tesseract/dict/dict.h

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///////////////////////////////////////////////////////////////////////
// File: dict.h
// Description: dict class.
// Author: Samuel Charron
//
// (C) Copyright 2006, Google Inc.
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
// http://www.apache.org/licenses/LICENSE-2.0
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.
//
///////////////////////////////////////////////////////////////////////
#ifndef TESSERACT_DICT_DICT_H_
#define TESSERACT_DICT_DICT_H_
#include "ambigs.h"
#include "dawg.h"
#include "dawg_cache.h"
#include "host.h"
#include "ratngs.h"
#include "stopper.h"
#include "trie.h"
#include "unicharset.h"
#include "params_training_featdef.h"
class MATRIX;
class WERD_RES;
#define MAX_WERD_LENGTH (inT64) 128
#define NO_RATING -1
/** Struct used to hold temporary information about fragments. */
struct CHAR_FRAGMENT_INFO {
UNICHAR_ID unichar_id;
const CHAR_FRAGMENT *fragment;
int num_fragments;
float rating;
float certainty;
};
namespace tesseract {
typedef GenericVector<Dawg *> DawgVector;
//
// Constants
//
static const int kRatingPad = 4;
static const char kDictWildcard[] = "\u2606"; // WHITE STAR
static const int kDictMaxWildcards = 2; // max wildcards for a word
// TODO(daria): If hyphens are different in different languages and can be
// inferred from training data we should load their values dynamically.
static const char kHyphenSymbol[] = "-";
static const char kSlashSymbol[] = "/";
static const char kQuestionSymbol[] = "?";
static const char kApostropheSymbol[] = "'";
static const float kSimCertaintyScale = -10.0; // similarity matcher scaling
static const float kSimCertaintyOffset = -10.0; // similarity matcher offset
static const float kSimilarityFloor = 100.0; // worst E*L product to stop on
static const int kDocDictMaxRepChars = 4;
// Enum for describing whether the x-height for the word is consistent:
// 0 - everything is good.
// 1 - there are one or two secondary (but consistent) baselines
// [think subscript and superscript], or there is an oversized
// first character.
// 2 - the word is inconsistent.
enum XHeightConsistencyEnum {XH_GOOD, XH_SUBNORMAL, XH_INCONSISTENT};
struct DawgArgs {
DawgArgs(DawgPositionVector *d, DawgPositionVector *up, PermuterType p)
: active_dawgs(d), updated_dawgs(up), permuter(p), valid_end(false) {}
DawgPositionVector *active_dawgs;
DawgPositionVector *updated_dawgs;
PermuterType permuter;
// True if the current position is a valid word end.
bool valid_end;
};
class Dict {
public:
Dict(CCUtil* image_ptr);
~Dict();
const CCUtil* getCCUtil() const {
return ccutil_;
}
CCUtil* getCCUtil() {
return ccutil_;
}
const UNICHARSET& getUnicharset() const {
return getCCUtil()->unicharset;
}
UNICHARSET& getUnicharset() {
return getCCUtil()->unicharset;
}
const UnicharAmbigs &getUnicharAmbigs() const {
return getCCUtil()->unichar_ambigs;
}
// Returns true if unichar_id is a word compounding character like - or /.
inline bool compound_marker(UNICHAR_ID unichar_id) {
const GenericVector<UNICHAR_ID>& normed_ids =
getUnicharset().normed_ids(unichar_id);
return normed_ids.size() == 1 &&
(normed_ids[0] == hyphen_unichar_id_ ||
normed_ids[0] == slash_unichar_id_);
}
// Returns true if unichar_id is an apostrophe-like character that may
// separate prefix/suffix words from a main body word.
inline bool is_apostrophe(UNICHAR_ID unichar_id) {
const GenericVector<UNICHAR_ID>& normed_ids =
getUnicharset().normed_ids(unichar_id);
return normed_ids.size() == 1 && normed_ids[0] == apostrophe_unichar_id_;
}
/* hyphen.cpp ************************************************************/
/// Returns true if we've recorded the beginning of a hyphenated word.
inline bool hyphenated() const { return
!last_word_on_line_ && hyphen_word_;
}
/// Size of the base word (the part on the line before) of a hyphenated word.
inline int hyphen_base_size() const {
return this->hyphenated() ? hyphen_word_->length() : 0;
}
/// If this word is hyphenated copy the base word (the part on
/// the line before) of a hyphenated word into the given word.
/// This function assumes that word is not NULL.
inline void copy_hyphen_info(WERD_CHOICE *word) const {
if (this->hyphenated()) {
*word = *hyphen_word_;
if (hyphen_debug_level) word->print("copy_hyphen_info: ");
}
}
/// Check whether the word has a hyphen at the end.
inline bool has_hyphen_end(UNICHAR_ID unichar_id, bool first_pos) const {
if (!last_word_on_line_ || first_pos)
return false;
const GenericVector<UNICHAR_ID>& normed_ids =
getUnicharset().normed_ids(unichar_id);
return normed_ids.size() == 1 && normed_ids[0] == hyphen_unichar_id_;
}
/// Same as above, but check the unichar at the end of the word.
inline bool has_hyphen_end(const WERD_CHOICE &word) const {
int word_index = word.length() - 1;
return has_hyphen_end(word.unichar_id(word_index), word_index == 0);
}
/// Unless the previous word was the last one on the line, and the current
/// one is not (thus it is the first one on the line), erase hyphen_word_,
/// clear hyphen_active_dawgs_, update last_word_on_line_.
void reset_hyphen_vars(bool last_word_on_line);
/// Update hyphen_word_, and copy the given DawgPositionVectors into
/// hyphen_active_dawgs_ .
void set_hyphen_word(const WERD_CHOICE &word,
const DawgPositionVector &active_dawgs);
/* permdawg.cpp ************************************************************/
// Note: Functions in permdawg.cpp are only used by NoDangerousAmbig().
// When this function is refactored, permdawg.cpp can be removed.
/// Copies word into best_choice if its rating is smaller
/// than that of best_choice.
inline void update_best_choice(const WERD_CHOICE &word,
WERD_CHOICE *best_choice) {
if (word.rating() < best_choice->rating()) {
*best_choice = word;
}
}
/// 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 init_active_dawgs(DawgPositionVector *active_dawgs,
bool ambigs_mode) const;
// Fill the given vector with the default collection of any-length dawgs
void default_dawgs(DawgPositionVector *anylength_dawgs,
bool suppress_patterns) const;
/// Recursively explore all the possible character combinations in
/// the given char_choices. Use go_deeper_dawg_fxn() to explore all the
/// dawgs in the dawgs_ vector in parallel and discard invalid words.
///
/// Allocate and return a WERD_CHOICE with the best valid word found.
WERD_CHOICE *dawg_permute_and_select(
const BLOB_CHOICE_LIST_VECTOR &char_choices, float rating_limit);
/// If the choice being composed so far could be a dictionary word
/// and we have not reached the end of the word keep exploring the
/// char_choices further.
void go_deeper_dawg_fxn(
const char *debug, const BLOB_CHOICE_LIST_VECTOR &char_choices,
int char_choice_index, const CHAR_FRAGMENT_INFO *prev_char_frag_info,
bool word_ending, WERD_CHOICE *word, float certainties[],
float *limit, WERD_CHOICE *best_choice, int *attempts_left,
void *void_more_args);
/// Pointer to go_deeper function.
void (Dict::*go_deeper_fxn_)(const char *debug,
const BLOB_CHOICE_LIST_VECTOR &char_choices,
int char_choice_index,
const CHAR_FRAGMENT_INFO *prev_char_frag_info,
bool word_ending, WERD_CHOICE *word,
float certainties[], float *limit,
WERD_CHOICE *best_choice, int *attempts_left,
void *void_more_args);
//
// Helper functions for dawg_permute_and_select().
//
void permute_choices(
const char *debug,
const BLOB_CHOICE_LIST_VECTOR &char_choices,
int char_choice_index,
const CHAR_FRAGMENT_INFO *prev_char_frag_info,
WERD_CHOICE *word,
float certainties[],
float *limit,
WERD_CHOICE *best_choice,
int *attempts_left,
void *more_args);
void append_choices(
const char *debug,
const BLOB_CHOICE_LIST_VECTOR &char_choices,
const BLOB_CHOICE &blob_choice,
int char_choice_index,
const CHAR_FRAGMENT_INFO *prev_char_frag_info,
WERD_CHOICE *word,
float certainties[],
float *limit,
WERD_CHOICE *best_choice,
int *attempts_left,
void *more_args);
bool fragment_state_okay(UNICHAR_ID curr_unichar_id,
float curr_rating, float curr_certainty,
const CHAR_FRAGMENT_INFO *prev_char_frag_info,
const char *debug, int word_ending,
CHAR_FRAGMENT_INFO *char_frag_info);
/* stopper.cpp *************************************************************/
bool NoDangerousAmbig(WERD_CHOICE *BestChoice,
DANGERR *fixpt,
bool fix_replaceable,
MATRIX* ratings);
// Replaces the corresponding wrong ngram in werd_choice with the correct
// one. The whole correct n-gram is inserted into the ratings matrix and
// the werd_choice: no more fragments!. Rating and certainty of new entries
// in matrix and werd_choice are the sum and mean of the wrong ngram
// respectively.
// E.g. for werd_choice mystring'' and ambiguity ''->": werd_choice becomes
// mystring", with a new entry in the ratings matrix for ".
void ReplaceAmbig(int wrong_ngram_begin_index, int wrong_ngram_size,
UNICHAR_ID correct_ngram_id, WERD_CHOICE *werd_choice,
MATRIX *ratings);
/// Returns the length of the shortest alpha run in WordChoice.
int LengthOfShortestAlphaRun(const WERD_CHOICE &WordChoice) const;
/// Returns true if the certainty of the BestChoice word is within a
/// reasonable range of the average certainties for the best choices for
/// each character in the segmentation. This test is used to catch words
/// in which one character is much worse than the other characters in the
/// word (i.e. false will be returned in that case). The algorithm computes
/// the mean and std deviation of the certainties in the word with the worst
/// certainty thrown out.
int UniformCertainties(const WERD_CHOICE& word);
/// Returns true if the given best_choice is good enough to stop.
bool AcceptableChoice(const WERD_CHOICE& best_choice,
XHeightConsistencyEnum xheight_consistency);
/// Returns false if the best choice for the current word is questionable
/// and should be tried again on the second pass or should be flagged to
/// the user.
bool AcceptableResult(WERD_RES *word) const;
void EndDangerousAmbigs();
/// Prints the current choices for this word to stdout.
void DebugWordChoices();
/// Sets up stopper variables in preparation for the first pass.
void SettupStopperPass1();
/// Sets up stopper variables in preparation for the second pass.
void SettupStopperPass2();
/* context.cpp *************************************************************/
/// Check a string to see if it matches a set of lexical rules.
int case_ok(const WERD_CHOICE &word, const UNICHARSET &unicharset) const;
/// Returns true if the word looks like an absolute garbage
/// (e.g. image mistakenly recognized as text).
bool absolute_garbage(const WERD_CHOICE &word, const UNICHARSET &unicharset);
/* dict.cpp ****************************************************************/
/// Initialize Dict class - load dawgs from [lang].traineddata and
/// user-specified wordlist and parttern list.
static DawgCache *GlobalDawgCache();
// Sets up ready for a Load or LoadLSTM.
void SetupForLoad(DawgCache *dawg_cache);
// Loads the dawgs needed by Tesseract. Call FinishLoad() after.
void Load(const STRING &lang, TessdataManager *data_file);
// Loads the dawgs needed by the LSTM model. Call FinishLoad() after.
void LoadLSTM(const STRING &lang, TessdataManager *data_file);
// Completes the loading process after Load() and/or LoadLSTM().
// Returns false if no dictionaries were loaded.
bool FinishLoad();
void End();
// Resets the document dictionary analogous to ResetAdaptiveClassifier.
void ResetDocumentDictionary() {
if (pending_words_ != NULL)
pending_words_->clear();
if (document_words_ != NULL)
document_words_->clear();
}
/**
* Returns the maximal permuter code (from ccstruct/ratngs.h) if in light
* of the current state the letter at word_index in the given word
* is allowed according to at least one of the dawgs in dawgs_,
* otherwise returns NO_PERM.
*
* The state is described by void_dawg_args, which are interpreted as
* DawgArgs and contain relevant active dawg positions.
* Each entry in the active_dawgs vector contains an index
* into the dawgs_ vector and an EDGE_REF that indicates the last edge
* followed in the dawg. It also may contain a position in the punctuation
* dawg which describes surrounding punctuation (see struct DawgPosition).
*
* Input:
* At word_index 0 dawg_args->active_dawgs should contain an entry for each
* dawg that may start at the beginning of a word, with punc_ref and edge_ref
* initialized to NO_EDGE. Since the punctuation dawg includes the empty
* pattern " " (meaning anything without surrounding punctuation), having a
* single entry for the punctuation dawg will cover all dawgs reachable
* therefrom -- that includes all number and word dawgs. The only dawg
* non-reachable from the punctuation_dawg is the pattern dawg.
* If hyphen state needs to be applied, initial dawg_args->active_dawgs can
* be copied from the saved hyphen state (maintained by Dict).
* For word_index > 0 the corresponding state (active_dawgs and punc position)
* can be obtained from dawg_args->updated_dawgs passed to
* def_letter_is_okay for word_index-1.
* Note: the function assumes that active_dawgs, nd updated_dawgs
* member variables of dawg_args are not NULL.
*
* Output:
* The function fills in dawg_args->updated_dawgs vector with the
* entries for dawgs that contain the word up to the letter at word_index.
*
*/
//
int def_letter_is_okay(void* void_dawg_args,
UNICHAR_ID unichar_id, bool word_end) const;
int (Dict::*letter_is_okay_)(void* void_dawg_args,
UNICHAR_ID unichar_id, bool word_end) const;
/// Calls letter_is_okay_ member function.
int LetterIsOkay(void* void_dawg_args,
UNICHAR_ID unichar_id, bool word_end) const {
return (this->*letter_is_okay_)(void_dawg_args, unichar_id, word_end);
}
/// Probability in context function used by the ngram permuter.
double (Dict::*probability_in_context_)(const char* lang,
const char* context,
int context_bytes,
const char* character,
int character_bytes);
/// Calls probability_in_context_ member function.
double ProbabilityInContext(const char* context,
int context_bytes,
const char* character,
int character_bytes) {
return (this->*probability_in_context_)(
getCCUtil()->lang.string(),
context, context_bytes,
character, character_bytes);
}
/// Default (no-op) implementation of probability in context function.
double def_probability_in_context(
const char* lang, const char* context, int context_bytes,
const char* character, int character_bytes) {
(void)lang;
(void)context;
(void)context_bytes;
(void)character;
(void)character_bytes;
return 0.0;
}
double ngram_probability_in_context(const char* lang,
const char* context,
int context_bytes,
const char* character,
int character_bytes);
// Interface with params model.
float (Dict::*params_model_classify_)(const char *lang, void *path);
float ParamsModelClassify(const char *lang, void *path);
// Call params_model_classify_ member function.
float CallParamsModelClassify(void *path) {
ASSERT_HOST(params_model_classify_ != NULL); // ASSERT_HOST -> assert
return (this->*params_model_classify_)(
getCCUtil()->lang.string(), path);
}
inline void SetWildcardID(UNICHAR_ID id) { wildcard_unichar_id_ = id; }
inline UNICHAR_ID WildcardID() const { return wildcard_unichar_id_; }
/// Return the number of dawgs in the dawgs_ vector.
inline int NumDawgs() const { return dawgs_.size(); }
/// Return i-th dawg pointer recorded in the dawgs_ vector.
inline const Dawg *GetDawg(int index) const { return dawgs_[index]; }
/// Return the points to the punctuation dawg.
inline const Dawg *GetPuncDawg() const { return punc_dawg_; }
/// Return the points to the unambiguous words dawg.
inline const Dawg *GetUnambigDawg() const { return unambig_dawg_; }
/// Returns the appropriate next node given the EDGE_REF.
static inline NODE_REF GetStartingNode(const Dawg *dawg, EDGE_REF edge_ref) {
if (edge_ref == NO_EDGE) return 0; // beginning to explore the dawg
NODE_REF node = dawg->next_node(edge_ref);
if (node == 0) node = NO_EDGE; // end of word
return node;
}
// Given a unichar from a string and a given dawg, return the unichar
// we should use to match in that dawg type. (for example, in the number
// dawg, all numbers are transformed to kPatternUnicharId).
inline UNICHAR_ID char_for_dawg(UNICHAR_ID ch, const Dawg *dawg) const {
if (!dawg) return ch;
switch (dawg->type()) {
case DAWG_TYPE_NUMBER:
return getUnicharset().get_isdigit(ch) ? Dawg::kPatternUnicharID : ch;
default:
return ch;
}
}
/// For each of the character classes of the given unichar_id (and the
/// unichar_id itself) finds the corresponding outgoing node or self-loop
/// in the given dawg and (after checking that it is valid) records it in
/// dawg_args->updated_ative_dawgs. Updates current_permuter if any valid
/// edges were found.
void ProcessPatternEdges(const Dawg *dawg, const DawgPosition &info,
UNICHAR_ID unichar_id, bool word_end,
DawgArgs *dawg_args,
PermuterType *current_permuter) const;
/// Read/Write/Access special purpose dawgs which contain words
/// only of a certain length (used for phrase search for
/// non-space-delimited languages).
/// Check all the DAWGs to see if this word is in any of them.
inline static bool valid_word_permuter(uinT8 perm, bool numbers_ok) {
return (perm == SYSTEM_DAWG_PERM || perm == FREQ_DAWG_PERM ||
perm == DOC_DAWG_PERM || perm == USER_DAWG_PERM ||
perm == USER_PATTERN_PERM || perm == COMPOUND_PERM ||
(numbers_ok && perm == NUMBER_PERM));
}
int valid_word(const WERD_CHOICE &word, bool numbers_ok) const;
int valid_word(const WERD_CHOICE &word) const {
return valid_word(word, false); // return NO_PERM for words with digits
}
int valid_word_or_number(const WERD_CHOICE &word) const {
return valid_word(word, true); // return NUMBER_PERM for valid numbers
}
/// This function is used by api/tesseract_cube_combiner.cpp
int valid_word(const char *string) const {
WERD_CHOICE word(string, getUnicharset());
return valid_word(word);
}
// Do the two WERD_CHOICEs form a meaningful bigram?
bool valid_bigram(const WERD_CHOICE &word1, const WERD_CHOICE &word2) const;
/// Returns true if the word contains a valid punctuation pattern.
/// Note: Since the domains of punctuation symbols and symblos
/// used in numbers are not disjoint, a valid number might contain
/// an invalid punctuation pattern (e.g. .99).
bool valid_punctuation(const WERD_CHOICE &word);
/// Returns true if a good answer is found for the unknown blob rating.
int good_choice(const WERD_CHOICE &choice);
/// Adds a word found on this document to the document specific dictionary.
void add_document_word(const WERD_CHOICE &best_choice);
/// Adjusts the rating of the given word.
void adjust_word(WERD_CHOICE *word,
bool nonword, XHeightConsistencyEnum xheight_consistency,
float additional_adjust,
bool modify_rating,
bool debug);
/// Set wordseg_rating_adjust_factor_ to the given value.
inline void SetWordsegRatingAdjustFactor(float f) {
wordseg_rating_adjust_factor_ = f;
}
/// Returns true if the language is space-delimited (not CJ, or T).
bool IsSpaceDelimitedLang() const;
private:
/** Private member variables. */
CCUtil* ccutil_;
/**
* Table that stores ambiguities computed during training
* (loaded when NoDangerousAmbigs() is called for the first time).
* Each entry i in the table stores a set of amibiguities whose
* wrong ngram starts with unichar id i.
*/
UnicharAmbigs *dang_ambigs_table_;
/** Same as above, but for ambiguities with replace flag set. */
UnicharAmbigs *replace_ambigs_table_;
/** Additional certainty padding allowed before a word is rejected. */
FLOAT32 reject_offset_;
// Cached UNICHAR_IDs:
UNICHAR_ID wildcard_unichar_id_; // kDictWildcard.
UNICHAR_ID apostrophe_unichar_id_; // kApostropheSymbol.
UNICHAR_ID question_unichar_id_; // kQuestionSymbol.
UNICHAR_ID slash_unichar_id_; // kSlashSymbol.
UNICHAR_ID hyphen_unichar_id_; // kHyphenSymbol.
// Hyphen-related variables.
WERD_CHOICE *hyphen_word_;
DawgPositionVector hyphen_active_dawgs_;
bool last_word_on_line_;
// List of lists of "equivalent" UNICHAR_IDs for the purposes of dictionary
// matching. The first member of each list is taken as canonical. For
// example, the first list contains hyphens and dashes with the first symbol
// being the ASCII hyphen minus.
GenericVector<GenericVectorEqEq<UNICHAR_ID> > equivalent_symbols_;
// Dawg Cache reference - this is who we ask to allocate/deallocate dawgs.
DawgCache *dawg_cache_;
bool dawg_cache_is_ours_; // we should delete our own dawg_cache_
// Dawgs.
DawgVector dawgs_;
SuccessorListsVector successors_;
Trie *pending_words_;
/// The following pointers are only cached for convenience.
/// The dawgs will be deleted when dawgs_ vector is destroyed.
// bigram_dawg_ points to a dawg of two-word bigrams which always supercede if
// any of them are present on the best choices list for a word pair.
// the bigrams are stored as space-separated words where:
// (1) leading and trailing punctuation has been removed from each word and
// (2) any digits have been replaced with '?' marks.
Dawg *bigram_dawg_;
// TODO(daria): need to support multiple languages in the future,
// so maybe will need to maintain a list of dawgs of each kind.
Dawg *freq_dawg_;
Dawg *unambig_dawg_;
Dawg *punc_dawg_;
Trie *document_words_;
/// Current segmentation cost adjust factor for word rating.
/// See comments in incorporate_segcost.
float wordseg_rating_adjust_factor_;
// File for recording ambiguities discovered during dictionary search.
FILE *output_ambig_words_file_;
public:
/// Variable members.
/// These have to be declared and initialized after image_ptr_, which contains
/// the pointer to the params vector - the member of its base CCUtil class.
STRING_VAR_H(user_words_file, "", "A filename of user-provided words.");
STRING_VAR_H(user_words_suffix, "",
"A suffix of user-provided words located in tessdata.");
STRING_VAR_H(user_patterns_file, "",
"A filename of user-provided patterns.");
STRING_VAR_H(user_patterns_suffix, "",
"A suffix of user-provided patterns located in tessdata.");
BOOL_VAR_H(load_system_dawg, true, "Load system word dawg.");
BOOL_VAR_H(load_freq_dawg, true, "Load frequent word dawg.");
BOOL_VAR_H(load_unambig_dawg, true, "Load unambiguous word dawg.");
BOOL_VAR_H(load_punc_dawg, true,
"Load dawg with punctuation patterns.");
BOOL_VAR_H(load_number_dawg, true, "Load dawg with number patterns.");
BOOL_VAR_H(load_bigram_dawg, true,
"Load dawg with special word bigrams.");
double_VAR_H(xheight_penalty_subscripts, 0.125,
"Score penalty (0.1 = 10%) added if there are subscripts "
"or superscripts in a word, but it is otherwise OK.");
double_VAR_H(xheight_penalty_inconsistent, 0.25,
"Score penalty (0.1 = 10%) added if an xheight is "
"inconsistent.");
double_VAR_H(segment_penalty_dict_frequent_word, 1.0,
"Score multiplier for word matches which have good case and"
"are frequent in the given language (lower is better).");
double_VAR_H(segment_penalty_dict_case_ok, 1.1,
"Score multiplier for word matches that have good case "
"(lower is better).");
double_VAR_H(segment_penalty_dict_case_bad, 1.3125,
"Default score multiplier for word matches, which may have "
"case issues (lower is better).");
// TODO(daria): remove this param when ngram permuter is deprecated.
double_VAR_H(segment_penalty_ngram_best_choice, 1.24,
"Multipler to for the best choice from the ngram model.");
double_VAR_H(segment_penalty_dict_nonword, 1.25,
"Score multiplier for glyph fragment segmentations which "
"do not match a dictionary word (lower is better).");
double_VAR_H(segment_penalty_garbage, 1.50,
"Score multiplier for poorly cased strings that are not in"
" the dictionary and generally look like garbage (lower is"
" better).");
STRING_VAR_H(output_ambig_words_file, "",
"Output file for ambiguities found in the dictionary");
INT_VAR_H(dawg_debug_level, 0, "Set to 1 for general debug info"
", to 2 for more details, to 3 to see all the debug messages");
INT_VAR_H(hyphen_debug_level, 0, "Debug level for hyphenated words.");
INT_VAR_H(max_viterbi_list_size, 10, "Maximum size of viterbi list.");
BOOL_VAR_H(use_only_first_uft8_step, false,
"Use only the first UTF8 step of the given string"
" when computing log probabilities.");
double_VAR_H(certainty_scale, 20.0, "Certainty scaling factor");
double_VAR_H(stopper_nondict_certainty_base, -2.50,
"Certainty threshold for non-dict words");
double_VAR_H(stopper_phase2_certainty_rejection_offset, 1.0,
"Reject certainty offset");
INT_VAR_H(stopper_smallword_size, 2,
"Size of dict word to be treated as non-dict word");
double_VAR_H(stopper_certainty_per_char, -0.50,
"Certainty to add for each dict char above small word size.");
double_VAR_H(stopper_allowable_character_badness, 3.0,
"Max certaintly variation allowed in a word (in sigma)");
INT_VAR_H(stopper_debug_level, 0, "Stopper debug level");
BOOL_VAR_H(stopper_no_acceptable_choices, false,
"Make AcceptableChoice() always return false. Useful"
" when there is a need to explore all segmentations");
BOOL_VAR_H(save_raw_choices, false,
"Deprecated- backward compatibility only");
INT_VAR_H(tessedit_truncate_wordchoice_log, 10, "Max words to keep in list");
STRING_VAR_H(word_to_debug, "", "Word for which stopper debug information"
" should be printed to stdout");
STRING_VAR_H(word_to_debug_lengths, "",
"Lengths of unichars in word_to_debug");
INT_VAR_H(fragments_debug, 0, "Debug character fragments");
BOOL_VAR_H(segment_nonalphabetic_script, false,
"Don't use any alphabetic-specific tricks."
"Set to true in the traineddata config file for"
" scripts that are cursive or inherently fixed-pitch");
BOOL_VAR_H(save_doc_words, 0, "Save Document Words");
double_VAR_H(doc_dict_pending_threshold, 0.0,
"Worst certainty for using pending dictionary");
double_VAR_H(doc_dict_certainty_threshold, -2.25, "Worst certainty"
" for words that can be inserted into the document dictionary");
INT_VAR_H(max_permuter_attempts, 10000, "Maximum number of different"
" character choices to consider during permutation."
" This limit is especially useful when user patterns"
" are specified, since overly generic patterns can result in"
" dawg search exploring an overly large number of options.");
};
} // namespace tesseract
#endif // THIRD_PARTY_TESSERACT_DICT_DICT_H_