/****************************************************************** * File: control.cpp (Formerly control.c) * Description: Module-independent matcher controller. * Author: Ray Smith * Created: Thu Apr 23 11:09:58 BST 1992 * ReHacked: Tue Sep 22 08:42:49 BST 1992 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 #include #ifdef __UNIX__ #include #include #include #endif #include #include "ocrclass.h" #include "werdit.h" #include "drawfx.h" #include "tessbox.h" #include "tessvars.h" #include "pgedit.h" #include "reject.h" #include "fixspace.h" #include "docqual.h" #include "control.h" #include "output.h" #include "callcpp.h" #include "globals.h" #include "sorthelper.h" #include "tesseractclass.h" // Include automatically generated configuration file if running autoconf. #ifdef HAVE_CONFIG_H #include "config_auto.h" #endif #define MIN_FONT_ROW_COUNT 8 #define MAX_XHEIGHT_DIFF 3 const char* const kBackUpConfigFile = "tempconfigdata.config"; // Multiple of x-height to make a repeated word have spaces in it. const double kRepcharGapThreshold = 0.5; // Min believable x-height for any text when refitting as a fraction of // original x-height const double kMinRefitXHeightFraction = 0.5; /** * recog_pseudo_word * * Make a word from the selected blobs and run Tess on them. * * @param page_res recognise blobs * @param selection_box within this box */ namespace tesseract { void Tesseract::recog_pseudo_word(PAGE_RES* page_res, TBOX &selection_box) { WERD *word; ROW *pseudo_row; // row of word BLOCK *pseudo_block; // block of word word = make_pseudo_word(page_res, selection_box, pseudo_block, pseudo_row); if (word != NULL) { WERD_RES word_res(word); recog_interactive(pseudo_block, pseudo_row, &word_res); delete word; } } /** * recog_interactive * * Recognize a single word in interactive mode. * * @param block block * @param row row of word * @param word_res word to recognise */ BOOL8 Tesseract::recog_interactive(BLOCK* block, ROW* row, WERD_RES* word_res) { inT16 char_qual; inT16 good_char_qual; WordData word_data(block, row, word_res); SetupWordPassN(2, &word_data); classify_word_and_language(&Tesseract::classify_word_pass2, &word_data); if (tessedit_debug_quality_metrics) { word_char_quality(word_res, row, &char_qual, &good_char_qual); tprintf ("\n%d chars; word_blob_quality: %d; outline_errs: %d; char_quality: %d; good_char_quality: %d\n", word_res->reject_map.length(), word_blob_quality(word_res, row), word_outline_errs(word_res), char_qual, good_char_qual); } return TRUE; } // Helper function to check for a target word and handle it appropriately. // Inspired by Jetsoft's requirement to process only single words on pass2 // and beyond. // If word_config is not null: // If the word_box and target_word_box overlap, read the word_config file // else reset to previous config data. // return true. // else // If the word_box and target_word_box overlap or pass <= 1, return true. // Note that this function uses a fixed temporary file for storing the previous // configs, so it is neither thread-safe, nor process-safe, but the assumption // is that it will only be used for one debug window at a time. // // Since this function is used for debugging (and not to change OCR results) // set only debug params from the word config file. bool Tesseract::ProcessTargetWord(const TBOX& word_box, const TBOX& target_word_box, const char* word_config, int pass) { if (word_config != NULL) { if (word_box.major_overlap(target_word_box)) { if (backup_config_file_ == NULL) { backup_config_file_ = kBackUpConfigFile; FILE* config_fp = fopen(backup_config_file_, "wb"); ParamUtils::PrintParams(config_fp, params()); fclose(config_fp); ParamUtils::ReadParamsFile(word_config, SET_PARAM_CONSTRAINT_DEBUG_ONLY, params()); } } else { if (backup_config_file_ != NULL) { ParamUtils::ReadParamsFile(backup_config_file_, SET_PARAM_CONSTRAINT_DEBUG_ONLY, params()); backup_config_file_ = NULL; } } } else if (pass > 1 && !word_box.major_overlap(target_word_box)) { return false; } return true; } // If tesseract is to be run, sets the words up ready for it. void Tesseract::SetupAllWordsPassN(int pass_n, const TBOX* target_word_box, const char* word_config, PAGE_RES* page_res, GenericVector* words) { // Prepare all the words. PAGE_RES_IT page_res_it(page_res); for (page_res_it.restart_page(); page_res_it.word() != NULL; page_res_it.forward()) { if (pass_n == 1) page_res_it.word()->SetupFake(unicharset); if (target_word_box == NULL || ProcessTargetWord(page_res_it.word()->word->bounding_box(), *target_word_box, word_config, 1)) { words->push_back(WordData(page_res_it)); } } // Setup all the words for recognition with polygonal approximation. for (int w = 0; w < words->size(); ++w) { SetupWordPassN(pass_n, &(*words)[w]); if (w > 0) (*words)[w].prev_word = &(*words)[w - 1]; } } // Sets up the single word ready for whichever engine is to be run. void Tesseract::SetupWordPassN(int pass_n, WordData* word) { if (pass_n == 1 || !word->word->done || tessedit_training_tess) { if (pass_n == 2) { // TODO(rays) Should we do this on pass1 too? word->word->caps_height = 0.0; if (word->word->x_height == 0.0f) word->word->x_height = word->row->x_height(); } // Cube doesn't get setup for pass2. if (pass_n != 2 || tessedit_ocr_engine_mode != OEM_CUBE_ONLY) { word->word->SetupForRecognition( unicharset, this, BestPix(), tessedit_ocr_engine_mode, NULL, classify_bln_numeric_mode, textord_use_cjk_fp_model, poly_allow_detailed_fx, word->row, word->block); } } if (!sub_langs_.empty()) { if (word->lang_words.size() != sub_langs_.size()) { // Setup the words for all the sub-languages now. WERD_RES empty; word->lang_words.init_to_size(sub_langs_.size(), empty); } for (int s = 0; s < sub_langs_.size(); ++s) { Tesseract* lang_t = sub_langs_[s]; if (pass_n == 1 || (lang_t->tessedit_ocr_engine_mode != OEM_CUBE_ONLY && (!word->lang_words[s].done || lang_t->tessedit_training_tess))) { word->lang_words[s].InitForRetryRecognition(*word->word); word->lang_words[s].SetupForRecognition( lang_t->unicharset, lang_t, BestPix(), lang_t->tessedit_ocr_engine_mode, NULL, lang_t->classify_bln_numeric_mode, lang_t->textord_use_cjk_fp_model, lang_t->poly_allow_detailed_fx, word->row, word->block); } } } } // Runs word recognition on all the words. bool Tesseract::RecogAllWordsPassN(int pass_n, ETEXT_DESC* monitor, GenericVector* words) { // TODO(rays) Before this loop can be parallelized (it would yield a massive // speed-up) all remaining member globals need to be converted to local/heap // (eg set_pass1 and set_pass2) and an intermediate adaption pass needs to be // added. The results will be significantly different with adaption on, and // deterioration will need investigation. for (int w = 0; w < words->size(); ++w) { WordData* word = &(*words)[w]; if (monitor != NULL) { monitor->ocr_alive = TRUE; if (pass_n == 1) monitor->progress = 30 + 50 * w / words->size(); else monitor->progress = 80 + 10 * w / words->size(); if (monitor->deadline_exceeded() || (monitor->cancel != NULL && (*monitor->cancel)(monitor->cancel_this, words->size()))) { // Timeout. Fake out the rest of the words. for (; w < words->size(); ++w) { (*words)[w].word->SetupFake(unicharset); } return false; } } if (word->word->tess_failed) continue; WordRecognizer recognizer = pass_n == 1 ? &Tesseract::classify_word_pass1 : &Tesseract::classify_word_pass2; classify_word_and_language(recognizer, word); if (tessedit_dump_choices) { word_dumper(NULL, word->row, word->word); tprintf("Pass%d: %s [%s]\n", pass_n, word->word->best_choice->unichar_string().string(), word->word->best_choice->debug_string().string()); } } return true; } /** * recog_all_words() * * Walk the page_res, recognizing all the words. * If monitor is not null, it is used as a progress monitor/timeout/cancel. * If dopasses is 0, all recognition passes are run, * 1 just pass 1, 2 passes2 and higher. * If target_word_box is not null, special things are done to words that * overlap the target_word_box: * if word_config is not null, the word config file is read for just the * target word(s), otherwise, on pass 2 and beyond ONLY the target words * are processed (Jetsoft modification.) * Returns false if we cancelled prematurely. * * @param page_res page structure * @param monitor progress monitor * @param word_config word_config file * @param target_word_box specifies just to extract a rectangle * @param dopasses 0 - all, 1 just pass 1, 2 passes 2 and higher */ bool Tesseract::recog_all_words(PAGE_RES* page_res, ETEXT_DESC* monitor, const TBOX* target_word_box, const char* word_config, int dopasses) { PAGE_RES_IT page_res_it(page_res); if (tessedit_minimal_rej_pass1) { tessedit_test_adaption.set_value (TRUE); tessedit_minimal_rejection.set_value (TRUE); } if (dopasses==0 || dopasses==1) { page_res_it.restart_page(); // ****************** Pass 1 ******************* // Clear adaptive classifier at the beginning of the page if it is full. // This is done only at the beginning of the page to ensure that the // classifier is not reset at an arbitrary point while processing the page, // which would cripple Passes 2+ if the reset happens towards the end of // Pass 1 on a page with very difficult text. // TODO(daria): preemptively clear the classifier if it is almost full. if (AdaptiveClassifierIsFull()) ResetAdaptiveClassifierInternal(); // Now check the sub-langs as well. for (int i = 0; i < sub_langs_.size(); ++i) { if (sub_langs_[i]->AdaptiveClassifierIsFull()) sub_langs_[i]->ResetAdaptiveClassifierInternal(); } // Set up all words ready for recognition, so that if parallelism is on // all the input and output classes are ready to run the classifier. GenericVector words; SetupAllWordsPassN(1, target_word_box, word_config, page_res, &words); if (tessedit_parallelize) { PrerecAllWordsPar(words); } stats_.word_count = words.size(); stats_.dict_words = 0; stats_.doc_blob_quality = 0; stats_.doc_outline_errs = 0; stats_.doc_char_quality = 0; stats_.good_char_count = 0; stats_.doc_good_char_quality = 0; most_recently_used_ = this; // Run pass 1 word recognition. if (!RecogAllWordsPassN(1, monitor, &words)) return false; // Pass 1 post-processing. while (page_res_it.word() != NULL) { if (page_res_it.word()->word->flag(W_REP_CHAR)) { fix_rep_char(&page_res_it); page_res_it.forward(); continue; } // Count dict words. if (page_res_it.word()->best_choice->permuter() == USER_DAWG_PERM) ++(stats_.dict_words); // Update misadaption log (we only need to do it on pass 1, since // adaption only happens on this pass). if (page_res_it.word()->blamer_bundle != NULL && page_res_it.word()->blamer_bundle->misadaption_debug().length() > 0) { page_res->misadaption_log.push_back( page_res_it.word()->blamer_bundle->misadaption_debug()); } page_res_it.forward(); } } if (dopasses == 1) return true; // ****************** Pass 2 ******************* if (tessedit_tess_adaption_mode != 0x0 && !tessedit_test_adaption) { page_res_it.restart_page(); GenericVector words; SetupAllWordsPassN(2, target_word_box, word_config, page_res, &words); if (tessedit_parallelize) { PrerecAllWordsPar(words); } most_recently_used_ = this; // Run pass 2 word recognition. if (!RecogAllWordsPassN(2, monitor, &words)) return false; // Pass 2 post-processing. while (page_res_it.word() != NULL) { WERD_RES* word = page_res_it.word(); if (word->word->flag(W_REP_CHAR) && !word->done) { fix_rep_char(&page_res_it); page_res_it.forward(); continue; } page_res_it.forward(); } } // The next passes can only be run if tesseract has been used, as cube // doesn't set all the necessary outputs in WERD_RES. if (tessedit_ocr_engine_mode == OEM_TESSERACT_ONLY || tessedit_ocr_engine_mode == OEM_TESSERACT_CUBE_COMBINED) { // ****************** Pass 3 ******************* // Fix fuzzy spaces. set_global_loc_code(LOC_FUZZY_SPACE); if (!tessedit_test_adaption && tessedit_fix_fuzzy_spaces && !tessedit_word_for_word && !right_to_left()) fix_fuzzy_spaces(monitor, stats_.word_count, page_res); // ****************** Pass 4 ******************* if (tessedit_enable_bigram_correction) bigram_correction_pass(page_res); // ****************** Pass 5,6 ******************* rejection_passes(page_res, monitor, target_word_box, word_config); // ****************** Pass 7 ******************* // Cube combiner. // If cube is loaded and its combiner is present, run it. if (tessedit_ocr_engine_mode == OEM_TESSERACT_CUBE_COMBINED) { run_cube_combiner(page_res); } // ****************** Pass 8 ******************* font_recognition_pass(page_res); // ****************** Pass 9 ******************* // Check the correctness of the final results. blamer_pass(page_res); } script_pos_pass(page_res); // Write results pass. set_global_loc_code(LOC_WRITE_RESULTS); // This is now redundant, but retained commented so show how to obtain // bounding boxes and style information. // changed by jetsoft // needed for dll to output memory structure if ((dopasses == 0 || dopasses == 2) && (monitor || tessedit_write_unlv)) output_pass(page_res_it, target_word_box); // end jetsoft PageSegMode pageseg_mode = static_cast( static_cast(tessedit_pageseg_mode)); textord_.CleanupSingleRowResult(pageseg_mode, page_res); if (monitor != NULL) { monitor->progress = 100; } return true; } void Tesseract::bigram_correction_pass(PAGE_RES *page_res) { PAGE_RES_IT word_it(page_res); WERD_RES *w_prev = NULL; WERD_RES *w = word_it.word(); while (1) { w_prev = w; while (word_it.forward() != NULL && (!word_it.word() || word_it.word()->part_of_combo)) { // advance word_it, skipping over parts of combos } if (!word_it.word()) break; w = word_it.word(); if (!w || !w_prev || w->uch_set != w_prev->uch_set) { continue; } if (w_prev->word->flag(W_REP_CHAR) || w->word->flag(W_REP_CHAR)) { if (tessedit_bigram_debug) { tprintf("Skipping because one of the words is W_REP_CHAR\n"); } continue; } // Two words sharing the same language model, excellent! GenericVector overrides_word1; GenericVector overrides_word2; STRING orig_w1_str = w_prev->best_choice->unichar_string(); STRING orig_w2_str = w->best_choice->unichar_string(); WERD_CHOICE prev_best(w->uch_set); { int w1start, w1end; w_prev->best_choice->GetNonSuperscriptSpan(&w1start, &w1end); prev_best = w_prev->best_choice->shallow_copy(w1start, w1end); } WERD_CHOICE this_best(w->uch_set); { int w2start, w2end; w->best_choice->GetNonSuperscriptSpan(&w2start, &w2end); this_best = w->best_choice->shallow_copy(w2start, w2end); } if (w->tesseract->getDict().valid_bigram(prev_best, this_best)) { if (tessedit_bigram_debug) { tprintf("Top choice \"%s %s\" verified by bigram model.\n", orig_w1_str.string(), orig_w2_str.string()); } continue; } if (tessedit_bigram_debug > 2) { tprintf("Examining alt choices for \"%s %s\".\n", orig_w1_str.string(), orig_w2_str.string()); } if (tessedit_bigram_debug > 1) { if (!w_prev->best_choices.singleton()) { w_prev->PrintBestChoices(); } if (!w->best_choices.singleton()) { w->PrintBestChoices(); } } float best_rating = 0.0; int best_idx = 0; WERD_CHOICE_IT prev_it(&w_prev->best_choices); for (prev_it.mark_cycle_pt(); !prev_it.cycled_list(); prev_it.forward()) { WERD_CHOICE *p1 = prev_it.data(); WERD_CHOICE strip1(w->uch_set); { int p1start, p1end; p1->GetNonSuperscriptSpan(&p1start, &p1end); strip1 = p1->shallow_copy(p1start, p1end); } WERD_CHOICE_IT w_it(&w->best_choices); for (w_it.mark_cycle_pt(); !w_it.cycled_list(); w_it.forward()) { WERD_CHOICE *p2 = w_it.data(); WERD_CHOICE strip2(w->uch_set); { int p2start, p2end; p2->GetNonSuperscriptSpan(&p2start, &p2end); strip2 = p2->shallow_copy(p2start, p2end); } if (w->tesseract->getDict().valid_bigram(strip1, strip2)) { overrides_word1.push_back(p1); overrides_word2.push_back(p2); if (overrides_word1.size() == 1 || p1->rating() + p2->rating() < best_rating) { best_rating = p1->rating() + p2->rating(); best_idx = overrides_word1.size() - 1; } } } } if (overrides_word1.size() >= 1) { // Excellent, we have some bigram matches. if (EqualIgnoringCaseAndTerminalPunct(*w_prev->best_choice, *overrides_word1[best_idx]) && EqualIgnoringCaseAndTerminalPunct(*w->best_choice, *overrides_word2[best_idx])) { if (tessedit_bigram_debug > 1) { tprintf("Top choice \"%s %s\" verified (sans case) by bigram " "model.\n", orig_w1_str.string(), orig_w2_str.string()); } continue; } STRING new_w1_str = overrides_word1[best_idx]->unichar_string(); STRING new_w2_str = overrides_word2[best_idx]->unichar_string(); if (new_w1_str != orig_w1_str) { w_prev->ReplaceBestChoice(overrides_word1[best_idx]); } if (new_w2_str != orig_w2_str) { w->ReplaceBestChoice(overrides_word2[best_idx]); } if (tessedit_bigram_debug > 0) { STRING choices_description; int num_bigram_choices = overrides_word1.size() * overrides_word2.size(); if (num_bigram_choices == 1) { choices_description = "This was the unique bigram choice."; } else { if (tessedit_bigram_debug > 1) { STRING bigrams_list; const int kMaxChoicesToPrint = 20; for (int i = 0; i < overrides_word1.size() && i < kMaxChoicesToPrint; i++) { if (i > 0) { bigrams_list += ", "; } WERD_CHOICE *p1 = overrides_word1[i]; WERD_CHOICE *p2 = overrides_word2[i]; bigrams_list += p1->unichar_string() + " " + p2->unichar_string(); if (i == kMaxChoicesToPrint) { bigrams_list += " ..."; } } choices_description = "There were many choices: {"; choices_description += bigrams_list; choices_description += "}"; } else { choices_description.add_str_int("There were ", num_bigram_choices); choices_description += " compatible bigrams."; } } tprintf("Replaced \"%s %s\" with \"%s %s\" with bigram model. %s\n", orig_w1_str.string(), orig_w2_str.string(), new_w1_str.string(), new_w2_str.string(), choices_description.string()); } } } } void Tesseract::rejection_passes(PAGE_RES* page_res, ETEXT_DESC* monitor, const TBOX* target_word_box, const char* word_config) { PAGE_RES_IT page_res_it(page_res); // ****************** Pass 5 ******************* // Gather statistics on rejects. int word_index = 0; while (!tessedit_test_adaption && page_res_it.word() != NULL) { set_global_loc_code(LOC_MM_ADAPT); WERD_RES* word = page_res_it.word(); word_index++; if (monitor != NULL) { monitor->ocr_alive = TRUE; monitor->progress = 95 + 5 * word_index / stats_.word_count; } if (word->rebuild_word == NULL) { // Word was not processed by tesseract. page_res_it.forward(); continue; } check_debug_pt(word, 70); // changed by jetsoft // specific to its needs to extract one word when need if (target_word_box && !ProcessTargetWord(word->word->bounding_box(), *target_word_box, word_config, 4)) { page_res_it.forward(); continue; } // end jetsoft page_res_it.rej_stat_word(); int chars_in_word = word->reject_map.length(); int rejects_in_word = word->reject_map.reject_count(); int blob_quality = word_blob_quality(word, page_res_it.row()->row); stats_.doc_blob_quality += blob_quality; int outline_errs = word_outline_errs(word); stats_.doc_outline_errs += outline_errs; inT16 all_char_quality; inT16 accepted_all_char_quality; word_char_quality(word, page_res_it.row()->row, &all_char_quality, &accepted_all_char_quality); stats_.doc_char_quality += all_char_quality; uinT8 permuter_type = word->best_choice->permuter(); if ((permuter_type == SYSTEM_DAWG_PERM) || (permuter_type == FREQ_DAWG_PERM) || (permuter_type == USER_DAWG_PERM)) { stats_.good_char_count += chars_in_word - rejects_in_word; stats_.doc_good_char_quality += accepted_all_char_quality; } check_debug_pt(word, 80); if (tessedit_reject_bad_qual_wds && (blob_quality == 0) && (outline_errs >= chars_in_word)) word->reject_map.rej_word_bad_quality(); check_debug_pt(word, 90); page_res_it.forward(); } if (tessedit_debug_quality_metrics) { tprintf ("QUALITY: num_chs= %d num_rejs= %d %5.3f blob_qual= %d %5.3f" " outline_errs= %d %5.3f char_qual= %d %5.3f good_ch_qual= %d %5.3f\n", page_res->char_count, page_res->rej_count, page_res->rej_count / static_cast(page_res->char_count), stats_.doc_blob_quality, stats_.doc_blob_quality / static_cast(page_res->char_count), stats_.doc_outline_errs, stats_.doc_outline_errs / static_cast(page_res->char_count), stats_.doc_char_quality, stats_.doc_char_quality / static_cast(page_res->char_count), stats_.doc_good_char_quality, (stats_.good_char_count > 0) ? (stats_.doc_good_char_quality / static_cast(stats_.good_char_count)) : 0.0); } BOOL8 good_quality_doc = ((page_res->rej_count / static_cast(page_res->char_count)) <= quality_rej_pc) && (stats_.doc_blob_quality / static_cast(page_res->char_count) >= quality_blob_pc) && (stats_.doc_outline_errs / static_cast(page_res->char_count) <= quality_outline_pc) && (stats_.doc_char_quality / static_cast(page_res->char_count) >= quality_char_pc); // ****************** Pass 6 ******************* // Do whole document or whole block rejection pass if (!tessedit_test_adaption) { set_global_loc_code(LOC_DOC_BLK_REJ); quality_based_rejection(page_res_it, good_quality_doc); } } void Tesseract::blamer_pass(PAGE_RES* page_res) { if (!wordrec_run_blamer) return; PAGE_RES_IT page_res_it(page_res); for (page_res_it.restart_page(); page_res_it.word() != NULL; page_res_it.forward()) { WERD_RES *word = page_res_it.word(); BlamerBundle::LastChanceBlame(wordrec_debug_blamer, word); page_res->blame_reasons[word->blamer_bundle->incorrect_result_reason()]++; } tprintf("Blame reasons:\n"); for (int bl = 0; bl < IRR_NUM_REASONS; ++bl) { tprintf("%s %d\n", BlamerBundle::IncorrectReasonName( static_cast(bl)), page_res->blame_reasons[bl]); } if (page_res->misadaption_log.length() > 0) { tprintf("Misadaption log:\n"); for (int i = 0; i < page_res->misadaption_log.length(); ++i) { tprintf("%s\n", page_res->misadaption_log[i].string()); } } } // Sets script positions and detects smallcaps on all output words. void Tesseract::script_pos_pass(PAGE_RES* page_res) { PAGE_RES_IT page_res_it(page_res); for (page_res_it.restart_page(); page_res_it.word() != NULL; page_res_it.forward()) { WERD_RES* word = page_res_it.word(); if (word->word->flag(W_REP_CHAR)) { page_res_it.forward(); continue; } float x_height = page_res_it.block()->block->x_height(); float word_x_height = word->x_height; if (word_x_height < word->best_choice->min_x_height() || word_x_height > word->best_choice->max_x_height()) { word_x_height = (word->best_choice->min_x_height() + word->best_choice->max_x_height()) / 2.0f; } // Test for small caps. Word capheight must be close to block xheight, // and word must contain no lower case letters, and at least one upper case. double small_cap_xheight = x_height * kXHeightCapRatio; double small_cap_delta = (x_height - small_cap_xheight) / 2.0; if (word->uch_set->script_has_xheight() && small_cap_xheight - small_cap_delta <= word_x_height && word_x_height <= small_cap_xheight + small_cap_delta) { // Scan for upper/lower. int num_upper = 0; int num_lower = 0; for (int i = 0; i < word->best_choice->length(); ++i) { if (word->uch_set->get_isupper(word->best_choice->unichar_id(i))) ++num_upper; else if (word->uch_set->get_islower(word->best_choice->unichar_id(i))) ++num_lower; } if (num_upper > 0 && num_lower == 0) word->small_caps = true; } word->SetScriptPositions(); } } // Helper returns true if the new_word is better than the word, using a // simple test of better certainty AND rating (to reduce false positives // from cube) or a dictionary vs non-dictionary word. static bool NewWordBetter(const WERD_RES& word, const WERD_RES& new_word, double rating_ratio, double certainty_margin) { if (new_word.best_choice == NULL) { return false; // New one no good. } if (word.best_choice == NULL) { return true; // Old one no good. } if (new_word.best_choice->certainty() > word.best_choice->certainty() && new_word.best_choice->rating() < word.best_choice->rating()) { return true; // New word has better confidence. } if (!Dict::valid_word_permuter(word.best_choice->permuter(), false) && Dict::valid_word_permuter(new_word.best_choice->permuter(), false) && new_word.best_choice->rating() < word.best_choice->rating() * rating_ratio && new_word.best_choice->certainty() > word.best_choice->certainty() - certainty_margin) { return true; // New word is from a dictionary. } return false; // New word is no better. } // Helper to recognize the word using the given (language-specific) tesseract. // Returns true if the result was better than previously. bool Tesseract::RetryWithLanguage(const WERD_RES& best_word, WordData* word_data, WERD_RES* word, WordRecognizer recognizer) { if (classify_debug_level || cube_debug_level) { tprintf("Retrying word using lang %s, oem %d\n", lang.string(), static_cast(tessedit_ocr_engine_mode)); } // Run the recognizer on the word. // Initial version is a bit of a hack based on better certainty and rating // (to reduce false positives from cube) or a dictionary vs non-dictionary // word. (this->*recognizer)(word_data, word); bool new_is_better = NewWordBetter(best_word, *word, classify_max_rating_ratio, classify_max_certainty_margin); if (classify_debug_level || cube_debug_level) { if (word->best_choice == NULL) { tprintf("NULL result %s better!\n", new_is_better ? "IS" : "NOT"); } else { tprintf("New result %s better:%s, r=%g, c=%g\n", new_is_better ? "IS" : "NOT", word->best_choice->unichar_string().string(), word->best_choice->rating(), word->best_choice->certainty()); } } return new_is_better; } // Generic function for classifying a word. Can be used either for pass1 or // pass2 according to the function passed to recognizer. // word block and row are the current location in the document's PAGE_RES. // Recognizes in the current language, and if successful that is all. // If recognition was not successful, tries all available languages until // it gets a successful result or runs out of languages. Keeps the best result. void Tesseract::classify_word_and_language(WordRecognizer recognizer, WordData* word_data) { // Points to the best result. May be word or in lang_words. WERD_RES* word = word_data->word; clock_t start_t = clock(); if (classify_debug_level || cube_debug_level) { tprintf("Processing word with lang %s at:", most_recently_used_->lang.string()); word->word->bounding_box().print(); } const char* result_type = "Initial"; bool initially_done = !word->tess_failed && word->done; if (initially_done) { // If done on pass1, leave it as-is. most_recently_used_ = word->tesseract; result_type = "Already done"; } else { if (most_recently_used_ != this) { // Point to the word for most_recently_used_. for (int s = 0; s < sub_langs_.size(); ++s) { if (most_recently_used_ == sub_langs_[s]) { word = &word_data->lang_words[s]; break; } } } (most_recently_used_->*recognizer)(word_data, word); if (!word->tess_failed && word->tess_accepted) result_type = "Accepted"; } if (classify_debug_level || cube_debug_level) { tprintf("%s result: %s r=%.4g, c=%.4g, accepted=%d, adaptable=%d" " xht=[%g,%g]\n", result_type, word->best_choice->unichar_string().string(), word->best_choice->rating(), word->best_choice->certainty(), word->tess_accepted, word->tess_would_adapt, word->best_choice->min_x_height(), word->best_choice->max_x_height()); } if (word->tess_failed || !word->tess_accepted) { // Try all the other languages to see if they are any better. Tesseract* previous_used = most_recently_used_; if (most_recently_used_ != this) { if (classify_debug_level) { tprintf("Retrying with main-Tesseract, lang: %s\n", lang.string()); } if (word_data->word->tesseract == this) { // This is pass1, and we are trying the main language. if (RetryWithLanguage(*word, word_data, word_data->word, recognizer)) { most_recently_used_ = this; word = word_data->word; } } else { // This is pass2, and we are trying the main language again, but it // has no word allocated to it, so we must re-initialize it. WERD_RES main_word(*word_data->word); main_word.InitForRetryRecognition(*word_data->word); main_word.SetupForRecognition(unicharset, this, BestPix(), tessedit_ocr_engine_mode, NULL, classify_bln_numeric_mode, textord_use_cjk_fp_model, poly_allow_detailed_fx, word_data->row, word_data->block); if (RetryWithLanguage(*word, word_data, &main_word, recognizer)) { most_recently_used_ = this; word_data->word->ConsumeWordResults(&main_word); word = word_data->word; } } if (!word->tess_failed && word->tess_accepted) return; // No need to look at the others. } for (int i = 0; i < sub_langs_.size(); ++i) { if (sub_langs_[i] != previous_used) { if (classify_debug_level) { tprintf("Retrying with sub-Tesseract[%d] lang: %s\n", i, sub_langs_[i]->lang.string()); } if (sub_langs_[i]->RetryWithLanguage(*word, word_data, &word_data->lang_words[i], recognizer)) { most_recently_used_ = sub_langs_[i]; word = &word_data->lang_words[i]; if (!word->tess_failed && word->tess_accepted) break; // No need to look at the others. } } } } if (word != word_data->word) { // Move the result for the best language to the main word. word_data->word->ConsumeWordResults(word); } clock_t ocr_t = clock(); if (tessedit_timing_debug) { tprintf("%s (ocr took %.2f sec)\n", word->best_choice->unichar_string().string(), static_cast(ocr_t-start_t)/CLOCKS_PER_SEC); } } /** * classify_word_pass1 * * Baseline normalize the word and pass it to Tess. */ void Tesseract::classify_word_pass1(WordData* word_data, WERD_RES* word) { ROW* row = word_data->row; BLOCK* block = word_data->block; prev_word_best_choice_ = word_data->prev_word != NULL ? word_data->prev_word->word->best_choice : NULL; // If we only intend to run cube - run it and return. if (tessedit_ocr_engine_mode == OEM_CUBE_ONLY) { cube_word_pass1(block, row, word); return; } match_word_pass_n(1, word, row, block); if (!word->tess_failed && !word->word->flag(W_REP_CHAR)) { word->tess_would_adapt = AdaptableWord(word); bool adapt_ok = word_adaptable(word, tessedit_tess_adaption_mode); if (adapt_ok) { // Send word to adaptive classifier for training. word->BestChoiceToCorrectText(); LearnWord(NULL, word); // Mark misadaptions if running blamer. if (word->blamer_bundle != NULL) { word->blamer_bundle->SetMisAdaptionDebug(word->best_choice, wordrec_debug_blamer); } } if (tessedit_enable_doc_dict && !word->IsAmbiguous()) tess_add_doc_word(word->best_choice); } } // Helper to report the result of the xheight fix. void Tesseract::ReportXhtFixResult(bool accept_new_word, float new_x_ht, WERD_RES* word, WERD_RES* new_word) { tprintf("New XHT Match:%s = %s ", word->best_choice->unichar_string().string(), word->best_choice->debug_string().string()); word->reject_map.print(debug_fp); tprintf(" -> %s = %s ", new_word->best_choice->unichar_string().string(), new_word->best_choice->debug_string().string()); new_word->reject_map.print(debug_fp); tprintf(" %s->%s %s %s\n", word->guessed_x_ht ? "GUESS" : "CERT", new_word->guessed_x_ht ? "GUESS" : "CERT", new_x_ht > 0.1 ? "STILL DOUBT" : "OK", accept_new_word ? "ACCEPTED" : ""); } // Run the x-height fix-up, based on min/max top/bottom information in // unicharset. // Returns true if the word was changed. // See the comment in fixxht.cpp for a description of the overall process. bool Tesseract::TrainedXheightFix(WERD_RES *word, BLOCK* block, ROW *row) { bool accept_new_x_ht = false; int original_misfits = CountMisfitTops(word); if (original_misfits == 0) return false; float new_x_ht = ComputeCompatibleXheight(word); if (new_x_ht >= kMinRefitXHeightFraction * word->x_height) { WERD_RES new_x_ht_word(word->word); if (word->blamer_bundle != NULL) { new_x_ht_word.blamer_bundle = new BlamerBundle(); new_x_ht_word.blamer_bundle->CopyTruth(*(word->blamer_bundle)); } new_x_ht_word.x_height = new_x_ht; new_x_ht_word.caps_height = 0.0; new_x_ht_word.SetupForRecognition( unicharset, this, BestPix(), tessedit_ocr_engine_mode, NULL, classify_bln_numeric_mode, textord_use_cjk_fp_model, poly_allow_detailed_fx, row, block); match_word_pass_n(2, &new_x_ht_word, row, block); if (!new_x_ht_word.tess_failed) { int new_misfits = CountMisfitTops(&new_x_ht_word); if (debug_x_ht_level >= 1) { tprintf("Old misfits=%d with x-height %f, new=%d with x-height %f\n", original_misfits, word->x_height, new_misfits, new_x_ht); tprintf("Old rating= %f, certainty=%f, new=%f, %f\n", word->best_choice->rating(), word->best_choice->certainty(), new_x_ht_word.best_choice->rating(), new_x_ht_word.best_choice->certainty()); } // The misfits must improve and either the rating or certainty. accept_new_x_ht = new_misfits < original_misfits && (new_x_ht_word.best_choice->certainty() > word->best_choice->certainty() || new_x_ht_word.best_choice->rating() < word->best_choice->rating()); if (debug_x_ht_level >= 1) { ReportXhtFixResult(accept_new_x_ht, new_x_ht, word, &new_x_ht_word); } } if (accept_new_x_ht) { word->ConsumeWordResults(&new_x_ht_word); return true; } } return false; } /** * classify_word_pass2 * * Control what to do with the word in pass 2 */ void Tesseract::classify_word_pass2(WordData* word_data, WERD_RES* word) { // Return if we do not want to run Tesseract. if (tessedit_ocr_engine_mode != OEM_TESSERACT_ONLY && tessedit_ocr_engine_mode != OEM_TESSERACT_CUBE_COMBINED) return; ROW* row = word_data->row; BLOCK* block = word_data->block; prev_word_best_choice_ = word_data->prev_word != NULL ? word_data->prev_word->word->best_choice : NULL; set_global_subloc_code(SUBLOC_NORM); check_debug_pt(word, 30); if (!word->done || tessedit_training_tess) { word->caps_height = 0.0; if (word->x_height == 0.0f) word->x_height = row->x_height(); match_word_pass_n(2, word, row, block); check_debug_pt(word, 40); } SubAndSuperscriptFix(word); if (!word->tess_failed && !word->word->flag(W_REP_CHAR)) { if (unicharset.top_bottom_useful() && unicharset.script_has_xheight() && block->classify_rotation().y() == 0.0f) { // Use the tops and bottoms since they are available. TrainedXheightFix(word, block, row); } set_global_subloc_code(SUBLOC_NORM); } #ifndef GRAPHICS_DISABLED if (tessedit_display_outwords) { if (fx_win == NULL) create_fx_win(); clear_fx_win(); word->rebuild_word->plot(fx_win); TBOX wbox = word->rebuild_word->bounding_box(); fx_win->ZoomToRectangle(wbox.left(), wbox.top(), wbox.right(), wbox.bottom()); ScrollView::Update(); } #endif set_global_subloc_code(SUBLOC_NORM); check_debug_pt(word, 50); } /** * match_word_pass2 * * Baseline normalize the word and pass it to Tess. */ void Tesseract::match_word_pass_n(int pass_n, WERD_RES *word, ROW *row, BLOCK* block) { if (word->tess_failed) return; tess_segment_pass_n(pass_n, word); if (!word->tess_failed) { if (!word->word->flag (W_REP_CHAR)) { word->fix_quotes(); if (tessedit_fix_hyphens) word->fix_hyphens(); /* Dont trust fix_quotes! - though I think I've fixed the bug */ if (word->best_choice->length() != word->box_word->length()) { tprintf("POST FIX_QUOTES FAIL String:\"%s\"; Strlen=%d;" " #Blobs=%d\n", word->best_choice->debug_string().string(), word->best_choice->length(), word->box_word->length()); } word->tess_accepted = tess_acceptable_word(word); // Also sets word->done flag make_reject_map(word, row, pass_n); } } set_word_fonts(word); ASSERT_HOST(word->raw_choice != NULL); } // Helper to return the best rated BLOB_CHOICE in the whole word that matches // the given char_id, or NULL if none can be found. static BLOB_CHOICE* FindBestMatchingChoice(UNICHAR_ID char_id, WERD_RES* word_res) { // Find the corresponding best BLOB_CHOICE from any position in the word_res. BLOB_CHOICE* best_choice = NULL; for (int i = 0; i < word_res->best_choice->length(); ++i) { BLOB_CHOICE* choice = FindMatchingChoice(char_id, word_res->GetBlobChoices(i)); if (choice != NULL) { if (best_choice == NULL || choice->rating() < best_choice->rating()) best_choice = choice; } } return best_choice; } // Helper to insert blob_choice in each location in the leader word if there is // no matching BLOB_CHOICE there already, and correct any incorrect results // in the best_choice. static void CorrectRepcharChoices(BLOB_CHOICE* blob_choice, WERD_RES* word_res) { WERD_CHOICE* word = word_res->best_choice; for (int i = 0; i < word_res->best_choice->length(); ++i) { BLOB_CHOICE* choice = FindMatchingChoice(blob_choice->unichar_id(), word_res->GetBlobChoices(i)); if (choice == NULL) { BLOB_CHOICE_IT choice_it(word_res->GetBlobChoices(i)); choice_it.add_before_stay_put(new BLOB_CHOICE(*blob_choice)); } } // Correct any incorrect results in word. for (int i = 0; i < word->length(); ++i) { if (word->unichar_id(i) != blob_choice->unichar_id()) word->set_unichar_id(blob_choice->unichar_id(), i); } } /** * fix_rep_char() * The word is a repeated char. (Leader.) Find the repeated char character. * Create the appropriate single-word or multi-word sequence according to * the size of spaces in between blobs, and correct the classifications * where some of the characters disagree with the majority. */ void Tesseract::fix_rep_char(PAGE_RES_IT* page_res_it) { WERD_RES *word_res = page_res_it->word(); const WERD_CHOICE &word = *(word_res->best_choice); // Find the frequency of each unique character in the word. UNICHAR_ID space = word_res->uch_set->unichar_to_id(" "); SortHelper rep_ch(word.length()); for (int i = 0; i < word.length(); ++i) { if (word.unichar_id(i) != space) rep_ch.Add(word.unichar_id(i), 1); } // Find the most frequent result. UNICHAR_ID maxch_id = INVALID_UNICHAR_ID; // most common char int max_count = rep_ch.MaxCount(&maxch_id); // Find the best exemplar of a classifier result for maxch_id. BLOB_CHOICE* best_choice = FindBestMatchingChoice(maxch_id, word_res); if (best_choice == NULL) { tprintf("Failed to find a choice for %s, occurring %d times\n", word_res->uch_set->debug_str(maxch_id).string(), max_count); return; } word_res->done = TRUE; // Measure the mean space. int total_gap = 0; int gap_count = 0; WERD* werd = word_res->word; C_BLOB_IT blob_it(werd->cblob_list()); C_BLOB* prev_blob = blob_it.data(); for (blob_it.forward(); !blob_it.at_first(); blob_it.forward()) { C_BLOB* blob = blob_it.data(); int gap = blob->bounding_box().left(); gap -= prev_blob->bounding_box().right(); total_gap += gap; ++gap_count; prev_blob = blob; } if (total_gap > word_res->x_height * gap_count * kRepcharGapThreshold) { // Needs spaces between. ExplodeRepeatedWord(best_choice, page_res_it); } else { // Just correct existing classification. CorrectRepcharChoices(best_choice, word_res); word_res->reject_map.initialise(word.length()); } } // Explode the word at the given iterator location into individual words // of a single given unichar_id defined by best_choice. // The original word is deleted, and the replacements copy most of their // fields from the original. void Tesseract::ExplodeRepeatedWord(BLOB_CHOICE* best_choice, PAGE_RES_IT* page_res_it) { WERD_RES *word_res = page_res_it->word(); ASSERT_HOST(best_choice != NULL); // Make a new word for each blob in the original. WERD* werd = word_res->word; C_BLOB_IT blob_it(werd->cblob_list()); for (; !blob_it.empty(); blob_it.forward()) { bool first_blob = blob_it.at_first(); bool last_blob = blob_it.at_last(); WERD* blob_word = werd->ConstructFromSingleBlob(first_blob, last_blob, blob_it.extract()); // Note that blamer_bundle (truth information) is not copied, which is // desirable, since the newly inserted words would not have the original // bounding box corresponding to the one recorded in truth fields. WERD_RES* rep_word = page_res_it->InsertSimpleCloneWord(*word_res, blob_word); // Setup the single char WERD_RES if (rep_word->SetupForRecognition(*word_res->uch_set, this, BestPix(), tessedit_ocr_engine_mode, NULL, false, textord_use_cjk_fp_model, poly_allow_detailed_fx, page_res_it->row()->row, page_res_it->block()->block)) { rep_word->CloneChoppedToRebuild(); BLOB_CHOICE* blob_choice = new BLOB_CHOICE(*best_choice); rep_word->FakeClassifyWord(1, &blob_choice); } } page_res_it->DeleteCurrentWord(); } ACCEPTABLE_WERD_TYPE Tesseract::acceptable_word_string( const UNICHARSET& char_set, const char *s, const char *lengths) { int i = 0; int offset = 0; int leading_punct_count; int upper_count = 0; int hyphen_pos = -1; ACCEPTABLE_WERD_TYPE word_type = AC_UNACCEPTABLE; if (strlen (lengths) > 20) return word_type; /* Single Leading punctuation char*/ if (s[offset] != '\0' && STRING(chs_leading_punct).contains(s[offset])) offset += lengths[i++]; leading_punct_count = i; /* Initial cap */ while (s[offset] != '\0' && char_set.get_isupper(s + offset, lengths[i])) { offset += lengths[i++]; upper_count++; } if (upper_count > 1) { word_type = AC_UPPER_CASE; } else { /* Lower case word, possibly with an initial cap */ while (s[offset] != '\0' && char_set.get_islower(s + offset, lengths[i])) { offset += lengths[i++]; } if (i - leading_punct_count < quality_min_initial_alphas_reqd) goto not_a_word; /* Allow a single hyphen in a lower case word - dont trust upper case - I've seen several cases of "H" -> "I-I" */ if (lengths[i] == 1 && s[offset] == '-') { hyphen_pos = i; offset += lengths[i++]; if (s[offset] != '\0') { while ((s[offset] != '\0') && char_set.get_islower(s + offset, lengths[i])) { offset += lengths[i++]; } if (i < hyphen_pos + 3) goto not_a_word; } } else { /* Allow "'s" in NON hyphenated lower case words */ if (lengths[i] == 1 && (s[offset] == '\'') && lengths[i + 1] == 1 && (s[offset + lengths[i]] == 's')) { offset += lengths[i++]; offset += lengths[i++]; } } if (upper_count > 0) word_type = AC_INITIAL_CAP; else word_type = AC_LOWER_CASE; } /* Up to two different, constrained trailing punctuation chars */ if (lengths[i] == 1 && s[offset] != '\0' && STRING(chs_trailing_punct1).contains(s[offset])) offset += lengths[i++]; if (lengths[i] == 1 && s[offset] != '\0' && i > 0 && s[offset - lengths[i - 1]] != s[offset] && STRING(chs_trailing_punct2).contains (s[offset])) offset += lengths[i++]; if (s[offset] != '\0') word_type = AC_UNACCEPTABLE; not_a_word: if (word_type == AC_UNACCEPTABLE) { /* Look for abbreviation string */ i = 0; offset = 0; if (s[0] != '\0' && char_set.get_isupper(s, lengths[0])) { word_type = AC_UC_ABBREV; while (s[offset] != '\0' && char_set.get_isupper(s + offset, lengths[i]) && lengths[i + 1] == 1 && s[offset + lengths[i]] == '.') { offset += lengths[i++]; offset += lengths[i++]; } } else if (s[0] != '\0' && char_set.get_islower(s, lengths[0])) { word_type = AC_LC_ABBREV; while (s[offset] != '\0' && char_set.get_islower(s + offset, lengths[i]) && lengths[i + 1] == 1 && s[offset + lengths[i]] == '.') { offset += lengths[i++]; offset += lengths[i++]; } } if (s[offset] != '\0') word_type = AC_UNACCEPTABLE; } return word_type; } BOOL8 Tesseract::check_debug_pt(WERD_RES *word, int location) { BOOL8 show_map_detail = FALSE; inT16 i; if (!test_pt) return FALSE; tessedit_rejection_debug.set_value (FALSE); debug_x_ht_level.set_value (0); if (word->word->bounding_box ().contains (FCOORD (test_pt_x, test_pt_y))) { if (location < 0) return TRUE; // For breakpoint use tessedit_rejection_debug.set_value (TRUE); debug_x_ht_level.set_value (20); tprintf ("\n\nTESTWD::"); switch (location) { case 0: tprintf ("classify_word_pass1 start\n"); word->word->print(); break; case 10: tprintf ("make_reject_map: initial map"); break; case 20: tprintf ("make_reject_map: after NN"); break; case 30: tprintf ("classify_word_pass2 - START"); break; case 40: tprintf ("classify_word_pass2 - Pre Xht"); break; case 50: tprintf ("classify_word_pass2 - END"); show_map_detail = TRUE; break; case 60: tprintf ("fixspace"); break; case 70: tprintf ("MM pass START"); break; case 80: tprintf ("MM pass END"); break; case 90: tprintf ("After Poor quality rejection"); break; case 100: tprintf ("unrej_good_quality_words - START"); break; case 110: tprintf ("unrej_good_quality_words - END"); break; case 120: tprintf ("Write results pass"); show_map_detail = TRUE; break; } tprintf(" \"%s\" ", word->best_choice->unichar_string().string()); word->reject_map.print (debug_fp); tprintf ("\n"); if (show_map_detail) { tprintf ("\"%s\"\n", word->best_choice->unichar_string().string()); for (i = 0; word->best_choice->unichar_string()[i] != '\0'; i++) { tprintf ("**** \"%c\" ****\n", word->best_choice->unichar_string()[i]); word->reject_map[i].full_print(debug_fp); } } tprintf ("Tess Accepted: %s\n", word->tess_accepted ? "TRUE" : "FALSE"); tprintf ("Done flag: %s\n\n", word->done ? "TRUE" : "FALSE"); return TRUE; } else { return FALSE; } } /** * find_modal_font * * Find the modal font and remove from the stats. */ static void find_modal_font( //good chars in word STATS *fonts, //font stats inT16 *font_out, //output font inT8 *font_count //output count ) { inT16 font; //font index inT32 count; //pile couat if (fonts->get_total () > 0) { font = (inT16) fonts->mode (); *font_out = font; count = fonts->pile_count (font); *font_count = count < MAX_INT8 ? count : MAX_INT8; fonts->add (font, -*font_count); } else { *font_out = -1; *font_count = 0; } } /** * set_word_fonts * * Get the fonts for the word. */ void Tesseract::set_word_fonts(WERD_RES *word) { // Don't try to set the word fonts for a cube word, as the configs // will be meaningless. if (word->chopped_word == NULL) return; ASSERT_HOST(word->best_choice != NULL); inT32 index; // char id index // character iterator BLOB_CHOICE_IT choice_it; // choice iterator int fontinfo_size = get_fontinfo_table().size(); int fontset_size = get_fontset_table().size(); if (fontinfo_size == 0 || fontset_size == 0) return; STATS fonts(0, fontinfo_size); // font counters word->italic = 0; word->bold = 0; if (!word->best_choice_fontinfo_ids.empty()) { word->best_choice_fontinfo_ids.clear(); } // Compute the modal font for the word for (index = 0; index < word->best_choice->length(); ++index) { UNICHAR_ID word_ch_id = word->best_choice->unichar_id(index); choice_it.set_to_list(word->GetBlobChoices(index)); if (tessedit_debug_fonts) { tprintf("Examining fonts in %s\n", word->best_choice->debug_string().string()); } for (choice_it.mark_cycle_pt(); !choice_it.cycled_list(); choice_it.forward()) { UNICHAR_ID blob_ch_id = choice_it.data()->unichar_id(); if (blob_ch_id == word_ch_id) { if (tessedit_debug_fonts) { tprintf("%s font %s (%d) font2 %s (%d)\n", word->uch_set->id_to_unichar(blob_ch_id), choice_it.data()->fontinfo_id() < 0 ? "unknown" : fontinfo_table_.get(choice_it.data()->fontinfo_id()).name, choice_it.data()->fontinfo_id(), choice_it.data()->fontinfo_id2() < 0 ? "unknown" : fontinfo_table_.get(choice_it.data()->fontinfo_id2()).name, choice_it.data()->fontinfo_id2()); } // 1st choice font gets 2 pts, 2nd choice 1 pt. if (choice_it.data()->fontinfo_id() >= 0) { fonts.add(choice_it.data()->fontinfo_id(), 2); } if (choice_it.data()->fontinfo_id2() >= 0) { fonts.add(choice_it.data()->fontinfo_id2(), 1); } break; } } } inT16 font_id1, font_id2; find_modal_font(&fonts, &font_id1, &word->fontinfo_id_count); find_modal_font(&fonts, &font_id2, &word->fontinfo_id2_count); word->fontinfo = font_id1 >= 0 ? &fontinfo_table_.get(font_id1) : NULL; word->fontinfo2 = font_id2 >= 0 ? &fontinfo_table_.get(font_id2) : NULL; // All the blobs get the word's best choice font. for (int i = 0; i < word->best_choice->length(); ++i) { word->best_choice_fontinfo_ids.push_back(font_id1); } if (word->fontinfo_id_count > 0) { FontInfo fi = fontinfo_table_.get(font_id1); if (tessedit_debug_fonts) { if (word->fontinfo_id2_count > 0) { tprintf("Word modal font=%s, score=%d, 2nd choice %s/%d\n", fi.name, word->fontinfo_id_count, fontinfo_table_.get(font_id2).name, word->fontinfo_id2_count); } else { tprintf("Word modal font=%s, score=%d. No 2nd choice\n", fi.name, word->fontinfo_id_count); } } // 1st choices got 2 pts, so we need to halve the score for the mode. word->italic = (fi.is_italic() ? 1 : -1) * (word->fontinfo_id_count + 1) / 2; word->bold = (fi.is_bold() ? 1 : -1) * (word->fontinfo_id_count + 1) / 2; } } /** * font_recognition_pass * * Smooth the fonts for the document. */ void Tesseract::font_recognition_pass(PAGE_RES* page_res) { PAGE_RES_IT page_res_it(page_res); WERD_RES *word; // current word STATS doc_fonts(0, font_table_size_); // font counters // Gather font id statistics. for (page_res_it.restart_page(); page_res_it.word() != NULL; page_res_it.forward()) { word = page_res_it.word(); if (word->fontinfo != NULL) { doc_fonts.add(word->fontinfo->universal_id, word->fontinfo_id_count); } if (word->fontinfo2 != NULL) { doc_fonts.add(word->fontinfo2->universal_id, word->fontinfo_id2_count); } } inT16 doc_font; // modal font inT8 doc_font_count; // modal font find_modal_font(&doc_fonts, &doc_font, &doc_font_count); if (doc_font_count == 0) return; // Get the modal font pointer. const FontInfo* modal_font = NULL; for (page_res_it.restart_page(); page_res_it.word() != NULL; page_res_it.forward()) { word = page_res_it.word(); if (word->fontinfo != NULL && word->fontinfo->universal_id == doc_font) { modal_font = word->fontinfo; break; } if (word->fontinfo2 != NULL && word->fontinfo2->universal_id == doc_font) { modal_font = word->fontinfo2; break; } } ASSERT_HOST(modal_font != NULL); // Assign modal font to weak words. for (page_res_it.restart_page(); page_res_it.word() != NULL; page_res_it.forward()) { word = page_res_it.word(); int length = word->best_choice->length(); // 1st choices got 2 pts, so we need to halve the score for the mode. int count = (word->fontinfo_id_count + 1) / 2; if (!(count == length || (length > 3 && count >= length * 3 / 4))) { word->fontinfo = modal_font; // Counts only get 1 as it came from the doc. word->fontinfo_id_count = 1; word->italic = modal_font->is_italic() ? 1 : -1; word->bold = modal_font->is_bold() ? 1 : -1; } } } } // namespace tesseract