tesseract/ccmain/cube_control.cpp
2016-11-25 13:13:28 +01:00

443 lines
16 KiB
C++

/******************************************************************
* File: cube_control.cpp
* Description: Tesseract class methods for invoking cube convolutional
* neural network word recognizer.
* Author: Raquel Romano
* Created: September 2009
*
* (C) Copyright 2009, Google Inc.
** 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 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