tesseract/ccstruct/pageres.h
Ray Smith 84920b92b3 Font and classifier output structure cleanup.
Font recognition was poor, due to forcing a 1st and 2nd choice at
a character level, when the total score for the correct font is often
correct at the word level, so allowed the propagation of a full set
of fonts and scores to the word recognizer, which can now decide word
level fonts using the scores instead of simple votes.

Change precipitated a cleanup of output data structures for classifier
results, eliminating ScoredClass and INT_RESULT_STRUCT, with a few
extra elements going in UnicharRating, and using that wherever possible.
That added the extra complexity of 1-rating due to a flip between 0 is
good and 0 is bad for the internal classifier scores before they are
converted to rating and certainty.
2015-05-12 17:24:34 -07:00

774 lines
31 KiB
C++

/**********************************************************************
* 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 "blamer.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;
/* 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(bool merge_similar_words,
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(bool merge_similar_words, 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(bool merge_similar_words, 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 ROW that this word sits in. NOT owned by the WERD_RES.
ROW* blob_row;
// The denorm provides the transformation to get back to the rotated image
// coords from the chopped_word/rebuild_word BLN coords, but each blob also
// has its own denorm.
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.
// Vector of SEAM* holding chopping points matching chopped_word.
GenericVector<SEAM*> seam_array;
// Widths of blobs in chopped_word.
GenericVector<int> blob_widths;
// Gaps between blobs in chopped_word. blob_gaps[i] is the gap between
// blob i and blob i+1.
GenericVector<int> blob_gaps;
// Ratings matrix contains classifier choices for each classified combination
// of blobs. The dimension is the same as the number of blobs in chopped_word
// and the leading diagonal corresponds to classifier results of the blobs
// in chopped_word. The state_ members of best_choice, raw_choice and
// best_choices all correspond to this ratings matrix and allow extraction
// of the blob choices for any given WERD_CHOICE.
MATRIX* ratings; // Owned pointer.
// Pointer to the first WERD_CHOICE in best_choices. This is the result that
// will be output from Tesseract. Note that this is now a borrowed pointer
// and should NOT be deleted.
WERD_CHOICE* best_choice; // Borrowed pointer.
// The best raw_choice found during segmentation search. Differs from the
// best_choice by being the best result according to just the character
// classifier, not taking any language model information into account.
// Unlike best_choice, the pointer IS owned by this WERD_RES.
WERD_CHOICE* raw_choice; // Owned pointer.
// Alternative results found during chopping/segmentation search stages.
// Note that being an ELIST, best_choices owns the WERD_CHOICEs.
WERD_CHOICE_LIST best_choices;
// 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
bool odd_size; // word is bigger than line or leader dots.
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
float baseline_shift; // 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?
WERD_RES() {
InitNonPointers();
InitPointers();
}
WERD_RES(WERD *the_word) {
InitNonPointers();
InitPointers();
word = the_word;
}
// Deep copies everything except the ratings MATRIX.
// To get that use deep_copy below.
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 || best_choice == NULL ||
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();
void ClearWordChoices();
void ClearRatings();
// Deep copies everything except the ratings MATRIX.
// To get that use deep_copy below.
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. 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.
// If allow_detailed_fx is true, the feature extractor will receive fine
// precision outline information, allowing smoother features and better
// features on low resolution images.
// The norm_mode sets the default mode for normalization in absence
// of any of the above flags. It should really be a tesseract::OcrEngineMode
// but is declared as int for ease of use with tessedit_ocr_engine_mode.
// Returns false if the word is empty and sets up fake results.
bool SetupForRecognition(const UNICHARSET& unicharset_in,
tesseract::Tesseract* tesseract, Pix* pix,
int norm_mode,
const TBOX* norm_box, bool numeric_mode,
bool use_body_size, bool allow_detailed_fx,
ROW *row, const BLOCK* block);
// Set up the seam array, bln_boxes, best_choice, and raw_choice to empty
// accumulators from a made chopped word. We presume the fields are already
// empty.
void SetupBasicsFromChoppedWord(const UNICHARSET &unicharset_in);
// 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();
// Computes the blob_widths and blob_gaps from the chopped_word.
void SetupBlobWidthsAndGaps();
// Updates internal data to account for a new SEAM (chop) at the given
// blob_number. Fixes the ratings matrix and states in the choices, as well
// as the blob widths and gaps.
void InsertSeam(int blob_number, SEAM* seam);
// Returns true if all the word choices except the first have adjust_factors
// worse than the given threshold.
bool AlternativeChoiceAdjustmentsWorseThan(float threshold) const;
// Returns true if the current word is ambiguous (by number of answers or
// by dangerous ambigs.)
bool IsAmbiguous();
// Returns true if the ratings matrix size matches the sum of each of the
// segmentation states.
bool StatesAllValid();
// Prints a list of words found if debug is true or the word result matches
// the word_to_debug.
void DebugWordChoices(bool debug, const char* word_to_debug);
// Prints the top choice along with the accepted/done flags.
void DebugTopChoice(const char* msg) const;
// Removes from best_choices all choices which are not within a reasonable
// range of the best choice.
void FilterWordChoices(int debug_level);
// Computes a set of distance thresholds used to control adaption.
// Compares the best choice for the current word to the best raw choice
// to determine which characters were classified incorrectly by the
// classifier. Then places a separate threshold into thresholds for each
// character in the word. If the classifier was correct, max_rating is placed
// into thresholds. If the classifier was incorrect, the mean match rating
// (error percentage) of the classifier's incorrect choice minus some margin
// is placed into thresholds. This can then be used by the caller to try to
// create a new template for the desired class that will classify the
// character with a rating better than the threshold value. The match rating
// placed into thresholds is never allowed to be below min_rating in order to
// prevent trying to make overly tight templates.
// min_rating limits how tight to make a template.
// max_rating limits how loose to make a template.
// rating_margin denotes the amount of margin to put in template.
void ComputeAdaptionThresholds(float certainty_scale,
float min_rating,
float max_rating,
float rating_margin,
float* thresholds);
// Saves a copy of the word_choice if it has the best unadjusted rating.
// Returns true if the word_choice was the new best.
bool LogNewRawChoice(WERD_CHOICE* word_choice);
// Consumes word_choice by adding it to best_choices, (taking ownership) if
// the certainty for word_choice is some distance of the best choice in
// best_choices, or by deleting the word_choice and returning false.
// The best_choices list is kept in sorted order by rating. Duplicates are
// removed, and the list is kept no longer than max_num_choices in length.
// Returns true if the word_choice is still a valid pointer.
bool LogNewCookedChoice(int max_num_choices, bool debug,
WERD_CHOICE* word_choice);
// Prints a brief list of all the best choices.
void PrintBestChoices() const;
// Returns the sum of the widths of the blob between start_blob and last_blob
// inclusive.
int GetBlobsWidth(int start_blob, int last_blob);
// Returns the width of a gap between the specified blob and the next one.
int GetBlobsGap(int blob_index);
// Returns the BLOB_CHOICE corresponding to the given index in the
// best choice word taken from the appropriate cell in the ratings MATRIX.
// Borrowed pointer, so do not delete. May return NULL if there is no
// BLOB_CHOICE matching the unichar_id at the given index.
BLOB_CHOICE* GetBlobChoice(int index) const;
// Returns the BLOB_CHOICE_LIST corresponding to the given index in the
// best choice word taken from the appropriate cell in the ratings MATRIX.
// Borrowed pointer, so do not delete.
BLOB_CHOICE_LIST* GetBlobChoices(int index) const;
// 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.
// choice must be from the current best_choices list.
void ReplaceBestChoice(WERD_CHOICE* choice);
// Builds the rebuild_word and sets the best_state from the chopped_word and
// the best_choice->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 best_choice using the best_choice
// to get the unichars, and the unicharset to get the target positions.
void SetScriptPositions();
// Sets all the blobs in all the words (best choice and alternates) to be
// the given position. (When a sub/superscript is recognized as a separate
// word, it falls victim to the rule that a whole word cannot be sub or
// superscript, so this function overrides that problem.)
void SetAllScriptPositions(tesseract::ScriptPos position);
// 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 box_word must match blob_count.
void FakeClassifyWord(int blob_count, BLOB_CHOICE** choices);
// Creates a WERD_CHOICE for the word using the top choices from the leading
// diagonal of the ratings matrix.
void FakeWordFromRatings();
// 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);
// Merges 2 adjacent blobs in the result (index and index+1) and corrects
// all the data to account for the change.
void MergeAdjacentBlobs(int index);
// 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();
// 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();
// 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();
// Returns a really deep copy of *src, including the ratings MATRIX.
static WERD_RES* deep_copy(const WERD_RES* src) {
WERD_RES* result = new WERD_RES(*src);
// That didn't copy the ratings, but we want a copy if there is one to
// begin width.
if (src->ratings != NULL)
result->ratings = src->ratings->DeepCopy();
return result;
}
// 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);
// Replaces the current WERD/WERD_RES with the given words. The given words
// contain fake blobs that indicate the position of the characters. These are
// replaced with real blobs from the current word as much as possible.
void ReplaceCurrentWord(tesseract::PointerVector<WERD_RES>* words);
// Deletes the current WERD_RES and its underlying WERD.
void DeleteCurrentWord();
// Makes the current word a fuzzy space if not already fuzzy. Updates
// corresponding part of combo if required.
void MakeCurrentWordFuzzy();
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
void ResetWordIterator();
private:
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