tesseract/ccmain/cube_control.cpp
Jim O'Regan 524a61452d Doxygen
Squashed commit from https://github.com/tesseract-ocr/tesseract/tree/more-doxygen
closes #14

Commits:
6317305  doxygen
9f42f69  doxygen
0fc4d52  doxygen
37b4b55  fix typo
bded8f1  some more doxy
020eb00  slight tweak
524666d  doxygenify
2a36a3e  doxygenify
229d218  doxygenify
7fd28ae  doxygenify
a8c64bc  doxygenify
f5d21b6  fix
5d8ede8  doxygenify
a58a4e0  language_model.cpp
fa85709  lm_pain_points.cpp lm_state.cpp
6418da3  merge
06190ba  Merge branch 'old_doxygen_merge' into more-doxygen
84acf08  Merge branch 'master' into more-doxygen
50fe1ff  pagewalk.cpp cube_reco_context.cpp
2982583  change to relative
192a24a  applybox.cpp, take one
8eeb053  delete docs for obsolete params
52e4c77  modernise classify/ocrfeatures.cpp
2a1cba6  modernise cutil/emalloc.cpp
773e006  silence doxygen warning
aeb1731  silence doxygen warning
f18387f  silence doxygen; new params are unused?
15ad6bd  doxygenify cutil/efio.cpp
c8b5dad  doxygenify cutil/danerror.cpp
784450f  the globals and exceptions parts are obsolete; remove
8bca324  doxygen classify/normfeat.cpp
9bcbe16  doxygen classify/normmatch.cpp
aa9a971  doxygen ccmain/cube_control.cpp
c083ff2  doxygen ccmain/cube_reco_context.cpp
f842850  params changed
5c94f12  doxygen ccmain/cubeclassifier.cpp
15ba750  case sensitive
f5c71d4  case sensitive
f85655b  doxygen classify/intproto.cpp
4bbc7aa  partial doxygen classify/mfx.cpp
dbb6041  partial doxygen classify/intproto.cpp
2aa72db  finish doxygen classify/intproto.cpp
0b8de99  doxygen training/mftraining.cpp
0b5b35c  partial doxygen ccstruct/coutln.cpp
b81c766  partial doxygen ccstruct/coutln.cpp
40fc415  finished? doxygen ccstruct/coutln.cpp
6e4165c  doxygen classify/clusttool.cpp
0267dec  doxygen classify/cutoffs.cpp
7f0c70c  doxygen classify/fpoint.cpp
512f3bd  ignore ~ files
5668a52  doxygen classify/intmatcher.cpp
84788d4  doxygen classify/kdtree.cpp
29f36ca  doxygen classify/mfoutline.cpp
40b94b1  silence doxygen warnings
6c511b9  doxygen classify/mfx.cpp
f9b4080  doxygen classify/outfeat.cpp
aa1df05  doxygen classify/picofeat.cpp
cc5f466  doxygen training/cntraining.cpp
cce044f  doxygen training/commontraining.cpp
167e216  missing param
9498383  renamed params
37eeac2  renamed param
d87b5dd  case
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b858db8  typo
4c2a838  h2 context?
81a2c0c  fix some param names; add some missing params, no docs
bcf8a4c  add some missing params, no docs
af77f86  add some missing params, no docs; fix some param names
01df24e  fix some params
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cd21226  rm some missing params, add some new ones
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312ce37  missing param; rename one
ec2fdec  missing param
05e15e0  missing params
d515858  change "<" to &lt; to make doxygen happy
b476a28  wrong place
2015-07-20 18:48:00 +01:00

433 lines
15 KiB
C++

/******************************************************************
* File: cube_control.cpp
* Description: Tesseract class methods for invoking cube convolutional
* neural network word recognizer.
* Author: Raquel Romano
* Created: September 2009
*
**********************************************************************/
// Include automatically generated configuration file if running autoconf.
#ifdef HAVE_CONFIG_H
#include "config_auto.h"
#endif
#include "allheaders.h"
#include "cube_object.h"
#include "cube_reco_context.h"
#include "tesseractclass.h"
#include "tesseract_cube_combiner.h"
namespace tesseract {
/**
* @name convert_prob_to_tess_certainty
*
* Normalize a probability in the range [0.0, 1.0] to a tesseract
* certainty in the range [-20.0, 0.0]
*/
static float convert_prob_to_tess_certainty(float prob) {
return (prob - 1.0) * 20.0;
}
/**
* @name char_box_to_tbox
*
* Create a TBOX from a character bounding box. If nonzero, the
* x_offset accounts for any additional padding of the word box that
* should be taken into account.
*
*/
TBOX char_box_to_tbox(Box* char_box, TBOX word_box, int x_offset) {
l_int32 left;
l_int32 top;
l_int32 width;
l_int32 height;
l_int32 right;
l_int32 bottom;
boxGetGeometry(char_box, &left, &top, &width, &height);
left += word_box.left() - x_offset;
right = left + width;
top = word_box.bottom() + word_box.height() - top;
bottom = top - height;
return TBOX(left, bottom, right, top);
}
/**
* @name extract_cube_state
*
* Extract CharSamp objects and character bounding boxes from the
* CubeObject's state. The caller should free both structres.
*
*/
bool Tesseract::extract_cube_state(CubeObject* cube_obj,
int* num_chars,
Boxa** char_boxes,
CharSamp*** char_samples) {
if (!cube_obj) {
if (cube_debug_level > 0) {
tprintf("Cube WARNING (extract_cube_state): Invalid cube object "
"passed to extract_cube_state\n");
}
return false;
}
// Note that the CubeObject accessors return either the deslanted or
// regular objects search object or beam search object, whichever
// was used in the last call to Recognize()
CubeSearchObject* cube_search_obj = cube_obj->SrchObj();
if (!cube_search_obj) {
if (cube_debug_level > 0) {
tprintf("Cube WARNING (Extract_cube_state): Could not retrieve "
"cube's search object in extract_cube_state.\n");
}
return false;
}
BeamSearch *beam_search_obj = cube_obj->BeamObj();
if (!beam_search_obj) {
if (cube_debug_level > 0) {
tprintf("Cube WARNING (Extract_cube_state): Could not retrieve "
"cube's beam search object in extract_cube_state.\n");
}
return false;
}
// Get the character samples and bounding boxes by backtracking
// through the beam search path
int best_node_index = beam_search_obj->BestPresortedNodeIndex();
*char_samples = beam_search_obj->BackTrack(
cube_search_obj, best_node_index, num_chars, NULL, char_boxes);
if (!*char_samples)
return false;
return true;
}
/**
* @name create_cube_box_word
*
* Fill the given BoxWord with boxes from character bounding
* boxes. The char_boxes have local coordinates w.r.t. the
* word bounding box, i.e., the left-most character bbox of each word
* has (0,0) left-top coord, but the BoxWord must be defined in page
* coordinates.
*/
bool Tesseract::create_cube_box_word(Boxa *char_boxes,
int num_chars,
TBOX word_box,
BoxWord* box_word) {
if (!box_word) {
if (cube_debug_level > 0) {
tprintf("Cube WARNING (create_cube_box_word): Invalid box_word.\n");
}
return false;
}
// Find the x-coordinate of left-most char_box, which could be
// nonzero if the word image was padded before recognition took place.
int x_offset = -1;
for (int i = 0; i < num_chars; ++i) {
Box* char_box = boxaGetBox(char_boxes, i, L_CLONE);
if (x_offset < 0 || char_box->x < x_offset) {
x_offset = char_box->x;
}
boxDestroy(&char_box);
}
for (int i = 0; i < num_chars; ++i) {
Box* char_box = boxaGetBox(char_boxes, i, L_CLONE);
TBOX tbox = char_box_to_tbox(char_box, word_box, x_offset);
boxDestroy(&char_box);
box_word->InsertBox(i, tbox);
}
return true;
}
/**
* @name init_cube_objects
*
* Instantiates Tesseract object's CubeRecoContext and TesseractCubeCombiner.
* Returns false if cube context could not be created or if load_combiner is
* true, but the combiner could not be loaded.
*/
bool Tesseract::init_cube_objects(bool load_combiner,
TessdataManager *tessdata_manager) {
ASSERT_HOST(cube_cntxt_ == NULL);
ASSERT_HOST(tess_cube_combiner_ == NULL);
// Create the cube context object
cube_cntxt_ = CubeRecoContext::Create(this, tessdata_manager, &unicharset);
if (cube_cntxt_ == NULL) {
if (cube_debug_level > 0) {
tprintf("Cube WARNING (Tesseract::init_cube_objects()): Failed to "
"instantiate CubeRecoContext\n");
}
return false;
}
// Create the combiner object and load the combiner net for target languages.
if (load_combiner) {
tess_cube_combiner_ = new tesseract::TesseractCubeCombiner(cube_cntxt_);
if (!tess_cube_combiner_ || !tess_cube_combiner_->LoadCombinerNet()) {
delete cube_cntxt_;
cube_cntxt_ = NULL;
if (tess_cube_combiner_ != NULL) {
delete tess_cube_combiner_;
tess_cube_combiner_ = NULL;
}
if (cube_debug_level > 0)
tprintf("Cube ERROR (Failed to instantiate TesseractCubeCombiner\n");
return false;
}
}
return true;
}
/**
* @name run_cube_combiner
*
* Iterates through tesseract's results and calls cube on each word,
* combining the results with the existing tesseract result.
*/
void Tesseract::run_cube_combiner(PAGE_RES *page_res) {
if (page_res == NULL || tess_cube_combiner_ == NULL)
return;
PAGE_RES_IT page_res_it(page_res);
// Iterate through the word results and call cube on each word.
for (page_res_it.restart_page(); page_res_it.word () != NULL;
page_res_it.forward()) {
BLOCK* block = page_res_it.block()->block;
if (block->poly_block() != NULL && !block->poly_block()->IsText())
continue; // Don't deal with non-text blocks.
WERD_RES* word = page_res_it.word();
// Skip cube entirely if tesseract's certainty is greater than threshold.
int combiner_run_thresh = convert_prob_to_tess_certainty(
cube_cntxt_->Params()->CombinerRunThresh());
if (word->best_choice->certainty() >= combiner_run_thresh) {
continue;
}
// Use the same language as Tesseract used for the word.
Tesseract* lang_tess = word->tesseract;
// Setup a trial WERD_RES in which to classify with cube.
WERD_RES cube_word;
cube_word.InitForRetryRecognition(*word);
cube_word.SetupForRecognition(lang_tess->unicharset, this, BestPix(),
OEM_CUBE_ONLY,
NULL, false, false, false,
page_res_it.row()->row,
page_res_it.block()->block);
CubeObject *cube_obj = lang_tess->cube_recognize_word(
page_res_it.block()->block, &cube_word);
if (cube_obj != NULL)
lang_tess->cube_combine_word(cube_obj, &cube_word, word);
delete cube_obj;
}
}
/**
* @name cube_word_pass1
*
* Recognizes a single word using (only) cube. Compatible with
* Tesseract's classify_word_pass1/classify_word_pass2.
*/
void Tesseract::cube_word_pass1(BLOCK* block, ROW *row, WERD_RES *word) {
CubeObject *cube_obj = cube_recognize_word(block, word);
delete cube_obj;
}
/**
* @name cube_recognize_word
*
* Cube recognizer to recognize a single word as with classify_word_pass1
* but also returns the cube object in case the combiner is needed.
*/
CubeObject* Tesseract::cube_recognize_word(BLOCK* block, WERD_RES* word) {
if (!cube_binary_ || !cube_cntxt_) {
if (cube_debug_level > 0 && !cube_binary_)
tprintf("Tesseract::run_cube(): NULL binary image.\n");
word->SetupFake(unicharset);
return NULL;
}
TBOX word_box = word->word->bounding_box();
if (block != NULL && (block->re_rotation().x() != 1.0f ||
block->re_rotation().y() != 0.0f)) {
// TODO(rays) We have to rotate the bounding box to get the true coords.
// This will be achieved in the future via DENORM.
// In the mean time, cube can't process this word.
if (cube_debug_level > 0) {
tprintf("Cube can't process rotated word at:");
word_box.print();
}
word->SetupFake(unicharset);
return NULL;
}
CubeObject* cube_obj = new tesseract::CubeObject(
cube_cntxt_, cube_binary_, word_box.left(),
pixGetHeight(cube_binary_) - word_box.top(),
word_box.width(), word_box.height());
if (!cube_recognize(cube_obj, block, word)) {
delete cube_obj;
return NULL;
}
return cube_obj;
}
/**
* @name cube_combine_word
*
* Combines the cube and tesseract results for a single word, leaving the
* result in tess_word.
*/
void Tesseract::cube_combine_word(CubeObject* cube_obj, WERD_RES* cube_word,
WERD_RES* tess_word) {
float combiner_prob = tess_cube_combiner_->CombineResults(tess_word,
cube_obj);
// If combiner probability is greater than tess/cube combiner
// classifier threshold, i.e. tesseract wins, then just return the
// tesseract result unchanged, as the combiner knows nothing about how
// correct the answer is. If cube and tesseract agree, then improve the
// scores before returning.
WERD_CHOICE* tess_best = tess_word->best_choice;
WERD_CHOICE* cube_best = cube_word->best_choice;
if (cube_debug_level || classify_debug_level) {
tprintf("Combiner prob = %g vs threshold %g\n",
combiner_prob, cube_cntxt_->Params()->CombinerClassifierThresh());
}
if (combiner_prob >=
cube_cntxt_->Params()->CombinerClassifierThresh()) {
if (tess_best->unichar_string() == cube_best->unichar_string()) {
// Cube and tess agree, so improve the scores.
tess_best->set_rating(tess_best->rating() / 2);
tess_best->set_certainty(tess_best->certainty() / 2);
}
return;
}
// Cube wins.
// It is better for the language combiner to have all tesseract scores,
// so put them in the cube result.
cube_best->set_rating(tess_best->rating());
cube_best->set_certainty(tess_best->certainty());
if (cube_debug_level || classify_debug_level) {
tprintf("Cube INFO: tesseract result replaced by cube: %s -> %s\n",
tess_best->unichar_string().string(),
cube_best->unichar_string().string());
}
tess_word->ConsumeWordResults(cube_word);
}
/**
* @name cube_recognize
*
* Call cube on the current word, and write the result to word.
* Sets up a fake result and returns false if something goes wrong.
*/
bool Tesseract::cube_recognize(CubeObject *cube_obj, BLOCK* block,
WERD_RES *word) {
// Run cube
WordAltList *cube_alt_list = cube_obj->RecognizeWord();
if (!cube_alt_list || cube_alt_list->AltCount() <= 0) {
if (cube_debug_level > 0) {
tprintf("Cube returned nothing for word at:");
word->word->bounding_box().print();
}
word->SetupFake(unicharset);
return false;
}
// Get cube's best result and its probability, mapped to tesseract's
// certainty range
char_32 *cube_best_32 = cube_alt_list->Alt(0);
double cube_prob = CubeUtils::Cost2Prob(cube_alt_list->AltCost(0));
float cube_certainty = convert_prob_to_tess_certainty(cube_prob);
string cube_best_str;
CubeUtils::UTF32ToUTF8(cube_best_32, &cube_best_str);
// Retrieve Cube's character bounding boxes and CharSamples,
// corresponding to the most recent call to RecognizeWord().
Boxa *char_boxes = NULL;
CharSamp **char_samples = NULL;;
int num_chars;
if (!extract_cube_state(cube_obj, &num_chars, &char_boxes, &char_samples)
&& cube_debug_level > 0) {
tprintf("Cube WARNING (Tesseract::cube_recognize): Cannot extract "
"cube state.\n");
word->SetupFake(unicharset);
return false;
}
// Convert cube's character bounding boxes to a BoxWord.
BoxWord cube_box_word;
TBOX tess_word_box = word->word->bounding_box();
if (word->denorm.block() != NULL)
tess_word_box.rotate(word->denorm.block()->re_rotation());
bool box_word_success = create_cube_box_word(char_boxes, num_chars,
tess_word_box,
&cube_box_word);
boxaDestroy(&char_boxes);
if (!box_word_success) {
if (cube_debug_level > 0) {
tprintf("Cube WARNING (Tesseract::cube_recognize): Could not "
"create cube BoxWord\n");
}
word->SetupFake(unicharset);
return false;
}
// Fill tesseract result's fields with cube results
fill_werd_res(cube_box_word, cube_best_str.c_str(), word);
// Create cube's best choice.
BLOB_CHOICE** choices = new BLOB_CHOICE*[num_chars];
for (int i = 0; i < num_chars; ++i) {
UNICHAR_ID uch_id =
cube_cntxt_->CharacterSet()->UnicharID(char_samples[i]->StrLabel());
choices[i] = new BLOB_CHOICE(uch_id, -cube_certainty, cube_certainty,
-1, 0.0f, 0.0f, 0.0f, BCC_STATIC_CLASSIFIER);
}
word->FakeClassifyWord(num_chars, choices);
// within a word, cube recognizes the word in reading order.
word->best_choice->set_unichars_in_script_order(true);
delete [] choices;
delete [] char_samples;
// Some sanity checks
ASSERT_HOST(word->best_choice->length() == word->reject_map.length());
if (cube_debug_level || classify_debug_level) {
tprintf("Cube result: %s r=%g, c=%g\n",
word->best_choice->unichar_string().string(),
word->best_choice->rating(),
word->best_choice->certainty());
}
return true;
}
/**
* @name fill_werd_res
*
* Fill Tesseract's word result fields with cube's.
*
*/
void Tesseract::fill_werd_res(const BoxWord& cube_box_word,
const char* cube_best_str,
WERD_RES* tess_werd_res) {
delete tess_werd_res->box_word;
tess_werd_res->box_word = new BoxWord(cube_box_word);
tess_werd_res->box_word->ClipToOriginalWord(tess_werd_res->denorm.block(),
tess_werd_res->word);
// Fill text and remaining fields
tess_werd_res->word->set_text(cube_best_str);
tess_werd_res->tess_failed = FALSE;
tess_werd_res->tess_accepted = tess_acceptable_word(tess_werd_res);
// There is no output word, so we can' call AdaptableWord, but then I don't
// think we need to. Fudge the result with accepted.
tess_werd_res->tess_would_adapt = tess_werd_res->tess_accepted;
// Set word to done, i.e., ignore all of tesseract's tests for rejection
tess_werd_res->done = tess_werd_res->tess_accepted;
}
} // namespace tesseract