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https://github.com/tesseract-ocr/tesseract.git
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d11dc049e3
git-svn-id: https://tesseract-ocr.googlecode.com/svn/trunk@1015 d0cd1f9f-072b-0410-8dd7-cf729c803f20
330 lines
13 KiB
C++
330 lines
13 KiB
C++
/**********************************************************************
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* File: tfacepp.cpp (Formerly tface++.c)
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* Description: C++ side of the C/C++ Tess/Editor interface.
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* Author: Ray Smith
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* Created: Thu Apr 23 15:39:23 BST 1992
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*
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* (C) Copyright 1992, Hewlett-Packard Ltd.
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** Licensed under the Apache License, Version 2.0 (the "License");
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** you may not use this file except in compliance with the License.
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** You may obtain a copy of the License at
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** http://www.apache.org/licenses/LICENSE-2.0
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** Unless required by applicable law or agreed to in writing, software
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** distributed under the License is distributed on an "AS IS" BASIS,
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** WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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** See the License for the specific language governing permissions and
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** limitations under the License.
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*
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**********************************************************************/
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#ifdef _MSC_VER
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#pragma warning(disable:4244) // Conversion warnings
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#pragma warning(disable:4305) // int/float warnings
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#pragma warning(disable:4800) // int/bool warnings
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#endif
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#include <math.h>
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#include "blamer.h"
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#include "errcode.h"
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#include "ratngs.h"
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#include "reject.h"
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#include "tesseractclass.h"
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#include "werd.h"
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#define MAX_UNDIVIDED_LENGTH 24
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/**********************************************************************
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* recog_word
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*
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* Convert the word to tess form and pass it to the tess segmenter.
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* Convert the output back to editor form.
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**********************************************************************/
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namespace tesseract {
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void Tesseract::recog_word(WERD_RES *word) {
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if (wordrec_skip_no_truth_words && (word->blamer_bundle == NULL ||
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word->blamer_bundle->incorrect_result_reason() == IRR_NO_TRUTH)) {
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if (classify_debug_level) tprintf("No truth for word - skipping\n");
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word->tess_failed = true;
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return;
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}
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ASSERT_HOST(!word->chopped_word->blobs.empty());
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recog_word_recursive(word);
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word->SetupBoxWord();
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if (word->best_choice->length() != word->box_word->length()) {
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tprintf("recog_word ASSERT FAIL String:\"%s\"; "
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"Strlen=%d; #Blobs=%d\n",
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word->best_choice->debug_string().string(),
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word->best_choice->length(), word->box_word->length());
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}
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ASSERT_HOST(word->best_choice->length() == word->box_word->length());
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// Check that the ratings matrix size matches the sum of all the
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// segmentation states.
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if (!word->StatesAllValid()) {
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tprintf("Not all words have valid states relative to ratings matrix!!");
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word->DebugWordChoices(true, NULL);
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ASSERT_HOST(word->StatesAllValid());
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}
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if (tessedit_override_permuter) {
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/* Override the permuter type if a straight dictionary check disagrees. */
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uinT8 perm_type = word->best_choice->permuter();
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if ((perm_type != SYSTEM_DAWG_PERM) &&
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(perm_type != FREQ_DAWG_PERM) && (perm_type != USER_DAWG_PERM)) {
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uinT8 real_dict_perm_type = dict_word(*word->best_choice);
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if (((real_dict_perm_type == SYSTEM_DAWG_PERM) ||
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(real_dict_perm_type == FREQ_DAWG_PERM) ||
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(real_dict_perm_type == USER_DAWG_PERM)) &&
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(alpha_count(word->best_choice->unichar_string().string(),
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word->best_choice->unichar_lengths().string()) > 0)) {
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word->best_choice->set_permuter(real_dict_perm_type); // use dict perm
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}
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}
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if (tessedit_rejection_debug &&
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perm_type != word->best_choice->permuter()) {
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tprintf("Permuter Type Flipped from %d to %d\n",
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perm_type, word->best_choice->permuter());
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}
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}
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// Factored out from control.cpp
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ASSERT_HOST((word->best_choice == NULL) == (word->raw_choice == NULL));
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if (word->best_choice == NULL || word->best_choice->length() == 0 ||
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static_cast<int>(strspn(word->best_choice->unichar_string().string(),
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" ")) == word->best_choice->length()) {
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word->tess_failed = true;
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word->reject_map.initialise(word->box_word->length());
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word->reject_map.rej_word_tess_failure();
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} else {
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word->tess_failed = false;
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}
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}
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/**********************************************************************
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* recog_word_recursive
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*
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* Convert the word to tess form and pass it to the tess segmenter.
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* Convert the output back to editor form.
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**********************************************************************/
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void Tesseract::recog_word_recursive(WERD_RES *word) {
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int word_length = word->chopped_word->NumBlobs(); // no of blobs
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if (word_length > MAX_UNDIVIDED_LENGTH) {
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return split_and_recog_word(word);
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}
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cc_recog(word);
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word_length = word->rebuild_word->NumBlobs(); // No of blobs in output.
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// Do sanity checks and minor fixes on best_choice.
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if (word->best_choice->length() > word_length) {
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word->best_choice->make_bad(); // should never happen
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tprintf("recog_word: Discarded long string \"%s\""
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" (%d characters vs %d blobs)\n",
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word->best_choice->unichar_string().string(),
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word->best_choice->length(), word_length);
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tprintf("Word is at:");
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word->word->bounding_box().print();
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}
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if (word->best_choice->length() < word_length) {
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UNICHAR_ID space_id = unicharset.unichar_to_id(" ");
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while (word->best_choice->length() < word_length) {
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word->best_choice->append_unichar_id(space_id, 1, 0.0,
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word->best_choice->certainty());
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}
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}
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}
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/**********************************************************************
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* split_and_recog_word
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*
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* Split the word into 2 smaller pieces at the largest gap.
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* Recognize the pieces and stick the results back together.
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**********************************************************************/
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void Tesseract::split_and_recog_word(WERD_RES *word) {
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// Find the biggest blob gap in the chopped_word.
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int bestgap = -MAX_INT32;
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int split_index = 0;
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for (int b = 1; b < word->chopped_word->NumBlobs(); ++b) {
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TBOX prev_box = word->chopped_word->blobs[b - 1]->bounding_box();
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TBOX blob_box = word->chopped_word->blobs[b]->bounding_box();
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int gap = blob_box.left() - prev_box.right();
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if (gap > bestgap) {
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bestgap = gap;
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split_index = b;
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}
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}
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ASSERT_HOST(split_index > 0);
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WERD_RES *word2 = NULL;
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BlamerBundle *orig_bb = NULL;
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split_word(word, split_index, &word2, &orig_bb);
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// Recognize the first part of the word.
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recog_word_recursive(word);
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// Recognize the second part of the word.
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recog_word_recursive(word2);
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join_words(word, word2, orig_bb);
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}
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/**********************************************************************
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* split_word
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*
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* Split a given WERD_RES in place into two smaller words for recognition.
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* split_pt is the index of the first blob to go in the second word.
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* The underlying word is left alone, only the TWERD (and subsequent data)
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* are split up. orig_blamer_bundle is set to the original blamer bundle,
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* and will now be owned by the caller. New blamer bundles are forged for the
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* two pieces.
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**********************************************************************/
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void Tesseract::split_word(WERD_RES *word,
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int split_pt,
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WERD_RES **right_piece,
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BlamerBundle **orig_blamer_bundle) const {
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ASSERT_HOST(split_pt >0 && split_pt < word->chopped_word->NumBlobs());
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// Save a copy of the blamer bundle so we can try to reconstruct it below.
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BlamerBundle *orig_bb =
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word->blamer_bundle ? new BlamerBundle(*word->blamer_bundle) : NULL;
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WERD_RES *word2 = new WERD_RES(*word);
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// blow away the copied chopped_word, as we want to work with
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// the blobs from the input chopped_word so seam_arrays can be merged.
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TWERD *chopped = word->chopped_word;
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TWERD *chopped2 = new TWERD;
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chopped2->blobs.reserve(chopped->NumBlobs() - split_pt);
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for (int i = split_pt; i < chopped->NumBlobs(); ++i) {
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chopped2->blobs.push_back(chopped->blobs[i]);
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}
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chopped->blobs.truncate(split_pt);
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word->chopped_word = NULL;
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delete word2->chopped_word;
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word2->chopped_word = NULL;
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const UNICHARSET &unicharset = *word->uch_set;
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word->ClearResults();
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word2->ClearResults();
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word->chopped_word = chopped;
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word2->chopped_word = chopped2;
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word->SetupBasicsFromChoppedWord(unicharset);
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word2->SetupBasicsFromChoppedWord(unicharset);
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// Try to adjust the blamer bundle.
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if (orig_bb != NULL) {
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// TODO(rays) Looks like a leak to me.
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// orig_bb should take, rather than copy.
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word->blamer_bundle = new BlamerBundle();
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word2->blamer_bundle = new BlamerBundle();
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orig_bb->SplitBundle(chopped->blobs.back()->bounding_box().right(),
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word2->chopped_word->blobs[0]->bounding_box().left(),
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wordrec_debug_blamer,
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word->blamer_bundle, word2->blamer_bundle);
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}
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*right_piece = word2;
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*orig_blamer_bundle = orig_bb;
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}
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/**********************************************************************
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* join_words
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*
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* The opposite of split_word():
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* join word2 (including any recognized data / seam array / etc)
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* onto the right of word and then delete word2.
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* Also, if orig_bb is provided, stitch it back into word.
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**********************************************************************/
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void Tesseract::join_words(WERD_RES *word,
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WERD_RES *word2,
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BlamerBundle *orig_bb) const {
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TBOX prev_box = word->chopped_word->blobs.back()->bounding_box();
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TBOX blob_box = word2->chopped_word->blobs[0]->bounding_box();
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// Tack the word2 outputs onto the end of the word outputs.
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word->chopped_word->blobs += word2->chopped_word->blobs;
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word->rebuild_word->blobs += word2->rebuild_word->blobs;
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word2->chopped_word->blobs.clear();
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word2->rebuild_word->blobs.clear();
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TPOINT split_pt;
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split_pt.x = (prev_box.right() + blob_box.left()) / 2;
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split_pt.y = (prev_box.top() + prev_box.bottom() +
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blob_box.top() + blob_box.bottom()) / 4;
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// Move the word2 seams onto the end of the word1 seam_array.
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// Since the seam list is one element short, an empty seam marking the
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// end of the last blob in the first word is needed first.
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word->seam_array.push_back(new SEAM(0.0f, split_pt, NULL, NULL, NULL));
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word->seam_array += word2->seam_array;
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word2->seam_array.truncate(0);
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// Fix widths and gaps.
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word->blob_widths += word2->blob_widths;
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word->blob_gaps += word2->blob_gaps;
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// Fix the ratings matrix.
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int rat1 = word->ratings->dimension();
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int rat2 = word2->ratings->dimension();
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word->ratings->AttachOnCorner(word2->ratings);
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ASSERT_HOST(word->ratings->dimension() == rat1 + rat2);
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word->best_state += word2->best_state;
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// Append the word choices.
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*word->raw_choice += *word2->raw_choice;
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// How many alt choices from each should we try to get?
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const int kAltsPerPiece = 2;
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// When do we start throwing away extra alt choices?
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const int kTooManyAltChoices = 100;
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// Construct the cartesian product of the best_choices of word(1) and word2.
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WERD_CHOICE_LIST joined_choices;
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WERD_CHOICE_IT jc_it(&joined_choices);
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WERD_CHOICE_IT bc1_it(&word->best_choices);
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WERD_CHOICE_IT bc2_it(&word2->best_choices);
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int num_word1_choices = word->best_choices.length();
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int total_joined_choices = num_word1_choices;
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// Nota Bene: For the main loop here, we operate only on the 2nd and greater
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// word2 choices, and put them in the joined_choices list. The 1st word2
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// choice gets added to the original word1 choices in-place after we have
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// finished with them.
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int bc2_index = 1;
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for (bc2_it.forward(); !bc2_it.at_first(); bc2_it.forward(), ++bc2_index) {
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if (total_joined_choices >= kTooManyAltChoices &&
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bc2_index > kAltsPerPiece)
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break;
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int bc1_index = 0;
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for (bc1_it.move_to_first(); bc1_index < num_word1_choices;
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++bc1_index, bc1_it.forward()) {
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if (total_joined_choices >= kTooManyAltChoices &&
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bc1_index > kAltsPerPiece)
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break;
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WERD_CHOICE *wc = new WERD_CHOICE(*bc1_it.data());
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*wc += *bc2_it.data();
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jc_it.add_after_then_move(wc);
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++total_joined_choices;
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}
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}
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// Now that we've filled in as many alternates as we want, paste the best
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// choice for word2 onto the original word alt_choices.
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bc1_it.move_to_first();
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bc2_it.move_to_first();
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for (bc1_it.mark_cycle_pt(); !bc1_it.cycled_list(); bc1_it.forward()) {
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*bc1_it.data() += *bc2_it.data();
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}
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bc1_it.move_to_last();
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bc1_it.add_list_after(&joined_choices);
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// Restore the pointer to original blamer bundle and combine blamer
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// information recorded in the splits.
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if (orig_bb != NULL) {
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orig_bb->JoinBlames(*word->blamer_bundle, *word2->blamer_bundle,
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wordrec_debug_blamer);
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delete word->blamer_bundle;
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word->blamer_bundle = orig_bb;
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}
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word->SetupBoxWord();
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word->reject_map.initialise(word->box_word->length());
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delete word2;
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}
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} // namespace tesseract
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