*Recognition---READONLY-INPUT------------
// The bln_boxes contains the bounding boxes (only) of the input word, in the
// BLN space. The lengths of word and bln_boxes
// match as they are both before any chopping.
// TODO(rays) determine if docqual does anything useful and delete bln_boxes
// if it doesn't.
tesseract::BoxWord* bln_boxes; // BLN input bounding boxes.
// The denorm provides the transformation to get back to the rotated image
// coords from the chopped_word/rebuild_word BLN coords.
DENORM denorm; // For use on chopped_word.
// Unicharset used by the classifier output in best_choice and raw_choice.
const UNICHARSET* uch_set; // For converting back to utf8.
// ----Initialized by SetupFor*Recognition---BUT OUTPUT FROM RECOGNITION----
// ----Setup to a (different!) state expected by the various classifiers----
// TODO(rays) Tidy and make more consistent.
// The chopped_word is also in BLN space, and represents the fully chopped
// character fragments that make up the word.
// The length of chopped_word matches length of seam_array + 1 (if set).
TWERD* chopped_word; // BLN chopped fragments output.
SEAMS seam_array; // Seams matching chopped_word.
WERD_CHOICE *best_choice; // tess output
WERD_CHOICE *raw_choice; // top choice permuter
// Alternative paths found during chopping/segmentation search stages
// (the first entry being a slim copy of best_choice).
GenericVector<WERD_CHOICE *> alt_choices;
GenericVector<GenericVector<int> > alt_states;
// Truth bounding boxes, text and incorrect choice reason.
BlamerBundle *blamer_bundle;
// --------------OUTPUT FROM RECOGNITION-------------------------------
// --------------Not all fields are necessarily set.-------------------
// ---best_choice, raw_choice *must* end up set, with a box_word-------
// ---In complete output, the number of blobs in rebuild_word matches---
// ---the number of boxes in box_word, the number of unichar_ids in---
// ---best_choice, the number of ints in best_state, and the number---
// ---of strings in correct_text--------------------------------------
// ---SetupFake Sets everything to appropriate values if the word is---
// ---known to be bad before recognition.------------------------------
// The rebuild_word is also in BLN space, but represents the final best
// segmentation of the word. Its length is therefore the same as box_word.
TWERD* rebuild_word; // BLN best segmented word.
// The box_word is in the original image coordinate space. It is the
// bounding boxes of the rebuild_word, after denormalization.
// The length of box_word matches rebuild_word, best_state (if set) and
// correct_text (if set), as well as best_choice and represents the
// number of classified units in the output.
tesseract::BoxWord* box_word; // Denormalized output boxes.
// The best_state stores the relationship between chopped_word and
// rebuild_word. Each blob[i] in rebuild_word is composed of best_state[i]
// adjacent blobs in chopped_word. The seams in seam_array are hidden
// within a rebuild_word blob and revealed between them.
GenericVector<int> best_state; // Number of blobs in each best blob.
// The correct_text is used during training and adaption to carry the
// text to the training system without the need for a unicharset. There
// is one entry in the vector for each blob in rebuild_word and box_word.
GenericVector<STRING> correct_text;
// The Tesseract that was used to recognize this word. Just a borrowed
// pointer. Note: Tesseract's class definition is in a higher-level library.
// We avoid introducing a cyclic dependency by not using the Tesseract
// within WERD_RES. We are just storing it to provide access to it
// for the top-level multi-language controller, and maybe for output of
// the recognized language.
tesseract::Tesseract* tesseract;
// Less-well documented members.
// TODO(rays) Add more documentation here.
WERD_CHOICE *ep_choice; // ep text TODO(rays) delete this.
REJMAP reject_map; // best_choice rejects
BOOL8 tess_failed;
/*
If tess_failed is TRUE, one of the following tests failed when Tess
returned:
- The outword blob list was not the same length as the best_choice string;
- The best_choice string contained ALL blanks;
- The best_choice string was zero length
*/
BOOL8 tess_accepted; // Tess thinks its ok?
BOOL8 tess_would_adapt; // Tess would adapt?
BOOL8 done; // ready for output?
bool small_caps; // word appears to be small caps
inT8 italic;
inT8 bold;
// The fontinfos are pointers to data owned by the classifier.
const FontInfo* fontinfo;
const FontInfo* fontinfo2;
inT8 fontinfo_id_count; // number of votes
inT8 fontinfo_id2_count; // number of votes
BOOL8 guessed_x_ht;
BOOL8 guessed_caps_ht;
CRUNCH_MODE unlv_crunch_mode;
float x_height; // post match estimate
float caps_height; // post match estimate
/*
To deal with fuzzy spaces we need to be able to combine "words" to form
combinations when we suspect that the gap is a non-space. The (new) text
ord code generates separate words for EVERY fuzzy gap - flags in the word
indicate whether the gap is below the threshold (fuzzy kern) and is thus
NOT a real word break by default, or above the threshold (fuzzy space) and
this is a real word break by default.
The WERD_RES list contains all these words PLUS "combination" words built
out of (copies of) the words split by fuzzy kerns. The separate parts have
their "part_of_combo" flag set true and should be IGNORED on a default
reading of the list.
Combination words are FOLLOWED by the sequence of part_of_combo words
which they combine.
*/
BOOL8 combination; //of two fuzzy gap wds
BOOL8 part_of_combo; //part of a combo
BOOL8 reject_spaces; //Reject spacing?
// FontInfo ids for each unichar in best_choice.
GenericVector<inT8> best_choice_fontinfo_ids;
WERD_RES() {
InitNonPointers();
InitPointers();
}
WERD_RES(WERD *the_word) {
InitNonPointers();
InitPointers();
word = the_word;
}
WERD_RES(const WERD_RES &source) {
InitPointers();
*this = source; // see operator=
}
~WERD_RES();
// Returns the UTF-8 string for the given blob index in the best_choice word,
// given that we know whether we are in a right-to-left reading context.
// This matters for mirrorable characters such as parentheses. We recognize
// characters purely based on their shape on the page, and by default produce
// the corresponding unicode for a left-to-right context.
const char* const BestUTF8(int blob_index, bool in_rtl_context) const {
if (blob_index < 0 || blob_index >= best_choice->length())
return NULL;
UNICHAR_ID id = best_choice->unichar_id(blob_index);
if (id < 0 || id >= uch_set->size() || id == INVALID_UNICHAR_ID)
return NULL;
UNICHAR_ID mirrored = uch_set->get_mirror(id);
if (in_rtl_context && mirrored > 0 && mirrored != INVALID_UNICHAR_ID)
id = mirrored;
return uch_set->id_to_unichar_ext(id);
}
// Returns the UTF-8 string for the given blob index in the raw_choice word.
const char* const RawUTF8(int blob_index) const {
if (blob_index < 0 || blob_index >= raw_choice->length())
return NULL;
UNICHAR_ID id = raw_choice->unichar_id(blob_index);
if (id < 0 || id >= uch_set->size() || id == INVALID_UNICHAR_ID)
return NULL;
return uch_set->id_to_unichar(id);
}
UNICHARSET::Direction SymbolDirection(int blob_index) const {
if (best_choice == NULL ||
blob_index >= best_choice->length() ||
blob_index < 0)
return UNICHARSET::U_OTHER_NEUTRAL;
return uch_set->get_direction(best_choice->unichar_id(blob_index));
}
bool AnyRtlCharsInWord() const {
if (uch_set == NULL || best_choice == NULL || best_choice->length() < 1)
return false;
for (int id = 0; id < best_choice->length(); id++) {
int unichar_id = best_choice->unichar_id(id);
if (unichar_id < 0 || unichar_id >= uch_set->size())
continue; // Ignore illegal chars.
UNICHARSET::Direction dir =
uch_set->get_direction(unichar_id);
if (dir == UNICHARSET::U_RIGHT_TO_LEFT ||
dir == UNICHARSET::U_RIGHT_TO_LEFT_ARABIC ||
dir == UNICHARSET::U_ARABIC_NUMBER)
return true;
}
return false;
}
bool AnyLtrCharsInWord() const {
if (uch_set == NULL || best_choice == NULL || best_choice->length() < 1)
return false;
for (int id = 0; id < best_choice->length(); id++) {
int unichar_id = best_choice->unichar_id(id);
if (unichar_id < 0 || unichar_id >= uch_set->size())
continue; // Ignore illegal chars.
UNICHARSET::Direction dir = uch_set->get_direction(unichar_id);
if (dir == UNICHARSET::U_LEFT_TO_RIGHT)
return true;
}
return false;
}
// Return whether the blobs in this WERD_RES 0, 1,... come from an engine
// that gave us the unichars in reading order (as opposed to strict left
// to right).
bool UnicharsInReadingOrder() const {
return best_choice->unichars_in_script_order();
}
void InitNonPointers();
void InitPointers();
void Clear();
void ClearResults();
WERD_RES& operator=(const WERD_RES& source); //from this
void CopySimpleFields(const WERD_RES& source);
// Initializes a blank (default constructed) WERD_RES from one that has
// already been recognized.
// Use SetupFor*Recognition afterwards to complete the setup and make
// it ready for a retry recognition.
void InitForRetryRecognition(const WERD_RES& source);
// Sets up the members used in recognition: bln_boxes, chopped_word,
// seam_array, denorm, best_choice, raw_choice. Returns false if
// the word is empty and sets up fake results. If use_body_size is
// true and row->body_size is set, then body_size will be used for
// blob normalization instead of xheight + ascrise. This flag is for
// those languages that are using CJK pitch model and thus it has to
// be true if and only if tesseract->textord_use_cjk_fp_model is
// true.
bool SetupForTessRecognition(const UNICHARSET& unicharset_in,
tesseract::Tesseract* tesseract, Pix* pix,
bool numeric_mode, bool use_body_size,
ROW *row, BLOCK* block);
// Sets up the members used in recognition:
// bln_boxes, chopped_word, seam_array, denorm.
// Returns false if the word is empty and sets up fake results.
bool SetupForCubeRecognition(const UNICHARSET& unicharset_in,
tesseract::Tesseract* tesseract,
const BLOCK* block);
// Sets up the members used in recognition for an empty recognition result:
// bln_boxes, chopped_word, seam_array, denorm, best_choice, raw_choice.
void SetupFake(const UNICHARSET& uch);
// Set the word as having the script of the input unicharset.
void SetupWordScript(const UNICHARSET& unicharset_in);
// Sets up the blamer_bundle if it is not null, using the initialized denorm.
void SetupBlamerBundle();
// Moves the results fields from word to this. This takes ownership of all
// the data, so src can be destructed.
// word1.ConsumeWordResult(word);
// delete word;
// is simpler and faster than:
// word1 = *word;
// delete word;
// as it doesn't need to copy and reallocate anything.
void ConsumeWordResults(WERD_RES* word);
// Replace the best choice and rebuild box word.
void ReplaceBestChoice(const WERD_CHOICE& choice,
const GenericVector<int> &segmentation_state);
// Builds the rebuild_word from the chopped_word and the best_state.
void RebuildBestState();
// Copies the chopped_word to the rebuild_word, faking a best_state as well.
// Also sets up the output box_word.
void CloneChoppedToRebuild();
// Sets/replaces the box_word with one made from the rebuild_word.
void SetupBoxWord();
// Sets up the script positions in the output boxword using the best_choice
// to get the unichars, and the unicharset to get the target positions.
void SetScriptPositions();
// Returns the indices [start, end) containing the core of the word, stripped
// of any superscript digits on either side.
// (i.e., the non-footnote part of the word).
// Assumes that BoxWord is all set up for best_choice.
void WithoutFootnoteSpan(int *start, int *end) const;
// Given an alternate word choice and segmentation state, yield the indices
// [start, end) containig the core of the word, stripped of any superscript
// digits on either side. (i.e. stripping off the footnote parts).
void WithoutFootnoteSpan(
const WERD_CHOICE &choice, const GenericVector<int> &state,
int *start, int *end) const;
// Classifies the word with some already-calculated BLOB_CHOICEs.
// The choices are an array of blob_count pointers to BLOB_CHOICE,
// providing a single classifier result for each blob.
// The BLOB_CHOICEs are consumed and the word takes ownership.
// The number of blobs in the outword must match blob_count.
void FakeClassifyWord(int blob_count, BLOB_CHOICE** choices);
// Copies the best_choice strings to the correct_text for adaption/training.
void BestChoiceToCorrectText();
// Merges 2 adjacent blobs in the result if the permanent callback
// class_cb returns other than INVALID_UNICHAR_ID, AND the permanent
// callback box_cb is NULL or returns true, setting the merged blob
// result to the class returned from class_cb.
// Returns true if anything was merged.
bool ConditionalBlobMerge(
TessResultCallback2<UNICHAR_ID, UNICHAR_ID, UNICHAR_ID>* class_cb,
TessResultCallback2<bool, const TBOX&, const TBOX&>* box_cb,
BLOB_CHOICE_LIST_CLIST *blob_choices);
// Callback helper for fix_quotes returns a double quote if both
// arguments are quote, otherwise INVALID_UNICHAR_ID.
UNICHAR_ID BothQuotes(UNICHAR_ID id1, UNICHAR_ID id2);
void fix_quotes(BLOB_CHOICE_LIST_CLIST *blob_choices);
// Callback helper for fix_hyphens returns UNICHAR_ID of - if both
// arguments are hyphen, otherwise INVALID_UNICHAR_ID.
UNICHAR_ID BothHyphens(UNICHAR_ID id1, UNICHAR_ID id2);
// Callback helper for fix_hyphens returns true if box1 and box2 overlap
// (assuming both on the same textline, are in order and a chopped em dash.)
bool HyphenBoxesOverlap(const TBOX& box1, const TBOX& box2);
void fix_hyphens(BLOB_CHOICE_LIST_CLIST *blob_choices);
// Callback helper for merge_tess_fails returns a space if both
// arguments are space, otherwise INVALID_UNICHAR_ID.
UNICHAR_ID BothSpaces(UNICHAR_ID id1, UNICHAR_ID id2);
void merge_tess_fails();
static WERD_RES* deep_copy(const WERD_RES* src) {
return new WERD_RES(*src);
}
// Copy blobs from word_res onto this word (eliminating spaces between).
// Since this may be called bidirectionally OR both the BOL and EOL flags.
void copy_on(WERD_RES *word_res) { //from this word
word->set_flag(W_BOL, word->flag(W_BOL) || word_res->word->flag(W_BOL));
word->set_flag(W_EOL, word->flag(W_EOL) || word_res->word->flag(W_EOL));
word->copy_on(word_res->word);
}
// Returns true if the collection of count pieces, starting at start, are all
// natural connected components, ie there are no real chops involved.
bool PiecesAllNatural(int start, int count) const;
};
/*************************************************************************
* PAGE_RES_IT - Page results iterator
*************************************************************************/
class PAGE_RES_IT {
public:
PAGE_RES * page_res; // page being iterated
PAGE_RES_IT() {
} // empty contructor
PAGE_RES_IT(PAGE_RES *the_page_res) { // page result
page_res = the_page_res;
restart_page(); // ready to scan
}
// Do two PAGE_RES_ITs point at the same word?
// This is much cheaper than cmp().
bool operator ==(const PAGE_RES_IT &other) const;
bool operator !=(const PAGE_RES_IT &other) const {return !(*this == other); }
// Given another PAGE_RES_IT to the same page,
// this before other: -1
// this equal to other: 0
// this later than other: 1
int cmp(const PAGE_RES_IT &other) const;
WERD_RES *restart_page() {
return start_page(false); // Skip empty blocks.
}
WERD_RES *restart_page_with_empties() {
return start_page(true); // Allow empty blocks.
}
WERD_RES *start_page(bool empty_ok);
WERD_RES *restart_row();
// ============ Methods that mutate the underling structures ===========
// Note that these methods will potentially invalidate other PAGE_RES_ITs
// and are intended to be used only while a single PAGE_RES_IT is active.
// This problem needs to be taken into account if these mutation operators
// are ever provided to PageIterator or its subclasses.
// Inserts the new_word and a corresponding WERD_RES before the current
// position. The simple fields of the WERD_RES are copied from clone_res and
// the resulting WERD_RES is returned for further setup with best_choice etc.
WERD_RES* InsertSimpleCloneWord(const WERD_RES& clone_res, WERD* new_word);
// Deletes the current WERD_RES and its underlying WERD.
void DeleteCurrentWord();
WERD_RES *forward() { // Get next word.
return internal_forward(false, false);
}
// Move forward, but allow empty blocks to show as single NULL words.
WERD_RES *forward_with_empties() {
return internal_forward(false, true);
}
WERD_RES *forward_paragraph(); // get first word in next non-empty paragraph
WERD_RES *forward_block(); // get first word in next non-empty block
WERD_RES *prev_word() const { // previous word
return prev_word_res;
}
ROW_RES *prev_row() const { // row of prev word
return prev_row_res;
}
BLOCK_RES *prev_block() const { // block of prev word
return prev_block_res;
}
WERD_RES *word() const { // current word
return word_res;
}
ROW_RES *row() const { // row of current word
return row_res;
}
BLOCK_RES *block() const { // block of cur. word
return block_res;
}
WERD_RES *next_word() const { // next word
return next_word_res;
}
ROW_RES *next_row() const { // row of next word
return next_row_res;
}
BLOCK_RES *next_block() const { // block of next word
return next_block_res;
}
void rej_stat_word(); // for page/block/row
private:
void ResetWordIterator();
WERD_RES *internal_forward(bool new_block, bool empty_ok);
WERD_RES * prev_word_res; // previous word
ROW_RES *prev_row_res; // row of prev word
BLOCK_RES *prev_block_res; // block of prev word
WERD_RES *word_res; // current word
ROW_RES *row_res; // row of current word
BLOCK_RES *block_res; // block of cur. word
WERD_RES *next_word_res; // next word
ROW_RES *next_row_res; // row of next word
BLOCK_RES *next_block_res; // block of next word
BLOCK_RES_IT block_res_it; // iterators
ROW_RES_IT row_res_it;
WERD_RES_IT word_res_it;
};
#endif
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