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fdd4ffe85e
git-svn-id: https://tesseract-ocr.googlecode.com/svn/trunk@649 d0cd1f9f-072b-0410-8dd7-cf729c803f20
940 lines
40 KiB
C++
940 lines
40 KiB
C++
///////////////////////////////////////////////////////////////////////
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// File: dict.cpp
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// Description: dict class.
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// Author: Samuel Charron
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//
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// (C) Copyright 2006, Google Inc.
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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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#include <stdio.h>
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#include "dict.h"
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#include "unicodes.h"
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#ifdef _MSC_VER
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#pragma warning(disable:4244) // Conversion warnings
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#endif
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#include "tprintf.h"
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namespace tesseract {
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class Image;
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Dict::Dict(Image* image_ptr)
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: letter_is_okay_(&tesseract::Dict::def_letter_is_okay),
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probability_in_context_(&tesseract::Dict::def_probability_in_context),
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image_ptr_(image_ptr),
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STRING_INIT_MEMBER(user_words_suffix, "",
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"A list of user-provided words.",
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getImage()->getCCUtil()->params()),
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STRING_INIT_MEMBER(user_patterns_suffix, "",
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"A list of user-provided patterns.",
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getImage()->getCCUtil()->params()),
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BOOL_INIT_MEMBER(load_system_dawg, true, "Load system word dawg.",
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getImage()->getCCUtil()->params()),
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BOOL_INIT_MEMBER(load_freq_dawg, true, "Load frequent word dawg.",
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getImage()->getCCUtil()->params()),
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BOOL_INIT_MEMBER(load_unambig_dawg, true, "Load unambiguous word dawg.",
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getImage()->getCCUtil()->params()),
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BOOL_INIT_MEMBER(load_punc_dawg, true, "Load dawg with punctuation"
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" patterns.", getImage()->getCCUtil()->params()),
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BOOL_INIT_MEMBER(load_number_dawg, true, "Load dawg with number"
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" patterns.", getImage()->getCCUtil()->params()),
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BOOL_INIT_MEMBER(load_fixed_length_dawgs, true, "Load fixed length dawgs"
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" (e.g. for non-space delimited languages)",
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getImage()->getCCUtil()->params()),
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BOOL_INIT_MEMBER(load_bigram_dawg, false, "Load dawg with special word "
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"bigrams.", getImage()->getCCUtil()->params()),
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double_MEMBER(segment_penalty_dict_frequent_word, 1.0,
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"Score multiplier for word matches which have good case and"
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"are frequent in the given language (lower is better).",
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getImage()->getCCUtil()->params()),
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double_MEMBER(segment_penalty_dict_case_ok, 1.1,
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"Score multiplier for word matches that have good case "
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"(lower is better).", getImage()->getCCUtil()->params()),
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double_MEMBER(segment_penalty_dict_case_bad, 1.3125,
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"Default score multiplier for word matches, which may have "
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"case issues (lower is better).",
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getImage()->getCCUtil()->params()),
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double_MEMBER(segment_penalty_ngram_best_choice, 1.24,
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"Multipler to for the best choice from the ngram model.",
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getImage()->getCCUtil()->params()),
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double_MEMBER(segment_penalty_dict_nonword, 1.25,
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"Score multiplier for glyph fragment segmentations which "
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"do not match a dictionary word (lower is better).",
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getImage()->getCCUtil()->params()),
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double_MEMBER(segment_penalty_garbage, 1.50,
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"Score multiplier for poorly cased strings that are not in"
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" the dictionary and generally look like garbage (lower is"
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" better).", getImage()->getCCUtil()->params()),
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STRING_MEMBER(output_ambig_words_file, "",
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"Output file for ambiguities found in the dictionary",
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getImage()->getCCUtil()->params()),
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INT_MEMBER(dawg_debug_level, 0, "Set to 1 for general debug info"
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", to 2 for more details, to 3 to see all the debug messages",
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getImage()->getCCUtil()->params()),
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INT_MEMBER(hyphen_debug_level, 0, "Debug level for hyphenated words.",
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getImage()->getCCUtil()->params()),
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INT_MEMBER(max_viterbi_list_size, 10, "Maximum size of viterbi list.",
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getImage()->getCCUtil()->params()),
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BOOL_MEMBER(use_only_first_uft8_step, false,
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"Use only the first UTF8 step of the given string"
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" when computing log probabilities.",
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getImage()->getCCUtil()->params()),
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double_MEMBER(certainty_scale, 20.0, "Certainty scaling factor",
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getImage()->getCCUtil()->params()),
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double_MEMBER(stopper_nondict_certainty_base, -2.50,
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"Certainty threshold for non-dict words",
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getImage()->getCCUtil()->params()),
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double_MEMBER(stopper_phase2_certainty_rejection_offset, 1.0,
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"Reject certainty offset",
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getImage()->getCCUtil()->params()),
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INT_MEMBER(stopper_smallword_size, 2,
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"Size of dict word to be treated as non-dict word",
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getImage()->getCCUtil()->params()),
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double_MEMBER(stopper_certainty_per_char, -0.50, "Certainty to add"
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" for each dict char above small word size.",
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getImage()->getCCUtil()->params()),
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double_MEMBER(stopper_allowable_character_badness, 3.0,
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"Max certaintly variation allowed in a word (in sigma)",
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getImage()->getCCUtil()->params()),
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INT_MEMBER(stopper_debug_level, 0, "Stopper debug level",
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getImage()->getCCUtil()->params()),
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BOOL_MEMBER(stopper_no_acceptable_choices, false,
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"Make AcceptableChoice() always return false. Useful"
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" when there is a need to explore all segmentations",
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getImage()->getCCUtil()->params()),
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double_MEMBER(stopper_ambiguity_threshold_gain, 8.0,
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"Gain factor for ambiguity threshold.",
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getImage()->getCCUtil()->params()),
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double_MEMBER(stopper_ambiguity_threshold_offset, 1.5,
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"Certainty offset for ambiguity threshold.",
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getImage()->getCCUtil()->params()),
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BOOL_MEMBER(save_raw_choices, false, "Save all explored raw choices",
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getImage()->getCCUtil()->params()),
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INT_MEMBER(tessedit_truncate_wordchoice_log, 10,
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"Max words to keep in list",
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getImage()->getCCUtil()->params()),
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STRING_MEMBER(word_to_debug, "", "Word for which stopper debug"
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" information should be printed to stdout",
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getImage()->getCCUtil()->params()),
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STRING_MEMBER(word_to_debug_lengths, "",
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"Lengths of unichars in word_to_debug",
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getImage()->getCCUtil()->params()),
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INT_MEMBER(fragments_debug, 0, "Debug character fragments",
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getImage()->getCCUtil()->params()),
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INT_MEMBER(segment_debug, 0, "Debug the whole segmentation process",
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getImage()->getCCUtil()->params()),
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BOOL_MEMBER(permute_debug, 0, "Debug char permutation process",
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getImage()->getCCUtil()->params()),
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double_MEMBER(bestrate_pruning_factor, 2.0, "Multiplying factor of"
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" current best rate to prune other hypotheses",
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getImage()->getCCUtil()->params()),
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BOOL_MEMBER(permute_script_word, 0,
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"Turn on word script consistency permuter",
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getImage()->getCCUtil()->params()),
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BOOL_MEMBER(segment_segcost_rating, 0,
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"incorporate segmentation cost in word rating?",
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getImage()->getCCUtil()->params()),
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BOOL_MEMBER(segment_nonalphabetic_script, false,
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"Don't use any alphabetic-specific tricks."
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"Set to true in the traineddata config file for"
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" scripts that are cursive or inherently fixed-pitch",
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getImage()->getCCUtil()->params()),
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double_MEMBER(segment_reward_script, 0.95,
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"Score multipler for script consistency within a word. "
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"Being a 'reward' factor, it should be <= 1. "
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"Smaller value implies bigger reward.",
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getImage()->getCCUtil()->params()),
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BOOL_MEMBER(permute_fixed_length_dawg, 0,
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"Turn on fixed-length phrasebook search permuter",
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getImage()->getCCUtil()->params()),
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BOOL_MEMBER(permute_chartype_word, 0,
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"Turn on character type (property) consistency permuter",
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getImage()->getCCUtil()->params()),
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double_MEMBER(segment_reward_chartype, 0.97,
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"Score multipler for char type consistency within a word. ",
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getImage()->getCCUtil()->params()),
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double_MEMBER(segment_reward_ngram_best_choice, 0.99,
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"Score multipler for ngram permuter's best choice"
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" (only used in the Han script path).",
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getImage()->getCCUtil()->params()),
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BOOL_MEMBER(save_doc_words, 0, "Save Document Words",
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getImage()->getCCUtil()->params()),
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BOOL_MEMBER(doc_dict_enable, 1, "Enable Document Dictionary ",
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getImage()->getCCUtil()->params()),
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double_MEMBER(doc_dict_pending_threshold, 0.0,
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"Worst certainty for using pending dictionary",
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getImage()->getCCUtil()->params()),
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double_MEMBER(doc_dict_certainty_threshold, -2.25,
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"Worst certainty for words that can be inserted into the"
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"document dictionary", getImage()->getCCUtil()->params()),
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BOOL_MEMBER(ngram_permuter_activated, false,
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"Activate character-level n-gram-based permuter",
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getImage()->getCCUtil()->params()),
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INT_MEMBER(max_permuter_attempts, 10000, "Maximum number of different"
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" character choices to consider during permutation."
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" This limit is especially useful when user patterns"
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" are specified, since overly generic patterns can result in"
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" dawg search exploring an overly large number of options.",
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getImage()->getCCUtil()->params()),
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BOOL_MEMBER(permute_only_top, false, "Run only the top choice permuter",
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getImage()->getCCUtil()->params()) {
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dang_ambigs_table_ = NULL;
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replace_ambigs_table_ = NULL;
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keep_word_choices_ = false;
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reject_offset_ = 0.0;
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best_raw_choice_ = NULL;
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best_choices_ = NIL_LIST;
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raw_choices_ = NIL_LIST;
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go_deeper_fxn_ = NULL;
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hyphen_word_ = NULL;
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last_word_on_line_ = false;
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hyphen_unichar_id_ = INVALID_UNICHAR_ID;
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document_words_ = NULL;
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pending_words_ = NULL;
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bigram_dawg_ = NULL;
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freq_dawg_ = NULL;
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punc_dawg_ = NULL;
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max_fixed_length_dawgs_wdlen_ = -1;
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wordseg_rating_adjust_factor_ = -1.0f;
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output_ambig_words_file_ = NULL;
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}
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Dict::~Dict() {
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if (hyphen_word_ != NULL) delete hyphen_word_;
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if (output_ambig_words_file_ != NULL) fclose(output_ambig_words_file_);
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}
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void Dict::Load() {
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STRING name;
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STRING &lang = getImage()->getCCUtil()->lang;
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if (dawgs_.length() != 0) this->End();
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hyphen_unichar_id_ = getUnicharset().unichar_to_id(kHyphenSymbol);
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LoadEquivalenceList(kHyphenLikeUTF8);
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LoadEquivalenceList(kApostropheLikeUTF8);
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TessdataManager &tessdata_manager =
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getImage()->getCCUtil()->tessdata_manager;
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// Load dawgs_.
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if (load_punc_dawg && tessdata_manager.SeekToStart(TESSDATA_PUNC_DAWG)) {
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punc_dawg_ = new SquishedDawg(tessdata_manager.GetDataFilePtr(),
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DAWG_TYPE_PUNCTUATION, lang, PUNC_PERM,
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dawg_debug_level);
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dawgs_ += punc_dawg_;
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}
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if (load_system_dawg && tessdata_manager.SeekToStart(TESSDATA_SYSTEM_DAWG)) {
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dawgs_ += new SquishedDawg(tessdata_manager.GetDataFilePtr(),
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DAWG_TYPE_WORD, lang, SYSTEM_DAWG_PERM,
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dawg_debug_level);
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}
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if (load_number_dawg && tessdata_manager.SeekToStart(TESSDATA_NUMBER_DAWG)) {
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dawgs_ +=
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new SquishedDawg(tessdata_manager.GetDataFilePtr(),
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DAWG_TYPE_NUMBER, lang, NUMBER_PERM, dawg_debug_level);
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}
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if (load_bigram_dawg && tessdata_manager.SeekToStart(TESSDATA_BIGRAM_DAWG)) {
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bigram_dawg_ = new SquishedDawg(tessdata_manager.GetDataFilePtr(),
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DAWG_TYPE_WORD, // doesn't actually matter.
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lang,
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COMPOUND_PERM, // doesn't actually matter.
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dawg_debug_level);
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}
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if (load_freq_dawg && tessdata_manager.SeekToStart(TESSDATA_FREQ_DAWG)) {
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freq_dawg_ = new SquishedDawg(tessdata_manager.GetDataFilePtr(),
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DAWG_TYPE_WORD, lang, FREQ_DAWG_PERM,
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dawg_debug_level);
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dawgs_ += freq_dawg_;
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}
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if (load_unambig_dawg &&
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tessdata_manager.SeekToStart(TESSDATA_UNAMBIG_DAWG)) {
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unambig_dawg_ = new SquishedDawg(tessdata_manager.GetDataFilePtr(),
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DAWG_TYPE_WORD, lang, SYSTEM_DAWG_PERM,
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dawg_debug_level);
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dawgs_ += unambig_dawg_;
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}
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if (((STRING &)user_words_suffix).length() > 0) {
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Trie *trie_ptr = new Trie(DAWG_TYPE_WORD, lang, USER_DAWG_PERM,
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kMaxUserDawgEdges, getUnicharset().size(),
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dawg_debug_level);
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name = getImage()->getCCUtil()->language_data_path_prefix;
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name += user_words_suffix;
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if (!trie_ptr->read_word_list(name.string(), getUnicharset(),
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Trie::RRP_REVERSE_IF_HAS_RTL)) {
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tprintf("Error: failed to load %s\n", name.string());
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exit(1);
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}
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dawgs_ += trie_ptr;
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}
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if (((STRING &)user_patterns_suffix).length() > 0) {
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Trie *trie_ptr = new Trie(DAWG_TYPE_PATTERN, lang, USER_PATTERN_PERM,
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kMaxUserDawgEdges, getUnicharset().size(),
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dawg_debug_level);
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trie_ptr->initialize_patterns(&(getUnicharset()));
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name = getImage()->getCCUtil()->language_data_path_prefix;
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name += user_patterns_suffix;
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if (!trie_ptr->read_pattern_list(name.string(), getUnicharset())) {
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tprintf("Error: failed to load %s\n", name.string());
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exit(1);
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}
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dawgs_ += trie_ptr;
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}
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document_words_ = new Trie(DAWG_TYPE_WORD, lang, DOC_DAWG_PERM,
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kMaxDocDawgEdges, getUnicharset().size(),
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dawg_debug_level);
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dawgs_ += document_words_;
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// This dawg is temporary and should not be searched by letter_is_ok.
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pending_words_ = new Trie(DAWG_TYPE_WORD, lang, NO_PERM,
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kMaxDocDawgEdges, getUnicharset().size(),
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dawg_debug_level);
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// Load fixed length dawgs if necessary (used for phrase search
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// for non-space delimited languages).
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if (load_fixed_length_dawgs &&
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tessdata_manager.SeekToStart(TESSDATA_FIXED_LENGTH_DAWGS)) {
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ReadFixedLengthDawgs(DAWG_TYPE_WORD, lang, SYSTEM_DAWG_PERM,
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dawg_debug_level, tessdata_manager.GetDataFilePtr(),
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&dawgs_, &max_fixed_length_dawgs_wdlen_);
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}
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// Construct a list of corresponding successors for each dawg. Each entry i
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// in the successors_ vector is a vector of integers that represent the
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// indices into the dawgs_ vector of the successors for dawg i.
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successors_.reserve(dawgs_.length());
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for (int i = 0; i < dawgs_.length(); ++i) {
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const Dawg *dawg = dawgs_[i];
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SuccessorList *lst = new SuccessorList();
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for (int j = 0; j < dawgs_.length(); ++j) {
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const Dawg *other = dawgs_[j];
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if (dawg != NULL && other != NULL &&
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(dawg->lang() == other->lang()) &&
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kDawgSuccessors[dawg->type()][other->type()]) *lst += j;
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}
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successors_ += lst;
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}
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}
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void Dict::End() {
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if (dawgs_.length() == 0)
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return; // Not safe to call twice.
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dawgs_.delete_data_pointers();
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successors_.delete_data_pointers();
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dawgs_.clear();
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delete bigram_dawg_;
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successors_.clear();
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document_words_ = NULL;
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max_fixed_length_dawgs_wdlen_ = -1;
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if (pending_words_ != NULL) {
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delete pending_words_;
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pending_words_ = NULL;
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}
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}
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// Create unicharset adaptations of known, short lists of UTF-8 equivalent
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// characters (think all hyphen-like symbols). The first version of the
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// list is taken as equivalent for matching against the dictionary.
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void Dict::LoadEquivalenceList(const char *unichar_strings[]) {
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equivalent_symbols_.push_back(GenericVectorEqEq<UNICHAR_ID>());
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const UNICHARSET &unicharset = getUnicharset();
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GenericVectorEqEq<UNICHAR_ID> *equiv_list = &equivalent_symbols_.back();
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for (int i = 0; unichar_strings[i] != 0; i++) {
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UNICHAR_ID unichar_id = unicharset.unichar_to_id(unichar_strings[i]);
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if (unichar_id != INVALID_UNICHAR_ID) {
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equiv_list->push_back(unichar_id);
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}
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}
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}
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// Normalize all hyphen and apostrophes to the canonicalized one for
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// matching; pass everything else through as is.
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UNICHAR_ID Dict::NormalizeUnicharIdForMatch(UNICHAR_ID unichar_id) const {
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for (int i = 0; i < equivalent_symbols_.size(); i++) {
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if (equivalent_symbols_[i].contains(unichar_id)) {
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return equivalent_symbols_[i][0];
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}
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}
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return unichar_id;
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}
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// Returns true if in light of the current state unichar_id is allowed
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// according to at least one of the dawgs in the dawgs_ vector.
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// See more extensive comments in dict.h where this function is declared.
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int Dict::def_letter_is_okay(void* void_dawg_args,
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UNICHAR_ID unichar_id,
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bool word_end) const {
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DawgArgs *dawg_args = reinterpret_cast<DawgArgs*>(void_dawg_args);
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if (dawg_debug_level >= 3) {
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tprintf("def_letter_is_okay: current unichar=%s word_end=%d"
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" num active dawgs=%d num constraints=%d\n",
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getUnicharset().debug_str(unichar_id).string(), word_end,
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dawg_args->active_dawgs->length(),
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dawg_args->constraints->length());
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}
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// Do not accept words that contain kPatternUnicharID.
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// (otherwise pattern dawgs would not function correctly).
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// Do not accept words containing INVALID_UNICHAR_IDs.
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if (unichar_id == Dawg::kPatternUnicharID ||
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unichar_id == INVALID_UNICHAR_ID) {
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dawg_args->permuter = NO_PERM;
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return NO_PERM;
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}
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// Initialization.
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|
PermuterType curr_perm = NO_PERM;
|
|
dawg_args->updated_active_dawgs->clear();
|
|
const DawgInfoVector &constraints = *(dawg_args->constraints);
|
|
*dawg_args->updated_constraints = constraints;
|
|
|
|
// Go over the active_dawgs vector and insert DawgInfo records with the
|
|
// updated ref (an edge with the corresponding unichar id) into
|
|
// dawg_args->updated_active_dawgs.
|
|
for (int a = 0; a < dawg_args->active_dawgs->length(); ++a) {
|
|
const DawgInfo &info = (*dawg_args->active_dawgs)[a];
|
|
const Dawg *dawg = dawgs_[info.dawg_index];
|
|
// dawg_unichar_id will contain the literal unichar_id to be found in the
|
|
// dawgs (e.g. didgit pattern if unichar_id is a digit and dawg contains
|
|
// number patterns, word pattern if dawg is a puncutation dawg and we
|
|
// reached an end of beginning puntuation pattern, etc).
|
|
UNICHAR_ID dawg_unichar_id = unichar_id;
|
|
|
|
// If we are dealing with the pattern dawg, look up all the
|
|
// possible edges, not only for the exact unichar_id, but also
|
|
// for all its character classes (alpha, digit, etc).
|
|
if (dawg->type() == DAWG_TYPE_PATTERN) {
|
|
ProcessPatternEdges(dawg, info, dawg_unichar_id, word_end,
|
|
dawg_args, &curr_perm);
|
|
// There can't be any successors to dawg that is of type
|
|
// DAWG_TYPE_PATTERN, so we are done examining this DawgInfo.
|
|
continue;
|
|
}
|
|
|
|
// The number dawg generalizes all digits to be kPatternUnicharID,
|
|
// so try to match kPatternUnicharID if the current unichar is a digit.
|
|
if (dawg->type() == DAWG_TYPE_NUMBER &&
|
|
getUnicharset().get_isdigit(dawg_unichar_id)) {
|
|
dawg_unichar_id = Dawg::kPatternUnicharID;
|
|
}
|
|
|
|
// Find the edge out of the node for the dawg_unichar_id.
|
|
NODE_REF node = GetStartingNode(dawg, info.ref);
|
|
EDGE_REF edge = (node != NO_EDGE) ?
|
|
dawg->edge_char_of(node, dawg_unichar_id, word_end) : NO_EDGE;
|
|
|
|
if (dawg_debug_level >= 3) {
|
|
tprintf("Active dawg: [%d, " REFFORMAT "] edge=" REFFORMAT "\n",
|
|
info.dawg_index, node, edge);
|
|
}
|
|
|
|
if (edge != NO_EDGE) { // the unichar was found in the current dawg
|
|
if (ConstraintsOk(*(dawg_args->updated_constraints),
|
|
word_end, dawg->type())) {
|
|
if (dawg_debug_level >=3) {
|
|
tprintf("Letter found in dawg %d\n", info.dawg_index);
|
|
}
|
|
if (dawg->permuter() > curr_perm) curr_perm = dawg->permuter();
|
|
dawg_args->updated_active_dawgs->add_unique(
|
|
DawgInfo(info.dawg_index, edge), dawg_debug_level > 0,
|
|
"Append current dawg to updated active dawgs: ");
|
|
}
|
|
} else if (dawg_args->sought_word_length == kAnyWordLength) {
|
|
// The unichar was not found in the current dawg.
|
|
// Explore the successor dawgs (but only if we are not
|
|
// just searching one dawg with a fixed word length).
|
|
|
|
// Handle leading/trailing punctuation dawgs that denote a word pattern
|
|
// as an edge with kPatternUnicharID. If such an edge is found we add a
|
|
// constraint denoting the state of the dawg before the word pattern.
|
|
// This constraint will be applied later when this dawg is found among
|
|
// successor dawgs as well potentially at the end of the word.
|
|
if (dawg->type() == DAWG_TYPE_PUNCTUATION) {
|
|
edge = dawg->edge_char_of(node, Dawg::kPatternUnicharID, word_end);
|
|
if (edge != NO_EDGE) {
|
|
dawg_args->updated_constraints->add_unique(
|
|
DawgInfo(info.dawg_index, edge), dawg_debug_level > 0,
|
|
"Recording constraint: ");
|
|
} else {
|
|
// Do not explore successors of this dawg, since this
|
|
// must be invalid leading or trailing punctuation.
|
|
if (dawg_debug_level >= 3) {
|
|
tprintf("Invalid punctuation from dawg %d\n", info.dawg_index);
|
|
}
|
|
continue;
|
|
}
|
|
}
|
|
|
|
if (info.ref == NO_EDGE) {
|
|
if (dawg_debug_level >= 3) {
|
|
tprintf("No letters matched in dawg %d\n", info.dawg_index);
|
|
}
|
|
continue;
|
|
}
|
|
|
|
// Discard the dawg if the pattern can not end at previous letter.
|
|
if (edge == NO_EDGE && // previous part is not leading punctuation
|
|
!dawg->end_of_word(info.ref)) {
|
|
if (dawg_debug_level >= 3) {
|
|
tprintf("No valid pattern end in dawg %d\n", info.dawg_index);
|
|
}
|
|
continue;
|
|
}
|
|
|
|
// Look for the unichar in each of this dawg's successors
|
|
// and append those in which it is found to active_dawgs.
|
|
const SuccessorList &slist = *(successors_[info.dawg_index]);
|
|
for (int s = 0; s < slist.length(); ++s) {
|
|
int sdawg_index = slist[s];
|
|
const Dawg *sdawg = dawgs_[sdawg_index];
|
|
NODE_REF snode = 0;
|
|
// Apply constraints to the successor dawg.
|
|
for (int c = 0; c < constraints.length(); ++c) {
|
|
// If the successor dawg is described in the constraints change
|
|
// the start ref from 0 to the one recorded as the constraint.
|
|
const DawgInfo &cinfo = constraints[c];
|
|
if (cinfo.dawg_index == sdawg_index) {
|
|
snode = sdawg->next_node(cinfo.ref);
|
|
// Make sure we do not search the successor dawg if after
|
|
// applying the saved constraint we are at the end of the word.
|
|
if (snode == 0) snode = NO_EDGE;
|
|
if (dawg_debug_level >= 3) {
|
|
tprintf("Applying constraint [%d, " REFFORMAT "]\n",
|
|
sdawg_index, snode);
|
|
}
|
|
}
|
|
}
|
|
// Look for the letter in this successor dawg.
|
|
EDGE_REF sedge = sdawg->edge_char_of(snode, unichar_id, word_end);
|
|
// If we found the letter append sdawg to the active_dawgs list.
|
|
if (sedge != NO_EDGE &&
|
|
ConstraintsOk(*(dawg_args->updated_constraints), word_end,
|
|
dawgs_[sdawg_index]->type())) {
|
|
if (dawg_debug_level >= 3) {
|
|
tprintf("Letter found in the successor dawg %d\n", sdawg_index);
|
|
}
|
|
if (sdawg->permuter() > curr_perm) curr_perm = sdawg->permuter();
|
|
if (sdawg->next_node(sedge) != 0) { // if not word end
|
|
dawg_args->updated_active_dawgs->add_unique(
|
|
DawgInfo(sdawg_index, sedge), dawg_debug_level > 0,
|
|
"Append successor to updated active dawgs: ");
|
|
}
|
|
}
|
|
} // end successors loop
|
|
} // end if/else
|
|
} // end for
|
|
// Update dawg_args->permuter if it used to be NO_PERM or became NO_PERM
|
|
// or if we found the current letter in a non-punctuation dawg. This
|
|
// allows preserving information on which dawg the "core" word came from.
|
|
// Keep the old value of dawg_args->permuter if it is COMPOUND_PERM.
|
|
if (dawg_args->permuter == NO_PERM || curr_perm == NO_PERM ||
|
|
(curr_perm != PUNC_PERM && dawg_args->permuter != COMPOUND_PERM)) {
|
|
dawg_args->permuter = curr_perm;
|
|
}
|
|
return dawg_args->permuter;
|
|
}
|
|
|
|
void Dict::ProcessPatternEdges(const Dawg *dawg, const DawgInfo &info,
|
|
UNICHAR_ID unichar_id, bool word_end,
|
|
DawgArgs *dawg_args,
|
|
PermuterType *curr_perm) const {
|
|
NODE_REF node = GetStartingNode(dawg, info.ref);
|
|
// Try to find the edge corresponding to the exact unichar_id and to all the
|
|
// edges corresponding to the character class of unichar_id.
|
|
GenericVector<UNICHAR_ID> unichar_id_patterns;
|
|
unichar_id_patterns.push_back(unichar_id);
|
|
dawg->unichar_id_to_patterns(unichar_id, getUnicharset(),
|
|
&unichar_id_patterns);
|
|
for (int i = 0; i < unichar_id_patterns.size(); ++i) {
|
|
// On the first iteration check all the outgoing edges.
|
|
// On the second iteration check all self-loops.
|
|
for (int k = 0; k < 2; ++k) {
|
|
EDGE_REF edge = (k == 0) ?
|
|
dawg->edge_char_of(node, unichar_id_patterns[i], word_end)
|
|
: dawg->pattern_loop_edge(info.ref, unichar_id_patterns[i], word_end);
|
|
if (edge != NO_EDGE) {
|
|
if (dawg_debug_level >= 3) {
|
|
tprintf("Pattern dawg: [%d, " REFFORMAT "] edge=" REFFORMAT "\n",
|
|
info.dawg_index, node, edge);
|
|
}
|
|
if (ConstraintsOk(*(dawg_args->updated_constraints),
|
|
word_end, dawg->type())) {
|
|
if (dawg_debug_level >=3) {
|
|
tprintf("Letter found in pattern dawg %d\n", info.dawg_index);
|
|
}
|
|
if (dawg->permuter() > *curr_perm) *curr_perm = dawg->permuter();
|
|
dawg_args->updated_active_dawgs->add_unique(
|
|
DawgInfo(info.dawg_index, edge), dawg_debug_level > 0,
|
|
"Append current dawg to updated active dawgs: ");
|
|
}
|
|
}
|
|
}
|
|
}
|
|
}
|
|
|
|
void Dict::ReadFixedLengthDawgs(DawgType type, const STRING &lang,
|
|
PermuterType perm, int debug_level,
|
|
FILE *file, DawgVector *dawg_vec,
|
|
int *max_wdlen) {
|
|
int i;
|
|
DawgVector dawg_vec_copy;
|
|
dawg_vec_copy.move(dawg_vec); // save the input dawg_vec.
|
|
inT32 num_dawgs;
|
|
fread(&num_dawgs, sizeof(inT32), 1, file);
|
|
bool swap = (num_dawgs > MAX_WERD_LENGTH);
|
|
if (swap) num_dawgs = reverse32(num_dawgs);
|
|
inT32 word_length;
|
|
int max_word_length = 0;
|
|
// Read and record pointers to fixed-length dawgs such that:
|
|
// dawg_vec[word_length] = pointer to dawg with word length of word_length,
|
|
// NULL if such fixed-length dawg does not exist.
|
|
for (i = 0; i < num_dawgs; ++i) {
|
|
fread(&word_length, sizeof(inT32), 1, file);
|
|
if (swap) word_length = reverse32(word_length);
|
|
ASSERT_HOST(word_length > 0 && word_length <= MAX_WERD_LENGTH);
|
|
while (word_length >= dawg_vec->size()) dawg_vec->push_back(NULL);
|
|
(*dawg_vec)[word_length] =
|
|
new SquishedDawg(file, type, lang, perm, debug_level);
|
|
if (word_length > max_word_length) max_word_length = word_length;
|
|
}
|
|
*max_wdlen = max_word_length;
|
|
// Entries dawg_vec[0] to dawg_vec[max_word_length] now hold pointers
|
|
// to fixed-length dawgs. The rest of the vector will contain the dawg
|
|
// pointers from the original input dawg_vec.
|
|
for (i = 0; i < dawg_vec_copy.size(); ++i) {
|
|
dawg_vec->push_back(dawg_vec_copy[i]);
|
|
}
|
|
}
|
|
|
|
void Dict::WriteFixedLengthDawgs(
|
|
const GenericVector<SquishedDawg *> &dawg_vec,
|
|
int num_dawgs, int debug_level, FILE *output_file) {
|
|
fwrite(&num_dawgs, sizeof(inT32), 1, output_file);
|
|
if (debug_level) tprintf("Writing %d split length dawgs\n", num_dawgs);
|
|
for (int i = 1; i < dawg_vec.size(); ++i) {
|
|
if ((dawg_vec)[i] != NULL) {
|
|
fwrite(&i, sizeof(inT32), 1, output_file);
|
|
dawg_vec[i]->write_squished_dawg(output_file);
|
|
if (debug_level) tprintf("Wrote Dawg with word length %d\n", i);
|
|
}
|
|
}
|
|
}
|
|
|
|
// Fill the given active_dawgs vector with dawgs that could contain the
|
|
// beginning of the word. If hyphenated() returns true, copy the entries
|
|
// from hyphen_active_dawgs_ instead.
|
|
void Dict::init_active_dawgs(int sought_word_length,
|
|
DawgInfoVector *active_dawgs,
|
|
bool ambigs_mode) const {
|
|
int i;
|
|
if (sought_word_length != kAnyWordLength) {
|
|
// Only search one fixed word length dawg.
|
|
if (sought_word_length <= max_fixed_length_dawgs_wdlen_ &&
|
|
dawgs_[sought_word_length] != NULL) {
|
|
*active_dawgs += DawgInfo(sought_word_length, NO_EDGE);
|
|
}
|
|
} else if (hyphenated()) {
|
|
*active_dawgs = hyphen_active_dawgs_;
|
|
if (dawg_debug_level >= 3) {
|
|
for (i = 0; i < hyphen_active_dawgs_.size(); ++i) {
|
|
tprintf("Adding hyphen beginning dawg [%d, " REFFORMAT "]\n",
|
|
hyphen_active_dawgs_[i].dawg_index,
|
|
hyphen_active_dawgs_[i].ref);
|
|
}
|
|
}
|
|
} else {
|
|
for (i = 0; i < dawgs_.length(); ++i) {
|
|
if (dawgs_[i] != NULL && kBeginningDawgsType[(dawgs_[i])->type()] &&
|
|
!(ambigs_mode && (dawgs_[i])->type() == DAWG_TYPE_PATTERN)) {
|
|
*active_dawgs += DawgInfo(i, NO_EDGE);
|
|
if (dawg_debug_level >= 3) {
|
|
tprintf("Adding beginning dawg [%d, " REFFORMAT "]\n", i, NO_EDGE);
|
|
}
|
|
}
|
|
}
|
|
}
|
|
}
|
|
|
|
// If hyphenated() returns true, copy the entries from hyphen_constraints_
|
|
// into the given constraints vector.
|
|
void Dict::init_constraints(DawgInfoVector *constraints) const {
|
|
if (hyphenated()) {
|
|
*constraints = hyphen_constraints_;
|
|
if (dawg_debug_level >= 3) {
|
|
for (int i = 0; i < hyphen_constraints_.size(); ++i) {
|
|
tprintf("Adding hyphen constraint [%d, " REFFORMAT "]\n",
|
|
hyphen_constraints_[i].dawg_index,
|
|
hyphen_constraints_[i].ref);
|
|
}
|
|
}
|
|
}
|
|
}
|
|
|
|
void Dict::add_document_word(const WERD_CHOICE &best_choice) {
|
|
// Do not add hyphenated word parts to the document dawg.
|
|
// hyphen_word_ will be non-NULL after the set_hyphen_word() is
|
|
// called when the first part of the hyphenated word is
|
|
// discovered and while the second part of the word is recognized.
|
|
// hyphen_word_ is cleared in cc_recg() before the next word on
|
|
// the line is recognized.
|
|
if (hyphen_word_) return;
|
|
|
|
char filename[CHARS_PER_LINE];
|
|
FILE *doc_word_file;
|
|
int stringlen = best_choice.length();
|
|
|
|
if (!doc_dict_enable || valid_word(best_choice) ||
|
|
CurrentWordAmbig() || stringlen < 2)
|
|
return;
|
|
|
|
// Discard words that contain >= kDocDictMaxRepChars repeating unichars.
|
|
if (best_choice.length() >= kDocDictMaxRepChars) {
|
|
int num_rep_chars = 1;
|
|
UNICHAR_ID uch_id = best_choice.unichar_id(0);
|
|
for (int i = 1; i < best_choice.length(); ++i) {
|
|
if (best_choice.unichar_id(i) != uch_id) {
|
|
num_rep_chars = 1;
|
|
uch_id = best_choice.unichar_id(i);
|
|
} else {
|
|
++num_rep_chars;
|
|
if (num_rep_chars == kDocDictMaxRepChars) return;
|
|
}
|
|
}
|
|
}
|
|
|
|
if (best_choice.certainty() < doc_dict_certainty_threshold ||
|
|
stringlen == 2) {
|
|
if (best_choice.certainty() < doc_dict_pending_threshold)
|
|
return;
|
|
|
|
if (!pending_words_->word_in_dawg(best_choice)) {
|
|
if (stringlen > 2 ||
|
|
(stringlen == 2 &&
|
|
getUnicharset().get_isupper(best_choice.unichar_id(0)) &&
|
|
getUnicharset().get_isupper(best_choice.unichar_id(1)))) {
|
|
pending_words_->add_word_to_dawg(best_choice);
|
|
}
|
|
return;
|
|
}
|
|
}
|
|
|
|
if (save_doc_words) {
|
|
strcpy(filename, getImage()->getCCUtil()->imagefile.string());
|
|
strcat(filename, ".doc");
|
|
doc_word_file = open_file (filename, "a");
|
|
fprintf(doc_word_file, "%s\n",
|
|
best_choice.debug_string().string());
|
|
fclose(doc_word_file);
|
|
}
|
|
document_words_->add_word_to_dawg(best_choice);
|
|
}
|
|
|
|
void Dict::adjust_word(WERD_CHOICE *word,
|
|
float *certainty_array,
|
|
const BLOB_CHOICE_LIST_VECTOR *char_choices,
|
|
bool nonword,
|
|
float additional_adjust,
|
|
bool debug) {
|
|
bool is_han = (char_choices != NULL &&
|
|
getUnicharset().han_sid() != getUnicharset().null_sid() &&
|
|
get_top_word_script(*char_choices, getUnicharset()) ==
|
|
getUnicharset().han_sid());
|
|
bool case_is_ok = (is_han || case_ok(*word, getUnicharset()));
|
|
bool punc_is_ok = (is_han || !nonword || valid_punctuation(*word));
|
|
|
|
float adjust_factor = additional_adjust;
|
|
float new_rating = word->rating();
|
|
if (debug) {
|
|
tprintf("%sWord: %s %4.2f ", nonword ? "Non-" : "",
|
|
word->debug_string().string(), word->rating());
|
|
}
|
|
new_rating += kRatingPad;
|
|
if (nonword) { // non-dictionary word
|
|
if (case_is_ok && punc_is_ok) {
|
|
adjust_factor += segment_penalty_dict_nonword;
|
|
new_rating *= adjust_factor;
|
|
if (debug) tprintf(", W");
|
|
} else {
|
|
adjust_factor += segment_penalty_garbage;
|
|
new_rating *= adjust_factor;
|
|
if (debug) {
|
|
if (!case_is_ok) tprintf(", C");
|
|
if (!punc_is_ok) tprintf(", P");
|
|
}
|
|
}
|
|
} else { // dictionary word
|
|
if (case_is_ok) {
|
|
if (!is_han && freq_dawg_ != NULL && freq_dawg_->word_in_dawg(*word)) {
|
|
word->set_permuter(FREQ_DAWG_PERM);
|
|
adjust_factor += segment_penalty_dict_frequent_word;
|
|
new_rating *= adjust_factor;
|
|
if (debug) tprintf(", F");
|
|
} else {
|
|
adjust_factor += segment_penalty_dict_case_ok;
|
|
new_rating *= adjust_factor;
|
|
if (debug) tprintf(", ");
|
|
}
|
|
} else {
|
|
adjust_factor += segment_penalty_dict_case_bad;
|
|
new_rating *= adjust_factor;
|
|
if (debug) tprintf(", C");
|
|
}
|
|
}
|
|
new_rating -= kRatingPad;
|
|
word->set_rating(new_rating);
|
|
if (debug) tprintf(" %4.2f --> %4.2f\n", adjust_factor, new_rating);
|
|
LogNewChoice(adjust_factor, certainty_array, false, word);
|
|
}
|
|
|
|
int Dict::valid_word(const WERD_CHOICE &word, bool numbers_ok) const {
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const WERD_CHOICE *word_ptr = &word;
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WERD_CHOICE temp_word(word.unicharset());
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if (hyphenated()) {
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copy_hyphen_info(&temp_word);
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temp_word += word;
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word_ptr = &temp_word;
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}
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if (word_ptr->length() == 0) return NO_PERM;
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// Allocate vectors for holding current and updated
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// active_dawgs and constraints and initialize them.
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DawgInfoVector *active_dawgs = new DawgInfoVector[2];
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DawgInfoVector *constraints = new DawgInfoVector[2];
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init_active_dawgs(kAnyWordLength, &(active_dawgs[0]), false);
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init_constraints(&(constraints[0]));
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DawgArgs dawg_args(&(active_dawgs[0]), &(constraints[0]),
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&(active_dawgs[1]), &(constraints[1]),
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0.0, NO_PERM, kAnyWordLength, 0);
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int last_index = word_ptr->length() - 1;
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// Call leter_is_okay for each letter in the word.
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for (int i = hyphen_base_size(); i <= last_index; ++i) {
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if (!((this->*letter_is_okay_)(&dawg_args, word_ptr->unichar_id(i),
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i == last_index))) break;
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// Swap active_dawgs, constraints with the corresponding updated vector.
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if (dawg_args.updated_active_dawgs == &(active_dawgs[1])) {
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dawg_args.updated_active_dawgs = &(active_dawgs[0]);
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dawg_args.updated_constraints = &(constraints[0]);
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++(dawg_args.active_dawgs);
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++(dawg_args.constraints);
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} else {
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++(dawg_args.updated_active_dawgs);
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++(dawg_args.updated_constraints);
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dawg_args.active_dawgs = &(active_dawgs[0]);
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dawg_args.constraints = &(constraints[0]);
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}
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|
}
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delete[] active_dawgs;
|
|
delete[] constraints;
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return valid_word_permuter(dawg_args.permuter, numbers_ok) ?
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dawg_args.permuter : NO_PERM;
|
|
}
|
|
|
|
bool Dict::valid_bigram(const WERD_CHOICE &word1,
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const WERD_CHOICE &word2) const {
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|
if (bigram_dawg_ == NULL) return false;
|
|
|
|
// Extract the core word from the middle of each word with any digits
|
|
// replaced with question marks.
|
|
int w1start, w1end, w2start, w2end;
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|
word1.punct_stripped(&w1start, &w1end);
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|
word2.punct_stripped(&w2start, &w2end);
|
|
|
|
// We don't want to penalize a single guillemet, hyphen, etc.
|
|
// But our bigram list doesn't have any information about punctuation.
|
|
if (w1start >= w1end) return word1.length() < 3;
|
|
if (w2start >= w2end) return word2.length() < 3;
|
|
|
|
const UNICHARSET& uchset = getUnicharset();
|
|
STRING bigram_string;
|
|
for (int i = w1start; i < w1end; i++) {
|
|
UNICHAR_ID ch = NormalizeUnicharIdForMatch(word1.unichar_id(i));
|
|
bigram_string += uchset.get_isdigit(ch) ? "?" : uchset.id_to_unichar(ch);
|
|
}
|
|
bigram_string += " ";
|
|
for (int i = w2start; i < w2end; i++) {
|
|
UNICHAR_ID ch = NormalizeUnicharIdForMatch(word2.unichar_id(i));
|
|
bigram_string += uchset.get_isdigit(ch) ? "?" : uchset.id_to_unichar(ch);
|
|
}
|
|
WERD_CHOICE normalized_word(bigram_string.string(), uchset);
|
|
return bigram_dawg_->word_in_dawg(normalized_word);
|
|
}
|
|
|
|
bool Dict::valid_punctuation(const WERD_CHOICE &word) {
|
|
if (word.length() == 0) return NO_PERM;
|
|
int i;
|
|
WERD_CHOICE new_word(word.unicharset());
|
|
int last_index = word.length() - 1;
|
|
int new_len = 0;
|
|
for (i = 0; i <= last_index; ++i) {
|
|
UNICHAR_ID unichar_id = (word.unichar_id(i));
|
|
if (getUnicharset().get_ispunctuation(unichar_id)) {
|
|
new_word.append_unichar_id(unichar_id, 1, 0.0, 0.0);
|
|
} else if (!getUnicharset().get_isalpha(unichar_id) &&
|
|
!getUnicharset().get_isdigit(unichar_id)) {
|
|
return false; // neither punc, nor alpha, nor digit
|
|
} else if ((new_len = new_word.length()) == 0 ||
|
|
new_word.unichar_id(new_len-1) != Dawg::kPatternUnicharID) {
|
|
new_word.append_unichar_id(Dawg::kPatternUnicharID, 1, 0.0, 0.0);
|
|
}
|
|
}
|
|
for (i = 0; i < dawgs_.size(); ++i) {
|
|
if (dawgs_[i] != NULL &&
|
|
dawgs_[i]->type() == DAWG_TYPE_PUNCTUATION &&
|
|
dawgs_[i]->word_in_dawg(new_word)) return true;
|
|
}
|
|
return false;
|
|
}
|
|
|
|
// Returns the "dominant" script ID for the word. By "dominant", the script
|
|
// must account for at least half the characters. Otherwise, it returns 0.
|
|
// Note that for Japanese, Hiragana and Katakana are simply treated as Han.
|
|
int Dict::get_top_word_script(const BLOB_CHOICE_LIST_VECTOR &char_choices,
|
|
const UNICHARSET &unicharset) {
|
|
int max_script = unicharset.get_script_table_size();
|
|
int *sid = new int[max_script];
|
|
int x;
|
|
for (x = 0; x < max_script; x++) sid[x] = 0;
|
|
for (x = 0; x < char_choices.length(); ++x) {
|
|
BLOB_CHOICE_IT blob_choice_it(char_choices.get(x));
|
|
sid[blob_choice_it.data()->script_id()]++;
|
|
}
|
|
if (unicharset.han_sid() != unicharset.null_sid()) {
|
|
// Add the Hiragana & Katakana counts to Han and zero them out.
|
|
if (unicharset.hiragana_sid() != unicharset.null_sid()) {
|
|
sid[unicharset.han_sid()] += sid[unicharset.hiragana_sid()];
|
|
sid[unicharset.hiragana_sid()] = 0;
|
|
}
|
|
if (unicharset.katakana_sid() != unicharset.null_sid()) {
|
|
sid[unicharset.han_sid()] += sid[unicharset.katakana_sid()];
|
|
sid[unicharset.katakana_sid()] = 0;
|
|
}
|
|
}
|
|
// Note that high script ID overrides lower one on a tie, thus biasing
|
|
// towards non-Common script (if sorted that way in unicharset file).
|
|
int max_sid = 0;
|
|
for (x = 1; x < max_script; x++)
|
|
if (sid[x] >= sid[max_sid]) max_sid = x;
|
|
if (sid[max_sid] < char_choices.length() / 2)
|
|
max_sid = unicharset.null_sid();
|
|
delete[] sid;
|
|
return max_sid;
|
|
}
|
|
|
|
} // namespace tesseract
|