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4991295a39
tesseract/src/ccstruct/pageres.cpp
Egor Pugin 4991295a39 Convert ELIST into template.
2024-11-23 00:25:29 +03:00

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/**********************************************************************
* File: pageres.cpp (Formerly page_res.c)
* Description: Hierarchy of results classes from PAGE_RES to WERD_RES
* and an iterator class to iterate over the words.
* Main purposes:
* Easy way to iterate over the words without a 3-nested loop.
* Holds data used during word recognition.
* Holds information about alternative spacing paths.
* Author: Phil Cheatle
*
* (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.
*
**********************************************************************/
#include "pageres.h"
#include "blamer.h" // for BlamerBundle
#include "blobs.h" // for TWERD, TBLOB
#include "boxword.h" // for BoxWord
#include "errcode.h" // for ASSERT_HOST
#include "ocrblock.h" // for BLOCK_IT, BLOCK, BLOCK_LIST (ptr only)
#include "ocrrow.h" // for ROW, ROW_IT
#include "pdblock.h" // for PDBLK
#include "polyblk.h" // for POLY_BLOCK
#include "seam.h" // for SEAM, start_seam_list
#include "stepblob.h" // for C_BLOB_IT, C_BLOB, C_BLOB_LIST
#include "tprintf.h" // for tprintf
#include <tesseract/publictypes.h> // for OcrEngineMode, OEM_LSTM_ONLY
#include <cassert> // for assert
#include <cstdint> // for INT32_MAX
#include <cstring> // for strlen
struct Pix;
namespace tesseract {
// Gain factor for computing thresholds that determine the ambiguity of a
// word.
static const double kStopperAmbiguityThresholdGain = 8.0;
// Constant offset for computing thresholds that determine the ambiguity of a
// word.
static const double kStopperAmbiguityThresholdOffset = 1.5;
// Max number of broken pieces to associate.
const int kWordrecMaxNumJoinChunks = 4;
// Max ratio of word box height to line size to allow it to be processed as
// a line with other words.
const double kMaxWordSizeRatio = 1.25;
// Max ratio of line box height to line size to allow a new word to be added.
const double kMaxLineSizeRatio = 1.25;
// Max ratio of word gap to line size to allow a new word to be added.
const double kMaxWordGapRatio = 2.0;
// Computes and returns a threshold of certainty difference used to determine
// which words to keep, based on the adjustment factors of the two words.
// TODO(rays) This is horrible. Replace with an enhance params training model.
static double StopperAmbigThreshold(double f1, double f2) {
return (f2 - f1) * kStopperAmbiguityThresholdGain -
kStopperAmbiguityThresholdOffset;
}
/*************************************************************************
* PAGE_RES::PAGE_RES
*
* Constructor for page results
*************************************************************************/
PAGE_RES::PAGE_RES(bool merge_similar_words, BLOCK_LIST *the_block_list,
WERD_CHOICE **prev_word_best_choice_ptr) {
Init();
BLOCK_IT block_it(the_block_list);
BLOCK_RES_IT block_res_it(&block_res_list);
for (block_it.mark_cycle_pt(); !block_it.cycled_list(); block_it.forward()) {
block_res_it.add_to_end(
new BLOCK_RES(merge_similar_words, block_it.data()));
}
prev_word_best_choice = prev_word_best_choice_ptr;
}
/*************************************************************************
* BLOCK_RES::BLOCK_RES
*
* Constructor for BLOCK results
*************************************************************************/
BLOCK_RES::BLOCK_RES(bool merge_similar_words, BLOCK *the_block) {
ROW_IT row_it(the_block->row_list());
ROW_RES_IT row_res_it(&row_res_list);
char_count = 0;
rej_count = 0;
font_class = -1; // not assigned
x_height = -1.0;
font_assigned = false;
row_count = 0;
block = the_block;
for (row_it.mark_cycle_pt(); !row_it.cycled_list(); row_it.forward()) {
row_res_it.add_to_end(new ROW_RES(merge_similar_words, row_it.data()));
}
}
/*************************************************************************
* ROW_RES::ROW_RES
*
* Constructor for ROW results
*************************************************************************/
ROW_RES::ROW_RES(bool merge_similar_words, ROW *the_row) {
WERD_IT word_it(the_row->word_list());
WERD_RES_IT word_res_it(&word_res_list);
WERD_RES *combo = nullptr; // current combination of fuzzies
WERD *copy_word;
char_count = 0;
rej_count = 0;
whole_word_rej_count = 0;
row = the_row;
bool add_next_word = false;
TBOX union_box;
float line_height =
the_row->x_height() + the_row->ascenders() - the_row->descenders();
for (word_it.mark_cycle_pt(); !word_it.cycled_list(); word_it.forward()) {
auto *word_res = new WERD_RES(word_it.data());
word_res->x_height = the_row->x_height();
if (add_next_word) {
ASSERT_HOST(combo != nullptr);
// We are adding this word to the combination.
word_res->part_of_combo = true;
combo->copy_on(word_res);
} else if (merge_similar_words) {
union_box = word_res->word->bounding_box();
add_next_word = !word_res->word->flag(W_REP_CHAR) &&
union_box.height() <= line_height * kMaxWordSizeRatio;
word_res->odd_size = !add_next_word;
}
WERD *next_word = word_it.data_relative(1);
if (merge_similar_words) {
if (add_next_word && !next_word->flag(W_REP_CHAR)) {
// Next word will be added on if all of the following are true:
// Not a rep char.
// Box height small enough.
// Union box height small enough.
// Horizontal gap small enough.
TBOX next_box = next_word->bounding_box();
int prev_right = union_box.right();
union_box += next_box;
if (next_box.height() > line_height * kMaxWordSizeRatio ||
union_box.height() > line_height * kMaxLineSizeRatio ||
next_box.left() > prev_right + line_height * kMaxWordGapRatio) {
add_next_word = false;
}
}
next_word->set_flag(W_FUZZY_NON, add_next_word);
} else {
add_next_word = next_word->flag(W_FUZZY_NON);
}
if (add_next_word) {
if (combo == nullptr) {
copy_word = new WERD;
*copy_word = *(word_it.data()); // deep copy
combo = new WERD_RES(copy_word);
combo->x_height = the_row->x_height();
combo->combination = true;
word_res_it.add_to_end(combo);
}
word_res->part_of_combo = true;
} else {
combo = nullptr;
}
word_res_it.add_to_end(word_res);
}
}
WERD_RES &WERD_RES::operator=(const WERD_RES &source) {
this->ELIST<WERD_RES>::LINK::operator=(source);
Clear();
if (source.combination) {
word = new WERD;
*word = *(source.word); // deep copy
} else {
word = source.word; // pt to same word
}
if (source.bln_boxes != nullptr) {
bln_boxes = new tesseract::BoxWord(*source.bln_boxes);
}
if (source.chopped_word != nullptr) {
chopped_word = new TWERD(*source.chopped_word);
}
if (source.rebuild_word != nullptr) {
rebuild_word = new TWERD(*source.rebuild_word);
}
// TODO(rays) Do we ever need to copy the seam_array?
blob_row = source.blob_row;
denorm = source.denorm;
if (source.box_word != nullptr) {
box_word = new tesseract::BoxWord(*source.box_word);
}
best_state = source.best_state;
correct_text = source.correct_text;
blob_widths = source.blob_widths;
blob_gaps = source.blob_gaps;
// None of the uses of operator= require the ratings matrix to be copied,
// so don't as it would be really slow.
// Copy the cooked choices.
WERD_CHOICE_IT wc_it(const_cast<WERD_CHOICE_LIST *>(&source.best_choices));
WERD_CHOICE_IT wc_dest_it(&best_choices);
for (wc_it.mark_cycle_pt(); !wc_it.cycled_list(); wc_it.forward()) {
const WERD_CHOICE *choice = wc_it.data();
wc_dest_it.add_after_then_move(new WERD_CHOICE(*choice));
}
if (!wc_dest_it.empty()) {
wc_dest_it.move_to_first();
best_choice = wc_dest_it.data();
} else {
best_choice = nullptr;
}
if (source.raw_choice != nullptr) {
raw_choice = new WERD_CHOICE(*source.raw_choice);
} else {
raw_choice = nullptr;
}
if (source.ep_choice != nullptr) {
ep_choice = new WERD_CHOICE(*source.ep_choice);
} else {
ep_choice = nullptr;
}
reject_map = source.reject_map;
combination = source.combination;
part_of_combo = source.part_of_combo;
CopySimpleFields(source);
if (source.blamer_bundle != nullptr) {
blamer_bundle = new BlamerBundle(*(source.blamer_bundle));
}
return *this;
}
// Copies basic fields that don't involve pointers that might be useful
// to copy when making one WERD_RES from another.
void WERD_RES::CopySimpleFields(const WERD_RES &source) {
tess_failed = source.tess_failed;
tess_accepted = source.tess_accepted;
tess_would_adapt = source.tess_would_adapt;
done = source.done;
unlv_crunch_mode = source.unlv_crunch_mode;
small_caps = source.small_caps;
odd_size = source.odd_size;
fontinfo = source.fontinfo;
fontinfo2 = source.fontinfo2;
fontinfo_id_count = source.fontinfo_id_count;
fontinfo_id2_count = source.fontinfo_id2_count;
x_height = source.x_height;
caps_height = source.caps_height;
baseline_shift = source.baseline_shift;
guessed_x_ht = source.guessed_x_ht;
guessed_caps_ht = source.guessed_caps_ht;
reject_spaces = source.reject_spaces;
uch_set = source.uch_set;
tesseract = source.tesseract;
}
// 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 WERD_RES::InitForRetryRecognition(const WERD_RES &source) {
word = source.word;
CopySimpleFields(source);
if (source.blamer_bundle != nullptr) {
blamer_bundle = new BlamerBundle();
blamer_bundle->CopyTruth(*source.blamer_bundle);
}
}
// 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_hint sets the default mode for normalization in absence
// of any of the above flags.
// norm_box is used to override the word bounding box to determine the
// normalization scale and offset.
// Returns false if the word is empty and sets up fake results.
bool WERD_RES::SetupForRecognition(const UNICHARSET &unicharset_in,
tesseract::Tesseract *tess, Image pix,
int norm_mode, const TBOX *norm_box,
bool numeric_mode, bool use_body_size,
bool allow_detailed_fx, ROW *row,
const BLOCK *block) {
auto norm_mode_hint = static_cast<tesseract::OcrEngineMode>(norm_mode);
tesseract = tess;
POLY_BLOCK *pb = block != nullptr ? block->pdblk.poly_block() : nullptr;
if ((norm_mode_hint != tesseract::OEM_LSTM_ONLY &&
word->cblob_list()->empty()) ||
(pb != nullptr && !pb->IsText())) {
// Empty words occur when all the blobs have been moved to the rej_blobs
// list, which seems to occur frequently in junk.
SetupFake(unicharset_in);
word->set_flag(W_REP_CHAR, false);
return false;
}
ClearResults();
SetupWordScript(unicharset_in);
chopped_word = TWERD::PolygonalCopy(allow_detailed_fx, word);
float word_xheight =
use_body_size && row != nullptr && row->body_size() > 0.0f
? row->body_size()
: x_height;
chopped_word->BLNormalize(block, row, pix, word->flag(W_INVERSE),
word_xheight, baseline_shift, numeric_mode,
norm_mode_hint, norm_box, &denorm);
blob_row = row;
SetupBasicsFromChoppedWord(unicharset_in);
SetupBlamerBundle();
int num_blobs = chopped_word->NumBlobs();
ratings = new MATRIX(num_blobs, kWordrecMaxNumJoinChunks);
tess_failed = false;
return true;
}
// 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 WERD_RES::SetupBasicsFromChoppedWord(const UNICHARSET &unicharset_in) {
bln_boxes = tesseract::BoxWord::CopyFromNormalized(chopped_word);
start_seam_list(chopped_word, &seam_array);
SetupBlobWidthsAndGaps();
ClearWordChoices();
}
// Sets up the members used in recognition for an empty recognition result:
// bln_boxes, chopped_word, seam_array, denorm, best_choice, raw_choice.
void WERD_RES::SetupFake(const UNICHARSET &unicharset_in) {
ClearResults();
SetupWordScript(unicharset_in);
chopped_word = new TWERD;
rebuild_word = new TWERD;
bln_boxes = new tesseract::BoxWord;
box_word = new tesseract::BoxWord;
int blob_count = word->cblob_list()->length();
if (blob_count > 0) {
auto **fake_choices = new BLOB_CHOICE *[blob_count];
// For non-text blocks, just pass any blobs through to the box_word
// and call the word failed with a fake classification.
C_BLOB_IT b_it(word->cblob_list());
int blob_id = 0;
for (b_it.mark_cycle_pt(); !b_it.cycled_list(); b_it.forward()) {
TBOX box = b_it.data()->bounding_box();
box_word->InsertBox(box_word->length(), box);
fake_choices[blob_id++] = new BLOB_CHOICE;
}
FakeClassifyWord(blob_count, fake_choices);
delete[] fake_choices;
} else {
auto *word = new WERD_CHOICE(&unicharset_in);
word->make_bad();
LogNewRawChoice(word);
// Ownership of word is taken by *this WERD_RES in LogNewCookedChoice.
LogNewCookedChoice(1, false, word);
}
tess_failed = true;
done = true;
}
void WERD_RES::SetupWordScript(const UNICHARSET &uch) {
uch_set = &uch;
int script = uch.default_sid();
word->set_script_id(script);
word->set_flag(W_SCRIPT_HAS_XHEIGHT, uch.script_has_xheight());
word->set_flag(W_SCRIPT_IS_LATIN, script == uch.latin_sid());
}
// Sets up the blamer_bundle if it is not null, using the initialized denorm.
void WERD_RES::SetupBlamerBundle() {
if (blamer_bundle != nullptr) {
blamer_bundle->SetupNormTruthWord(denorm);
}
}
// Computes the blob_widths and blob_gaps from the chopped_word.
void WERD_RES::SetupBlobWidthsAndGaps() {
blob_widths.clear();
blob_gaps.clear();
int num_blobs = chopped_word->NumBlobs();
for (int b = 0; b < num_blobs; ++b) {
TBLOB *blob = chopped_word->blobs[b];
TBOX box = blob->bounding_box();
blob_widths.push_back(box.width());
if (b + 1 < num_blobs) {
blob_gaps.push_back(chopped_word->blobs[b + 1]->bounding_box().left() -
box.right());
}
}
}
// 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 WERD_RES::InsertSeam(int blob_number, SEAM *seam) {
// Insert the seam into the SEAMS array.
seam->PrepareToInsertSeam(seam_array, chopped_word->blobs, blob_number, true);
seam_array.insert(seam_array.begin() + blob_number, seam);
if (ratings != nullptr) {
// Expand the ratings matrix.
ratings = ratings->ConsumeAndMakeBigger(blob_number);
// Fix all the segmentation states.
if (raw_choice != nullptr) {
raw_choice->UpdateStateForSplit(blob_number);
}
WERD_CHOICE_IT wc_it(&best_choices);
for (wc_it.mark_cycle_pt(); !wc_it.cycled_list(); wc_it.forward()) {
WERD_CHOICE *choice = wc_it.data();
choice->UpdateStateForSplit(blob_number);
}
SetupBlobWidthsAndGaps();
}
}
// Returns true if all the word choices except the first have adjust_factors
// worse than the given threshold.
bool WERD_RES::AlternativeChoiceAdjustmentsWorseThan(float threshold) const {
// The choices are not changed by this iteration.
WERD_CHOICE_IT wc_it(const_cast<WERD_CHOICE_LIST *>(&best_choices));
for (wc_it.forward(); !wc_it.at_first(); wc_it.forward()) {
WERD_CHOICE *choice = wc_it.data();
if (choice->adjust_factor() <= threshold) {
return false;
}
}
return true;
}
// Returns true if the current word is ambiguous (by number of answers or
// by dangerous ambigs.)
bool WERD_RES::IsAmbiguous() {
return !best_choices.singleton() || best_choice->dangerous_ambig_found();
}
// Returns true if the ratings matrix size matches the sum of each of the
// segmentation states.
bool WERD_RES::StatesAllValid() {
unsigned ratings_dim = ratings->dimension();
if (raw_choice->TotalOfStates() != ratings_dim) {
tprintf("raw_choice has total of states = %u vs ratings dim of %u\n",
raw_choice->TotalOfStates(), ratings_dim);
return false;
}
WERD_CHOICE_IT it(&best_choices);
unsigned index = 0;
for (it.mark_cycle_pt(); !it.cycled_list(); it.forward(), ++index) {
WERD_CHOICE *choice = it.data();
if (choice->TotalOfStates() != ratings_dim) {
tprintf("Cooked #%u has total of states = %u vs ratings dim of %u\n",
index, choice->TotalOfStates(), ratings_dim);
return false;
}
}
return true;
}
// Prints a list of words found if debug is true or the word result matches
// the word_to_debug.
void WERD_RES::DebugWordChoices(bool debug, const char *word_to_debug) {
if (debug || (word_to_debug != nullptr && *word_to_debug != '\0' &&
best_choice != nullptr &&
best_choice->unichar_string() == std::string(word_to_debug))) {
if (raw_choice != nullptr) {
raw_choice->print("\nBest Raw Choice");
}
WERD_CHOICE_IT it(&best_choices);
int index = 0;
for (it.mark_cycle_pt(); !it.cycled_list(); it.forward(), ++index) {
WERD_CHOICE *choice = it.data();
std::string label;
label += "\nCooked Choice #" + std::to_string(index);
choice->print(label.c_str());
}
}
}
// Prints the top choice along with the accepted/done flags.
void WERD_RES::DebugTopChoice(const char *msg) const {
tprintf("Best choice: accepted=%d, adaptable=%d, done=%d : ", tess_accepted,
tess_would_adapt, done);
if (best_choice == nullptr) {
tprintf("<Null choice>\n");
} else {
best_choice->print(msg);
}
}
// Removes from best_choices all choices which are not within a reasonable
// range of the best choice.
// TODO(rays) incorporate the information used here into the params training
// re-ranker, in place of this heuristic that is based on the previous
// adjustment factor.
void WERD_RES::FilterWordChoices(int debug_level) {
if (best_choice == nullptr || best_choices.singleton()) {
return;
}
if (debug_level >= 2) {
best_choice->print("\nFiltering against best choice");
}
WERD_CHOICE_IT it(&best_choices);
int index = 0;
for (it.forward(); !it.at_first(); it.forward(), ++index) {
WERD_CHOICE *choice = it.data();
float threshold = StopperAmbigThreshold(best_choice->adjust_factor(),
choice->adjust_factor());
// i, j index the blob choice in choice, best_choice.
// chunk is an index into the chopped_word blobs (AKA chunks).
// Since the two words may use different segmentations of the chunks, we
// iterate over the chunks to find out whether a comparable blob
// classification is much worse than the best result.
unsigned i = 0, j = 0, chunk = 0;
// Each iteration of the while deals with 1 chunk. On entry choice_chunk
// and best_chunk are the indices of the first chunk in the NEXT blob,
// i.e. we don't have to increment i, j while chunk < choice_chunk and
// best_chunk respectively.
auto choice_chunk = choice->state(0), best_chunk = best_choice->state(0);
while (i < choice->length() && j < best_choice->length()) {
if (choice->unichar_id(i) != best_choice->unichar_id(j) &&
choice->certainty(i) - best_choice->certainty(j) < threshold) {
if (debug_level >= 2) {
choice->print("WorstCertaintyDiffWorseThan");
tprintf(
"i %u j %u Choice->Blob[i].Certainty %.4g"
" WorstOtherChoiceCertainty %g Threshold %g\n",
i, j, choice->certainty(i), best_choice->certainty(j), threshold);
tprintf("Discarding bad choice #%d\n", index);
}
delete it.extract();
break;
}
++chunk;
// If needed, advance choice_chunk to keep up with chunk.
while (choice_chunk < chunk && ++i < choice->length()) {
choice_chunk += choice->state(i);
}
// If needed, advance best_chunk to keep up with chunk.
while (best_chunk < chunk && ++j < best_choice->length()) {
best_chunk += best_choice->state(j);
}
}
}
}
void WERD_RES::ComputeAdaptionThresholds(float certainty_scale,
float min_rating, float max_rating,
float rating_margin,
float *thresholds) {
int chunk = 0;
int end_chunk = best_choice->state(0);
int end_raw_chunk = raw_choice->state(0);
int raw_blob = 0;
for (unsigned i = 0; i < best_choice->length(); i++, thresholds++) {
float avg_rating = 0.0f;
int num_error_chunks = 0;
// For each chunk in best choice blob i, count non-matching raw results.
while (chunk < end_chunk) {
if (chunk >= end_raw_chunk) {
++raw_blob;
end_raw_chunk += raw_choice->state(raw_blob);
}
if (best_choice->unichar_id(i) != raw_choice->unichar_id(raw_blob)) {
avg_rating += raw_choice->certainty(raw_blob);
++num_error_chunks;
}
++chunk;
}
if (num_error_chunks > 0) {
avg_rating /= num_error_chunks;
*thresholds = (avg_rating / -certainty_scale) * (1.0 - rating_margin);
} else {
*thresholds = max_rating;
}
if (*thresholds > max_rating) {
*thresholds = max_rating;
}
if (*thresholds < min_rating) {
*thresholds = min_rating;
}
}
}
// 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 WERD_RES::LogNewRawChoice(WERD_CHOICE *word_choice) {
if (raw_choice == nullptr || word_choice->rating() < raw_choice->rating()) {
delete raw_choice;
raw_choice = new WERD_CHOICE(*word_choice);
raw_choice->set_permuter(TOP_CHOICE_PERM);
return true;
}
return false;
}
// 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 WERD_RES::LogNewCookedChoice(int max_num_choices, bool debug,
WERD_CHOICE *word_choice) {
if (best_choice != nullptr) {
// Throw out obviously bad choices to save some work.
// TODO(rays) Get rid of this! This piece of code produces different
// results according to the order in which words are found, which is an
// undesirable behavior. It would be better to keep all the choices and
// prune them later when more information is available.
float max_certainty_delta = StopperAmbigThreshold(
best_choice->adjust_factor(), word_choice->adjust_factor());
if (max_certainty_delta > -kStopperAmbiguityThresholdOffset) {
max_certainty_delta = -kStopperAmbiguityThresholdOffset;
}
if (word_choice->certainty() - best_choice->certainty() <
max_certainty_delta) {
if (debug) {
std::string bad_string;
word_choice->string_and_lengths(&bad_string, nullptr);
tprintf(
"Discarding choice \"%s\" with an overly low certainty"
" %.3f vs best choice certainty %.3f (Threshold: %.3f)\n",
bad_string.c_str(), word_choice->certainty(),
best_choice->certainty(),
max_certainty_delta + best_choice->certainty());
}
delete word_choice;
return false;
}
}
// Insert in the list in order of increasing rating, but knock out worse
// string duplicates.
WERD_CHOICE_IT it(&best_choices);
const std::string &new_str = word_choice->unichar_string();
bool inserted = false;
int num_choices = 0;
if (!it.empty()) {
do {
WERD_CHOICE *choice = it.data();
if (choice->rating() > word_choice->rating() && !inserted) {
// Time to insert.
it.add_before_stay_put(word_choice);
inserted = true;
if (num_choices == 0) {
best_choice = word_choice; // This is the new best.
}
++num_choices;
}
if (choice->unichar_string() == new_str) {
if (inserted) {
// New is better.
delete it.extract();
} else {
// Old is better.
if (debug) {
tprintf("Discarding duplicate choice \"%s\", rating %g vs %g\n",
new_str.c_str(), word_choice->rating(), choice->rating());
}
delete word_choice;
return false;
}
} else {
++num_choices;
if (num_choices > max_num_choices) {
delete it.extract();
}
}
it.forward();
} while (!it.at_first());
}
if (!inserted && num_choices < max_num_choices) {
it.add_to_end(word_choice);
inserted = true;
if (num_choices == 0) {
best_choice = word_choice; // This is the new best.
}
}
if (debug) {
if (inserted) {
tprintf("New %s", best_choice == word_choice ? "Best" : "Secondary");
} else {
tprintf("Poor");
}
word_choice->print(" Word Choice");
}
if (!inserted) {
delete word_choice;
return false;
}
return true;
}
// Simple helper moves the ownership of the pointer data from src to dest,
// first deleting anything in dest, and nulling out src afterwards.
template <class T>
static void MovePointerData(T **dest, T **src) {
delete *dest;
*dest = *src;
*src = nullptr;
}
// Prints a brief list of all the best choices.
void WERD_RES::PrintBestChoices() const {
std::string alternates_str;
WERD_CHOICE_IT it(const_cast<WERD_CHOICE_LIST *>(&best_choices));
for (it.mark_cycle_pt(); !it.cycled_list(); it.forward()) {
if (!it.at_first()) {
alternates_str += "\", \"";
}
alternates_str += it.data()->unichar_string();
}
tprintf("Alternates for \"%s\": {\"%s\"}\n",
best_choice->unichar_string().c_str(), alternates_str.c_str());
}
// Returns the sum of the widths of the blob between start_blob and last_blob
// inclusive.
int WERD_RES::GetBlobsWidth(int start_blob, int last_blob) const {
int result = 0;
for (int b = start_blob; b <= last_blob; ++b) {
result += blob_widths[b];
if (b < last_blob) {
result += blob_gaps[b];
}
}
return result;
}
// Returns the width of a gap between the specified blob and the next one.
int WERD_RES::GetBlobsGap(unsigned blob_index) const {
if (blob_index >= blob_gaps.size()) {
return 0;
}
return blob_gaps[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 nullptr if there is no
// BLOB_CHOICE matching the unichar_id at the given index.
BLOB_CHOICE *WERD_RES::GetBlobChoice(unsigned index) const {
if (index >= best_choice->length()) {
return nullptr;
}
BLOB_CHOICE_LIST *choices = GetBlobChoices(index);
return FindMatchingChoice(best_choice->unichar_id(index), choices);
}
// 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 *WERD_RES::GetBlobChoices(int index) const {
return best_choice->blob_choices(index, ratings);
}
// Moves the results fields from word to this. This takes ownership of all
// the data, so src can be destructed.
void WERD_RES::ConsumeWordResults(WERD_RES *word) {
denorm = word->denorm;
blob_row = word->blob_row;
MovePointerData(&chopped_word, &word->chopped_word);
MovePointerData(&rebuild_word, &word->rebuild_word);
MovePointerData(&box_word, &word->box_word);
for (auto data : seam_array) {
delete data;
}
seam_array = word->seam_array;
word->seam_array.clear();
// TODO: optimize moves.
best_state = word->best_state;
word->best_state.clear();
correct_text = word->correct_text;
word->correct_text.clear();
blob_widths = word->blob_widths;
word->blob_widths.clear();
blob_gaps = word->blob_gaps;
word->blob_gaps.clear();
if (ratings != nullptr) {
ratings->delete_matrix_pointers();
}
MovePointerData(&ratings, &word->ratings);
best_choice = word->best_choice;
MovePointerData(&raw_choice, &word->raw_choice);
best_choices.clear();
WERD_CHOICE_IT wc_it(&best_choices);
wc_it.add_list_after(&word->best_choices);
reject_map = word->reject_map;
if (word->blamer_bundle != nullptr) {
assert(blamer_bundle != nullptr);
blamer_bundle->CopyResults(*(word->blamer_bundle));
}
CopySimpleFields(*word);
}
// Replace the best choice and rebuild box word.
// choice must be from the current best_choices list.
void WERD_RES::ReplaceBestChoice(WERD_CHOICE *choice) {
best_choice = choice;
RebuildBestState();
SetupBoxWord();
// Make up a fake reject map of the right length to keep the
// rejection pass happy.
reject_map.initialise(best_state.size());
done = tess_accepted = tess_would_adapt = true;
SetScriptPositions();
}
// Builds the rebuild_word and sets the best_state from the chopped_word and
// the best_choice->state.
void WERD_RES::RebuildBestState() {
ASSERT_HOST(best_choice != nullptr);
delete rebuild_word;
rebuild_word = new TWERD;
if (seam_array.empty()) {
start_seam_list(chopped_word, &seam_array);
}
best_state.clear();
int start = 0;
for (unsigned i = 0; i < best_choice->length(); ++i) {
int length = best_choice->state(i);
best_state.push_back(length);
if (length > 1) {
SEAM::JoinPieces(seam_array, chopped_word->blobs, start,
start + length - 1);
}
TBLOB *blob = chopped_word->blobs[start];
rebuild_word->blobs.push_back(new TBLOB(*blob));
if (length > 1) {
SEAM::BreakPieces(seam_array, chopped_word->blobs, start,
start + length - 1);
}
start += length;
}
}
// Copies the chopped_word to the rebuild_word, faking a best_state as well.
// Also sets up the output box_word.
void WERD_RES::CloneChoppedToRebuild() {
delete rebuild_word;
rebuild_word = new TWERD(*chopped_word);
SetupBoxWord();
auto word_len = box_word->length();
best_state.reserve(word_len);
correct_text.reserve(word_len);
for (unsigned i = 0; i < word_len; ++i) {
best_state.push_back(1);
correct_text.emplace_back("");
}
}
// Sets/replaces the box_word with one made from the rebuild_word.
void WERD_RES::SetupBoxWord() {
delete box_word;
rebuild_word->ComputeBoundingBoxes();
box_word = tesseract::BoxWord::CopyFromNormalized(rebuild_word);
box_word->ClipToOriginalWord(denorm.block(), word);
}
// Sets up the script positions in the output best_choice using the best_choice
// to get the unichars, and the unicharset to get the target positions.
void WERD_RES::SetScriptPositions() {
best_choice->SetScriptPositions(small_caps, chopped_word);
}
// Sets all the blobs in all the words (raw choice and best choices) 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 WERD_RES::SetAllScriptPositions(tesseract::ScriptPos position) {
raw_choice->SetAllScriptPositions(position);
WERD_CHOICE_IT wc_it(&best_choices);
for (wc_it.mark_cycle_pt(); !wc_it.cycled_list(); wc_it.forward()) {
wc_it.data()->SetAllScriptPositions(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 WERD_RES::FakeClassifyWord(unsigned blob_count, BLOB_CHOICE **choices) {
// Setup the WERD_RES.
ASSERT_HOST(box_word != nullptr);
ASSERT_HOST(blob_count == box_word->length());
ClearWordChoices();
ClearRatings();
ratings = new MATRIX(blob_count, 1);
for (unsigned c = 0; c < blob_count; ++c) {
auto *choice_list = new BLOB_CHOICE_LIST;
BLOB_CHOICE_IT choice_it(choice_list);
choice_it.add_after_then_move(choices[c]);
ratings->put(c, c, choice_list);
}
FakeWordFromRatings(TOP_CHOICE_PERM);
reject_map.initialise(blob_count);
best_state.clear();
best_state.resize(blob_count, 1);
done = true;
}
// Creates a WERD_CHOICE for the word using the top choices from the leading
// diagonal of the ratings matrix.
void WERD_RES::FakeWordFromRatings(PermuterType permuter) {
int num_blobs = ratings->dimension();
auto *word_choice = new WERD_CHOICE(uch_set, num_blobs);
word_choice->set_permuter(permuter);
for (int b = 0; b < num_blobs; ++b) {
UNICHAR_ID unichar_id = UNICHAR_SPACE;
// Initialize rating and certainty like in WERD_CHOICE::make_bad().
float rating = WERD_CHOICE::kBadRating;
float certainty = -FLT_MAX;
BLOB_CHOICE_LIST *choices = ratings->get(b, b);
if (choices != nullptr && !choices->empty()) {
BLOB_CHOICE_IT bc_it(choices);
BLOB_CHOICE *choice = bc_it.data();
unichar_id = choice->unichar_id();
rating = choice->rating();
certainty = choice->certainty();
}
word_choice->append_unichar_id_space_allocated(unichar_id, 1, rating,
certainty);
}
LogNewRawChoice(word_choice);
// Ownership of word_choice taken by word here.
LogNewCookedChoice(1, false, word_choice);
}
// Copies the best_choice strings to the correct_text for adaption/training.
void WERD_RES::BestChoiceToCorrectText() {
correct_text.clear();
ASSERT_HOST(best_choice != nullptr);
for (unsigned i = 0; i < best_choice->length(); ++i) {
UNICHAR_ID choice_id = best_choice->unichar_id(i);
const char *blob_choice = uch_set->id_to_unichar(choice_id);
correct_text.emplace_back(blob_choice);
}
}
// 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 nullptr or returns true, setting the merged blob
// result to the class returned from class_cb.
// Returns true if anything was merged.
bool WERD_RES::ConditionalBlobMerge(
const std::function<UNICHAR_ID(UNICHAR_ID, UNICHAR_ID)> &class_cb,
const std::function<bool(const TBOX &, const TBOX &)> &box_cb) {
ASSERT_HOST(best_choice->empty() || ratings != nullptr);
bool modified = false;
for (unsigned i = 0; i + 1 < best_choice->length(); ++i) {
UNICHAR_ID new_id =
class_cb(best_choice->unichar_id(i), best_choice->unichar_id(i + 1));
if (new_id != INVALID_UNICHAR_ID &&
(box_cb == nullptr ||
box_cb(box_word->BlobBox(i), box_word->BlobBox(i + 1)))) {
// Raw choice should not be fixed.
best_choice->set_unichar_id(new_id, i);
modified = true;
MergeAdjacentBlobs(i);
const MATRIX_COORD &coord = best_choice->MatrixCoord(i);
if (!coord.Valid(*ratings)) {
ratings->IncreaseBandSize(coord.row + 1 - coord.col);
}
BLOB_CHOICE_LIST *blob_choices = GetBlobChoices(i);
if (FindMatchingChoice(new_id, blob_choices) == nullptr) {
// Insert a fake result.
auto *blob_choice = new BLOB_CHOICE;
blob_choice->set_unichar_id(new_id);
BLOB_CHOICE_IT bc_it(blob_choices);
bc_it.add_before_then_move(blob_choice);
}
}
}
return modified;
}
// Merges 2 adjacent blobs in the result (index and index+1) and corrects
// all the data to account for the change.
void WERD_RES::MergeAdjacentBlobs(unsigned index) {
if (reject_map.length() == best_choice->length()) {
reject_map.remove_pos(index);
}
best_choice->remove_unichar_id(index + 1);
rebuild_word->MergeBlobs(index, index + 2);
box_word->MergeBoxes(index, index + 2);
if (index + 1 < best_state.size()) {
best_state[index] += best_state[index + 1];
best_state.erase(best_state.begin() + index + 1);
}
}
// TODO(tkielbus) Decide between keeping this behavior here or modifying the
// training data.
// Utility function for fix_quotes
// Return true if the next character in the string (given the UTF8 length in
// bytes) is a quote character.
static int is_simple_quote(const char *signed_str, int length) {
const auto *str = reinterpret_cast<const unsigned char *>(signed_str);
// Standard 1 byte quotes.
return (length == 1 && (*str == '\'' || *str == '`')) ||
// UTF-8 3 bytes curved quotes.
(length == 3 &&
((*str == 0xe2 && *(str + 1) == 0x80 && *(str + 2) == 0x98) ||
(*str == 0xe2 && *(str + 1) == 0x80 && *(str + 2) == 0x99)));
}
// Callback helper for fix_quotes returns a double quote if both
// arguments are quote, otherwise INVALID_UNICHAR_ID.
UNICHAR_ID WERD_RES::BothQuotes(UNICHAR_ID id1, UNICHAR_ID id2) {
const char *ch = uch_set->id_to_unichar(id1);
const char *next_ch = uch_set->id_to_unichar(id2);
if (is_simple_quote(ch, strlen(ch)) &&
is_simple_quote(next_ch, strlen(next_ch))) {
return uch_set->unichar_to_id("\"");
}
return INVALID_UNICHAR_ID;
}
// Change pairs of quotes to double quotes.
void WERD_RES::fix_quotes() {
if (!uch_set->contains_unichar("\"") ||
!uch_set->get_enabled(uch_set->unichar_to_id("\""))) {
return; // Don't create it if it is disallowed.
}
using namespace std::placeholders; // for _1, _2
ConditionalBlobMerge(std::bind(&WERD_RES::BothQuotes, this, _1, _2), nullptr);
}
// Callback helper for fix_hyphens returns UNICHAR_ID of - if both
// arguments are hyphen, otherwise INVALID_UNICHAR_ID.
UNICHAR_ID WERD_RES::BothHyphens(UNICHAR_ID id1, UNICHAR_ID id2) {
const char *ch = uch_set->id_to_unichar(id1);
const char *next_ch = uch_set->id_to_unichar(id2);
if (strlen(ch) == 1 && strlen(next_ch) == 1 && (*ch == '-' || *ch == '~') &&
(*next_ch == '-' || *next_ch == '~')) {
return uch_set->unichar_to_id("-");
}
return INVALID_UNICHAR_ID;
}
// 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 WERD_RES::HyphenBoxesOverlap(const TBOX &box1, const TBOX &box2) {
return box1.right() >= box2.left();
}
// Change pairs of hyphens to a single hyphen if the bounding boxes touch
// Typically a long dash which has been segmented.
void WERD_RES::fix_hyphens() {
if (!uch_set->contains_unichar("-") ||
!uch_set->get_enabled(uch_set->unichar_to_id("-"))) {
return; // Don't create it if it is disallowed.
}
using namespace std::placeholders; // for _1, _2
ConditionalBlobMerge(std::bind(&WERD_RES::BothHyphens, this, _1, _2),
std::bind(&WERD_RES::HyphenBoxesOverlap, this, _1, _2));
}
// Callback helper for merge_tess_fails returns a space if both
// arguments are space, otherwise INVALID_UNICHAR_ID.
UNICHAR_ID WERD_RES::BothSpaces(UNICHAR_ID id1, UNICHAR_ID id2) {
if (id1 == id2 && id1 == uch_set->unichar_to_id(" ")) {
return id1;
} else {
return INVALID_UNICHAR_ID;
}
}
// Change pairs of tess failures to a single one
void WERD_RES::merge_tess_fails() {
using namespace std::placeholders; // for _1, _2
if (ConditionalBlobMerge(std::bind(&WERD_RES::BothSpaces, this, _1, _2),
nullptr)) {
unsigned len = best_choice->length();
ASSERT_HOST(reject_map.length() == len);
ASSERT_HOST(box_word->length() == len);
}
}
// Returns true if the collection of count pieces, starting at start, are all
// natural connected components, ie there are no real chops involved.
bool WERD_RES::PiecesAllNatural(int start, int count) const {
// all seams must have no splits.
for (int index = start; index < start + count - 1; ++index) {
if (index >= 0 && static_cast<size_t>(index) < seam_array.size()) {
SEAM *seam = seam_array[index];
if (seam != nullptr && seam->HasAnySplits()) {
return false;
}
}
}
return true;
}
WERD_RES::~WERD_RES() {
Clear();
}
void WERD_RES::Clear() {
if (combination) {
delete word;
}
word = nullptr;
delete blamer_bundle;
blamer_bundle = nullptr;
ClearResults();
}
void WERD_RES::ClearResults() {
done = false;
fontinfo = nullptr;
fontinfo2 = nullptr;
fontinfo_id_count = 0;
fontinfo_id2_count = 0;
delete bln_boxes;
bln_boxes = nullptr;
blob_row = nullptr;
delete chopped_word;
chopped_word = nullptr;
delete rebuild_word;
rebuild_word = nullptr;
delete box_word;
box_word = nullptr;
best_state.clear();
correct_text.clear();
for (auto data : seam_array) {
delete data;
}
seam_array.clear();
blob_widths.clear();
blob_gaps.clear();
ClearRatings();
ClearWordChoices();
if (blamer_bundle != nullptr) {
blamer_bundle->ClearResults();
}
}
void WERD_RES::ClearWordChoices() {
best_choice = nullptr;
delete raw_choice;
raw_choice = nullptr;
best_choices.clear();
delete ep_choice;
ep_choice = nullptr;
}
void WERD_RES::ClearRatings() {
if (ratings != nullptr) {
ratings->delete_matrix_pointers();
delete ratings;
ratings = nullptr;
}
}
int PAGE_RES_IT::cmp(const PAGE_RES_IT &other) const {
ASSERT_HOST(page_res == other.page_res);
if (other.block_res == nullptr) {
// other points to the end of the page.
if (block_res == nullptr) {
return 0;
}
return -1;
}
if (block_res == nullptr) {
return 1; // we point to the end of the page.
}
if (block_res == other.block_res) {
if (other.row_res == nullptr || row_res == nullptr) {
// this should only happen if we hit an image block.
return 0;
}
if (row_res == other.row_res) {
// we point to the same block and row.
ASSERT_HOST(other.word_res != nullptr && word_res != nullptr);
if (word_res == other.word_res) {
// we point to the same word!
return 0;
}
WERD_RES_IT word_res_it(&row_res->word_res_list);
for (word_res_it.mark_cycle_pt(); !word_res_it.cycled_list();
word_res_it.forward()) {
if (word_res_it.data() == word_res) {
return -1;
} else if (word_res_it.data() == other.word_res) {
return 1;
}
}
ASSERT_HOST("Error: Incomparable PAGE_RES_ITs" == nullptr);
}
// we both point to the same block, but different rows.
ROW_RES_IT row_res_it(&block_res->row_res_list);
for (row_res_it.mark_cycle_pt(); !row_res_it.cycled_list();
row_res_it.forward()) {
if (row_res_it.data() == row_res) {
return -1;
} else if (row_res_it.data() == other.row_res) {
return 1;
}
}
ASSERT_HOST("Error: Incomparable PAGE_RES_ITs" == nullptr);
}
// We point to different blocks.
BLOCK_RES_IT block_res_it(&page_res->block_res_list);
for (block_res_it.mark_cycle_pt(); !block_res_it.cycled_list();
block_res_it.forward()) {
if (block_res_it.data() == block_res) {
return -1;
} else if (block_res_it.data() == other.block_res) {
return 1;
}
}
// Shouldn't happen...
ASSERT_HOST("Error: Incomparable PAGE_RES_ITs" == nullptr);
return 0;
}
// Inserts the new_word as a combination owned by 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 *PAGE_RES_IT::InsertSimpleCloneWord(const WERD_RES &clone_res,
WERD *new_word) {
// Make a WERD_RES for the new_word.
auto *new_res = new WERD_RES(new_word);
new_res->CopySimpleFields(clone_res);
new_res->combination = true;
// Insert into the appropriate place in the ROW_RES.
WERD_RES_IT wr_it(&row()->word_res_list);
for (wr_it.mark_cycle_pt(); !wr_it.cycled_list(); wr_it.forward()) {
WERD_RES *word = wr_it.data();
if (word == word_res) {
break;
}
}
ASSERT_HOST(!wr_it.cycled_list());
wr_it.add_before_then_move(new_res);
if (wr_it.at_first()) {
// This is the new first word, so reset the member iterator so it
// detects the cycled_list state correctly.
ResetWordIterator();
}
return new_res;
}
// Helper computes the boundaries between blobs in the word. The blob bounds
// are likely very poor, if they come from LSTM, where it only outputs the
// character at one pixel within it, so we find the midpoints between them.
static void ComputeBlobEnds(const WERD_RES &word, const TBOX &clip_box,
C_BLOB_LIST *next_word_blobs,
std::vector<int> *blob_ends) {
C_BLOB_IT blob_it(word.word->cblob_list());
for (int length : word.best_state) {
// Get the bounding box of the fake blobs
TBOX blob_box = blob_it.data()->bounding_box();
blob_it.forward();
for (int b = 1; b < length; ++b) {
blob_box += blob_it.data()->bounding_box();
blob_it.forward();
}
// This blob_box is crap, so for now we are only looking for the
// boundaries between them.
int blob_end = INT32_MAX;
if (!blob_it.at_first() || next_word_blobs != nullptr) {
if (blob_it.at_first()) {
blob_it.set_to_list(next_word_blobs);
}
blob_end = (blob_box.right() + blob_it.data()->bounding_box().left()) / 2;
}
blob_end = ClipToRange<int>(blob_end, clip_box.left(), clip_box.right());
blob_ends->push_back(blob_end);
}
blob_ends->back() = clip_box.right();
}
// Helper computes the bounds of a word by restricting it to existing words
// that significantly overlap.
static TBOX ComputeWordBounds(const tesseract::PointerVector<WERD_RES> &words,
int w_index, TBOX prev_box, WERD_RES_IT w_it) {
constexpr int kSignificantOverlapFraction = 4;
TBOX clipped_box;
TBOX current_box = words[w_index]->word->bounding_box();
TBOX next_box;
if (static_cast<size_t>(w_index + 1) < words.size() &&
words[w_index + 1] != nullptr && words[w_index + 1]->word != nullptr) {
next_box = words[w_index + 1]->word->bounding_box();
}
for (w_it.forward(); !w_it.at_first() && w_it.data()->part_of_combo;
w_it.forward()) {
if (w_it.data() == nullptr || w_it.data()->word == nullptr) {
continue;
}
TBOX w_box = w_it.data()->word->bounding_box();
int height_limit = std::min<int>(w_box.height(), w_box.width() / 2);
int width_limit = w_box.width() / kSignificantOverlapFraction;
int min_significant_overlap = std::max(height_limit, width_limit);
int overlap = w_box.intersection(current_box).width();
int prev_overlap = w_box.intersection(prev_box).width();
int next_overlap = w_box.intersection(next_box).width();
if (overlap > min_significant_overlap) {
if (prev_overlap > min_significant_overlap) {
// We have no choice but to use the LSTM word edge.
clipped_box.set_left(current_box.left());
} else if (next_overlap > min_significant_overlap) {
// We have no choice but to use the LSTM word edge.
clipped_box.set_right(current_box.right());
} else {
clipped_box += w_box;
}
}
}
if (clipped_box.height() <= 0) {
clipped_box.set_top(current_box.top());
clipped_box.set_bottom(current_box.bottom());
}
if (clipped_box.width() <= 0) {
clipped_box = current_box;
}
return clipped_box;
}
// Helper moves the blob from src to dest. If it isn't contained by clip_box,
// the blob is replaced by a fake that is contained.
static TBOX MoveAndClipBlob(C_BLOB_IT *src_it, C_BLOB_IT *dest_it,
const TBOX &clip_box) {
C_BLOB *src_blob = src_it->extract();
TBOX box = src_blob->bounding_box();
if (!clip_box.contains(box)) {
int left =
ClipToRange<int>(box.left(), clip_box.left(), clip_box.right() - 1);
int right =
ClipToRange<int>(box.right(), clip_box.left() + 1, clip_box.right());
int top =
ClipToRange<int>(box.top(), clip_box.bottom() + 1, clip_box.top());
int bottom =
ClipToRange<int>(box.bottom(), clip_box.bottom(), clip_box.top() - 1);
box = TBOX(left, bottom, right, top);
delete src_blob;
src_blob = C_BLOB::FakeBlob(box);
}
dest_it->add_after_then_move(src_blob);
return box;
}
// 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 PAGE_RES_IT::ReplaceCurrentWord(
tesseract::PointerVector<WERD_RES> *words) {
if (words->empty()) {
DeleteCurrentWord();
return;
}
WERD_RES *input_word = word();
// Set the BOL/EOL flags on the words from the input word.
if (input_word->word->flag(W_BOL)) {
(*words)[0]->word->set_flag(W_BOL, true);
} else {
(*words)[0]->word->set_blanks(input_word->word->space());
}
words->back()->word->set_flag(W_EOL, input_word->word->flag(W_EOL));
// Move the blobs from the input word to the new set of words.
// If the input word_res is a combination, then the replacements will also be
// combinations, and will own their own words. If the input word_res is not a
// combination, then the final replacements will not be either, (although it
// is allowed for the input words to be combinations) and their words
// will get put on the row list. This maintains the ownership rules.
WERD_IT w_it(row()->row->word_list());
if (!input_word->combination) {
for (w_it.mark_cycle_pt(); !w_it.cycled_list(); w_it.forward()) {
WERD *word = w_it.data();
if (word == input_word->word) {
break;
}
}
// w_it is now set to the input_word's word.
ASSERT_HOST(!w_it.cycled_list());
}
// Insert into the appropriate place in the ROW_RES.
WERD_RES_IT wr_it(&row()->word_res_list);
for (wr_it.mark_cycle_pt(); !wr_it.cycled_list(); wr_it.forward()) {
WERD_RES *word = wr_it.data();
if (word == input_word) {
break;
}
}
ASSERT_HOST(!wr_it.cycled_list());
// Since we only have an estimate of the bounds between blobs, use the blob
// x-middle as the determiner of where to put the blobs
C_BLOB_IT src_b_it(input_word->word->cblob_list());
src_b_it.sort(&C_BLOB::SortByXMiddle);
C_BLOB_IT rej_b_it(input_word->word->rej_cblob_list());
rej_b_it.sort(&C_BLOB::SortByXMiddle);
TBOX clip_box;
for (size_t w = 0; w < words->size(); ++w) {
WERD_RES *word_w = (*words)[w];
clip_box = ComputeWordBounds(*words, w, clip_box, wr_it_of_current_word);
// Compute blob boundaries.
std::vector<int> blob_ends;
C_BLOB_LIST *next_word_blobs =
w + 1 < words->size() ? (*words)[w + 1]->word->cblob_list() : nullptr;
ComputeBlobEnds(*word_w, clip_box, next_word_blobs, &blob_ends);
// Remove the fake blobs on the current word, but keep safe for back-up if
// no blob can be found.
C_BLOB_LIST fake_blobs;
C_BLOB_IT fake_b_it(&fake_blobs);
fake_b_it.add_list_after(word_w->word->cblob_list());
fake_b_it.move_to_first();
word_w->word->cblob_list()->clear();
C_BLOB_IT dest_it(word_w->word->cblob_list());
// Build the box word as we move the blobs.
auto *box_word = new tesseract::BoxWord;
for (size_t i = 0; i < blob_ends.size(); ++i, fake_b_it.forward()) {
int end_x = blob_ends[i];
TBOX blob_box;
// Add the blobs up to end_x.
while (!src_b_it.empty() &&
src_b_it.data()->bounding_box().x_middle() < end_x) {
blob_box += MoveAndClipBlob(&src_b_it, &dest_it, clip_box);
src_b_it.forward();
}
while (!rej_b_it.empty() &&
rej_b_it.data()->bounding_box().x_middle() < end_x) {
blob_box += MoveAndClipBlob(&rej_b_it, &dest_it, clip_box);
rej_b_it.forward();
}
if (blob_box.null_box()) {
// Use the original box as a back-up.
blob_box = MoveAndClipBlob(&fake_b_it, &dest_it, clip_box);
}
box_word->InsertBox(i, blob_box);
}
delete word_w->box_word;
word_w->box_word = box_word;
if (!input_word->combination) {
// Insert word_w->word into the ROW. It doesn't own its word, so the
// ROW needs to own it.
w_it.add_before_stay_put(word_w->word);
word_w->combination = false;
}
(*words)[w] = nullptr; // We are taking ownership.
wr_it.add_before_stay_put(word_w);
}
// We have taken ownership of the words.
words->clear();
// Delete the current word, which has been replaced. We could just call
// DeleteCurrentWord, but that would iterate both lists again, and we know
// we are already in the right place.
if (!input_word->combination) {
delete w_it.extract();
}
delete wr_it.extract();
ResetWordIterator();
}
// Deletes the current WERD_RES and its underlying WERD.
void PAGE_RES_IT::DeleteCurrentWord() {
// Check that this word is as we expect. part_of_combos are NEVER iterated
// by the normal iterator, so we should never be trying to delete them.
ASSERT_HOST(!word_res->part_of_combo);
if (!word_res->combination) {
// Combinations own their own word, so we won't find the word on the
// row's word_list, but it is legitimate to try to delete them.
// Delete word from the ROW when not a combination.
WERD_IT w_it(row()->row->word_list());
for (w_it.mark_cycle_pt(); !w_it.cycled_list(); w_it.forward()) {
if (w_it.data() == word_res->word) {
break;
}
}
ASSERT_HOST(!w_it.cycled_list());
delete w_it.extract();
}
// Remove the WERD_RES for the new_word.
// Remove the WORD_RES from the ROW_RES.
WERD_RES_IT wr_it(&row()->word_res_list);
for (wr_it.mark_cycle_pt(); !wr_it.cycled_list(); wr_it.forward()) {
if (wr_it.data() == word_res) {
word_res = nullptr;
break;
}
}
ASSERT_HOST(!wr_it.cycled_list());
delete wr_it.extract();
ResetWordIterator();
}
// Makes the current word a fuzzy space if not already fuzzy. Updates
// corresponding part of combo if required.
void PAGE_RES_IT::MakeCurrentWordFuzzy() {
WERD *real_word = word_res->word;
if (!real_word->flag(W_FUZZY_SP) && !real_word->flag(W_FUZZY_NON)) {
real_word->set_flag(W_FUZZY_SP, true);
if (word_res->combination) {
// The next word should be the corresponding part of combo, but we have
// already stepped past it, so find it by search.
WERD_RES_IT wr_it(&row()->word_res_list);
for (wr_it.mark_cycle_pt();
!wr_it.cycled_list() && wr_it.data() != word_res; wr_it.forward()) {
}
wr_it.forward();
ASSERT_HOST(wr_it.data()->part_of_combo);
real_word = wr_it.data()->word;
ASSERT_HOST(!real_word->flag(W_FUZZY_SP) &&
!real_word->flag(W_FUZZY_NON));
real_word->set_flag(W_FUZZY_SP, true);
}
}
}
/*************************************************************************
* PAGE_RES_IT::restart_page
*
* Set things up at the start of the page
*************************************************************************/
WERD_RES *PAGE_RES_IT::start_page(bool empty_ok) {
block_res_it.set_to_list(&page_res->block_res_list);
block_res_it.mark_cycle_pt();
prev_block_res = nullptr;
prev_row_res = nullptr;
prev_word_res = nullptr;
block_res = nullptr;
row_res = nullptr;
word_res = nullptr;
next_block_res = nullptr;
next_row_res = nullptr;
next_word_res = nullptr;
internal_forward(true, empty_ok);
return internal_forward(false, empty_ok);
}
// Recovers from operations on the current word, such as in InsertCloneWord
// and DeleteCurrentWord.
// Resets the word_res_it so that it is one past the next_word_res, as
// it should be after internal_forward. If next_row_res != row_res,
// then the next_word_res is in the next row, so there is no need to do
// anything to word_res_it, but it is still a good idea to reset the pointers
// word_res and prev_word_res, which are still in the current row.
void PAGE_RES_IT::ResetWordIterator() {
if (row_res == next_row_res) {
// Reset the member iterator so it can move forward and detect the
// cycled_list state correctly.
word_res_it.move_to_first();
for (word_res_it.mark_cycle_pt();
!word_res_it.cycled_list() && word_res_it.data() != next_word_res;
word_res_it.forward()) {
if (!word_res_it.data()->part_of_combo) {
if (prev_row_res == row_res) {
prev_word_res = word_res;
}
word_res = word_res_it.data();
}
}
ASSERT_HOST(!word_res_it.cycled_list());
wr_it_of_next_word = word_res_it;
word_res_it.forward();
} else {
// word_res_it is OK, but reset word_res and prev_word_res if needed.
WERD_RES_IT wr_it(&row_res->word_res_list);
for (wr_it.mark_cycle_pt(); !wr_it.cycled_list(); wr_it.forward()) {
if (!wr_it.data()->part_of_combo) {
if (prev_row_res == row_res) {
prev_word_res = word_res;
}
word_res = wr_it.data();
}
}
}
}
/*************************************************************************
* PAGE_RES_IT::internal_forward
*
* Find the next word on the page. If empty_ok is true, then non-text blocks
* and text blocks with no text are visited as if they contain a single
* imaginary word in a single imaginary row. (word() and row() both return
*nullptr in such a block and the return value is nullptr.) If empty_ok is
*false, the old behaviour is maintained. Each real word is visited and empty
*and non-text blocks and rows are skipped. new_block is used to initialize the
*iterators for a new block. The iterator maintains pointers to block, row and
*word for the previous, current and next words. These are correct, regardless
*of block/row boundaries. nullptr values denote start and end of the page.
*************************************************************************/
WERD_RES *PAGE_RES_IT::internal_forward(bool new_block, bool empty_ok) {
bool new_row = false;
prev_block_res = block_res;
prev_row_res = row_res;
prev_word_res = word_res;
block_res = next_block_res;
row_res = next_row_res;
word_res = next_word_res;
wr_it_of_current_word = wr_it_of_next_word;
next_block_res = nullptr;
next_row_res = nullptr;
next_word_res = nullptr;
while (!block_res_it.cycled_list()) {
if (new_block) {
new_block = false;
row_res_it.set_to_list(&block_res_it.data()->row_res_list);
row_res_it.mark_cycle_pt();
if (row_res_it.empty() && empty_ok) {
next_block_res = block_res_it.data();
break;
}
new_row = true;
}
while (!row_res_it.cycled_list()) {
if (new_row) {
new_row = false;
word_res_it.set_to_list(&row_res_it.data()->word_res_list);
word_res_it.mark_cycle_pt();
}
// Skip any part_of_combo words.
while (!word_res_it.cycled_list() && word_res_it.data()->part_of_combo) {
word_res_it.forward();
}
if (!word_res_it.cycled_list()) {
next_block_res = block_res_it.data();
next_row_res = row_res_it.data();
next_word_res = word_res_it.data();
wr_it_of_next_word = word_res_it;
word_res_it.forward();
goto foundword;
}
// end of row reached
row_res_it.forward();
new_row = true;
}
// end of block reached
block_res_it.forward();
new_block = true;
}
foundword:
// Update prev_word_best_choice pointer.
if (page_res != nullptr && page_res->prev_word_best_choice != nullptr) {
*page_res->prev_word_best_choice = (new_block || prev_word_res == nullptr)
? nullptr
: prev_word_res->best_choice;
}
return word_res;
}
/*************************************************************************
* PAGE_RES_IT::restart_row()
*
* Move to the beginning (leftmost word) of the current row.
*************************************************************************/
WERD_RES *PAGE_RES_IT::restart_row() {
ROW_RES *row = this->row();
if (!row) {
return nullptr;
}
for (restart_page(); this->row() != row; forward()) {
// pass
}
return word();
}
/*************************************************************************
* PAGE_RES_IT::forward_paragraph
*
* Move to the beginning of the next paragraph, allowing empty blocks.
*************************************************************************/
WERD_RES *PAGE_RES_IT::forward_paragraph() {
while (block_res == next_block_res &&
(next_row_res != nullptr && next_row_res->row != nullptr &&
row_res->row->para() == next_row_res->row->para())) {
internal_forward(false, true);
}
return internal_forward(false, true);
}
/*************************************************************************
* PAGE_RES_IT::forward_block
*
* Move to the beginning of the next block, allowing empty blocks.
*************************************************************************/
WERD_RES *PAGE_RES_IT::forward_block() {
while (block_res == next_block_res) {
internal_forward(false, true);
}
return internal_forward(false, true);
}
void PAGE_RES_IT::rej_stat_word() {
int16_t chars_in_word;
int16_t rejects_in_word = 0;
chars_in_word = word_res->reject_map.length();
page_res->char_count += chars_in_word;
block_res->char_count += chars_in_word;
row_res->char_count += chars_in_word;
rejects_in_word = word_res->reject_map.reject_count();
page_res->rej_count += rejects_in_word;
block_res->rej_count += rejects_in_word;
row_res->rej_count += rejects_in_word;
if (chars_in_word == rejects_in_word) {
row_res->whole_word_rej_count += rejects_in_word;
}
}
} // namespace tesseract
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