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tesseract/dict/dict.h
theraysmith 7cd3c74419 Deleted lots of dead code, including PBLOB 
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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 "host.h"
#include "image.h"
#include "oldlist.h"
#include "ratngs.h"
#include "stopper.h"
#include "trie.h"
#include "unicharset.h"
#include "permute.h"
#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 kAnyWordLength = -1;
static const int kRatingPad = 4;
// 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 int kMaxNumDawgEdgees = 2000000;
static const int kMaxDocDawgEdges = 250000;
static const int kMaxUserDawgEdges = 50000;
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;
struct DawgArgs {
DawgArgs(DawgInfoVector *d, DawgInfoVector *c, DawgInfoVector *ud,
DawgInfoVector *uc, float r, PermuterType p, int len, int e) :
active_dawgs(d), constraints(c), updated_active_dawgs(ud),
updated_constraints(uc), rating_margin(r) {
for (int i = 0; i < MAX_WERD_LENGTH; ++i) {
rating_array[i] = NO_RATING;
}
permuter = p;
sought_word_length = len;
end_char_choice_index = e;
}
DawgInfoVector *active_dawgs;
DawgInfoVector *constraints;
DawgInfoVector *updated_active_dawgs;
DawgInfoVector *updated_constraints;
PermuterType permuter;
int sought_word_length;
// TODO(daria): remove these fields when permdawg is deprecated.
float rating_margin; /**< pruning margin ratio */
float rating_array[MAX_WERD_LENGTH];
int end_char_choice_index;
};
class Dict {
public:
// Gain factor for ambiguity threshold.
static const float kStopperAmbiguityThresholdGain;
// Certainty offset for ambiguity threshold.
static const float kStopperAmbiguityThresholdOffset;
Dict(Image* image_ptr);
~Dict();
Image* getImage() {
return image_ptr_;
}
UNICHARSET& getUnicharset() {
return getImage()->getCCUtil()->unicharset;
}
const UnicharAmbigs &getUnicharAmbigs() {
return getImage()->getCCUtil()->unichar_ambigs;
}
inline bool compound_marker(UNICHAR_ID unichar_id) {
return (unichar_id == getUnicharset().unichar_to_id("-") ||
unichar_id == getUnicharset().unichar_to_id("/"));
}
/* hyphen.cpp ************************************************************/
/// Returns true if we've recorded the beginning of a hyphenated word.
inline bool hyphenated() { return
!last_word_on_line_ && hyphen_word_ && GetMaxFixedLengthDawgIndex() < 0;
}
/// Size of the base word (the part on the line before) of a hyphenated word.
inline int hyphen_base_size() {
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) {
if (this->hyphenated()) {
*word = *hyphen_word_;
if (hyphen_debug_level) word->print("copy_hyphen_info: ");
}
}
/// Erase the unichar ids corresponding to the portion of the word
/// from the previous line. The word is not changed if it is not
/// split between lines and hyphenated.
inline void remove_hyphen_head(WERD_CHOICE *word) {
if (this->hyphenated()) {
word->remove_unichar_ids(0, hyphen_word_->length());
if (hyphen_debug_level) hyphen_word_->print("remove_hyphen_head: ");
}
}
/// Check whether the word has a hyphen at the end.
inline bool has_hyphen_end(UNICHAR_ID unichar_id, bool first_pos) {
return (last_word_on_line_ && !first_pos &&
unichar_id == 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) {
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_, hyphen_constraints_ update last_word_on_line_.
void reset_hyphen_vars(bool last_word_on_line);
/// Update hyphen_word_, and copy the given DawgInfoVectors into
/// hyphen_active_dawgs_ and hyphen_constraints_.
void set_hyphen_word(const WERD_CHOICE &word,
const DawgInfoVector &active_dawgs,
const DawgInfoVector &constraints);
/* permdawg.cpp ************************************************************/
/// 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(int sought_word_length,
DawgInfoVector *active_dawgs,
bool ambigs_mode);
/// If hyphenated() returns true, copy the entries from hyphen_constraints_
/// into the given constraints vector.
void init_constraints(DawgInfoVector *constraints);
/// Returns true if we are operating in ambigs mode.
inline bool ambigs_mode(float rating_limit) { return rating_limit <= 0.0; }
/// 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,
int sought_word_length, int end_char_choice_index);
WERD_CHOICE *dawg_permute_and_select(
const BLOB_CHOICE_LIST_VECTOR &char_choices, float rating_limit) {
return dawg_permute_and_select(char_choices, rating_limit,
kAnyWordLength, 0);
}
/// 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.
/// Also:
/// -- sets hyphen word if needed
/// -- if word_ending is true and the word is better than best_choice,
/// copies word to best_choice and logs new word choice
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);
/* permute.cpp *************************************************************/
WERD_CHOICE *get_top_choice_word(
const BLOB_CHOICE_LIST_VECTOR &char_choices);
WERD_CHOICE *permute_top_choice(
const BLOB_CHOICE_LIST_VECTOR &char_choices,
float* rating_limit,
WERD_CHOICE *raw_choice,
BOOL8 *any_alpha);
const char* choose_il1(const char *first_char, //first choice
const char *second_char, //second choice
const char *third_char, //third choice
const char *prev_char, //prev in word
const char *next_char, //next in word
const char *next_next_char); //after next next in word
WERD_CHOICE *permute_all(const BLOB_CHOICE_LIST_VECTOR &char_choices,
const WERD_CHOICE *best_choice,
WERD_CHOICE *raw_choice);
void end_permute();
void permute_subword(const BLOB_CHOICE_LIST_VECTOR &char_choices,
float rating_limit,
int start,
int end,
WERD_CHOICE *current_word);
bool permute_characters(const BLOB_CHOICE_LIST_VECTOR &char_choices,
WERD_CHOICE *best_choice,
WERD_CHOICE *raw_choice);
WERD_CHOICE *permute_compound_words(
const BLOB_CHOICE_LIST_VECTOR &char_choices,
float rating_limit);
/// Find permutations matching a list of fixed-char-length dawgs
/// The bestchoice based on this permuter alone is returned. Alternatively,
/// non-conflicting changes can be combined through permuter_state.
WERD_CHOICE *permute_fixed_length_words(
const BLOB_CHOICE_LIST_VECTOR &char_choices,
PermuterState *permuter_state);
/// Incoporate segmentation cost into word rating
void incorporate_segcost(WERD_CHOICE* word);
/// Checks for script-consistent permutations. Similar to fixed-length
/// permuter, the best choice is returned by the function, but the combined
/// changes are also recorded into permuter_state.
WERD_CHOICE *permute_script_words(
const BLOB_CHOICE_LIST_VECTOR &char_choices,
PermuterState *permuter_state);
/// checks for consistency in character property (eg. alpah, digit, punct)
WERD_CHOICE *permute_chartype_words(
const BLOB_CHOICE_LIST_VECTOR &char_choices,
PermuterState *permuter_state);
/// Look up the main chartype for each character position and store it in
/// the given array. Also returns the dominant type from unambiguous top
/// choices.
char top_word_chartype(const BLOB_CHOICE_LIST_VECTOR &char_choices,
char* pos_chartypes);
WERD_CHOICE *top_fragments_permute_and_select(
const BLOB_CHOICE_LIST_VECTOR &char_choices,
float rating_limit);
/// While the choice being composed so far could be better
/// than best_choice keeps exploring char_choices.
/// If the end of the word is reached and the word is better than
/// best_choice, copies word to best_choice and logs the new word choice.
void go_deeper_top_fragments_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 *more_args);
/// Semi-generic functions used by multiple permuters.
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);
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);
/// Pointer to go_deeper function that will be modified by various permuters.
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);
/* stopper.cpp *************************************************************/
bool NoDangerousAmbig(WERD_CHOICE *BestChoice,
DANGERR *fixpt,
bool fix_replaceable,
BLOB_CHOICE_LIST_VECTOR *Choices,
bool *modified_blobs);
/// Replaces the corresponding wrong ngram in werd_choice with the correct
/// one. We indicate that this newly inserted ngram unichar is composed from
/// several fragments and modify the corresponding entries in blob_choices to
/// contain fragments of the correct ngram unichar instead of the original
/// unichars. Ratings and certainties of entries in blob_choices and
/// werd_choice are unichaged. E.g. for werd_choice mystring'' and ambiguity
/// ''->": werd_choice becomes mystring", first ' in blob_choices becomes
/// |"|0|2, second one is set to |"|1|2.
void ReplaceAmbig(int wrong_ngram_begin_index, int wrong_ngram_size,
UNICHAR_ID correct_ngram_id, WERD_CHOICE *werd_choice,
BLOB_CHOICE_LIST_VECTOR *blob_choices,
bool *modified_blobs);
inline void DisableChoiceAccum() { keep_word_choices_ = false; }
inline void EnableChoiceAccum() { keep_word_choices_ = true; }
inline bool ChoiceAccumEnabled() { return keep_word_choices_; }
/// Returns the length of the shortest alpha run in WordChoice.
int LengthOfShortestAlphaRun(const WERD_CHOICE &WordChoice);
/// Allocates a new viable choice data structure, copies WordChoice,
/// Certainties, and current_segmentation_ into it, returns a pointer to
/// the newly created VIABLE_CHOICE.
/// WordChoice is a choice to be converted to a viable choice.
/// AdjustFactor is a factor used to adjust ratings for WordChoice.
/// Certainties contain certainty for each character in WordChoice.
VIABLE_CHOICE NewViableChoice(const WERD_CHOICE &WordChoice,
FLOAT32 AdjustFactor,
const float Certainties[]);
/// Dumps a text representation of the specified Choice to File.
void PrintViableChoice(FILE *File, const char *Label, VIABLE_CHOICE Choice);
/// Compares unichar ids in word_choice to those in viable_choice,
/// returns true if they are the same.
bool StringSameAs(const WERD_CHOICE &WordChoice,
VIABLE_CHOICE ViableChoice);
/// Compares String to ViableChoice and returns true if they are the same.
bool StringSameAs(const char *String,
const char *String_lengths,
VIABLE_CHOICE ViableChoice);
/// 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 BLOB_CHOICE_LIST_VECTOR &Choices,
const WERD_CHOICE &BestChoice);
/// Returns true if the given best_choice is good enough to stop.
bool AcceptableChoice(BLOB_CHOICE_LIST_VECTOR *Choices,
WERD_CHOICE *BestChoice,
DANGERR *fixpt,
ACCEPTABLE_CHOICE_CALLER caller,
bool *modified_blobs);
/// 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(const WERD_CHOICE &BestChoice);
/// Compares the corresponding strings of WordChoice and ViableChoice and
/// returns true if they are the same.
int ChoiceSameAs(const WERD_CHOICE &WordChoice, VIABLE_CHOICE ViableChoice);
/// Adds Choice to ChoicesList if the adjusted certainty for Choice is within
/// a reasonable range of the best choice in ChoicesList. The ChoicesList list
/// is kept in sorted order by rating. Duplicates are removed.
/// WordChoice is the new choice for current word.
/// AdjustFactor is an adjustment factor which was applied to choice.
/// Certainties are certainties for each char in new choice.
/// raw_choice indicates whether WordChoice is a raw or best choice.
void LogNewChoice(FLOAT32 AdjustFactor, const float Certainties[],
bool raw_choice, WERD_CHOICE *WordChoice);
void EndDangerousAmbigs();
/// Returns true if WordChoice is the same as the current best choice.
bool CurrentBestChoiceIs(const WERD_CHOICE &WordChoice);
/// Returns the adjustment factor for the best choice for the current word.
FLOAT32 CurrentBestChoiceAdjustFactor();
/// Returns true if there are multiple good choices for the current word.
bool CurrentWordAmbig();
/// Prints the current choices for this word to stdout.
void DebugWordChoices();
/// Print all the choices in raw_choices_ list for non 1-1 ambiguities.
void PrintAmbigAlternatives(FILE *file, const char *label,
int label_num_unichars);
/// Fill ViableChoice with information from WordChoice, AChoice, AdjustFactor,
/// and Certainties.
void FillViableChoice(const WERD_CHOICE &WordChoice,
FLOAT32 AdjustFactor, const float Certainties[],
bool SameString, VIABLE_CHOICE ViableChoice);
/// Returns true if there are no alternative choices for the current word
/// or if all alternatives have an adjust factor worse than Threshold.
bool AlternativeChoicesWorseThan(FLOAT32 Threshold);
/// Removes from best_choices_ all choices which are not within a reasonable
/// range of the best choice.
void FilterWordChoices();
/// Compares the best choice for the current word to the best raw choice
/// to determine which characters were classified incorrectly by the
/// classifier. Then places a separate threshold into Thresholds for each
/// character in the word. If the classifier was correct, MaxRating is placed
/// into Thresholds. If the classifier was incorrect, the avg. match rating
/// (error percentage) of the classifier's incorrect choice minus some margin
/// is placed into thresholds.This can then be used by the caller to try to
/// create a new template for the desired class that will classify the
/// character with a rating better than the threshold value. The match rating
/// placed into Thresholds is never allowed to be below MinRating in order to
/// prevent trying to make overly tight templates.
/// MinRating limits how tight to make a template.
/// MaxRating limits how loose to make a template.
/// RatingMargin denotes the amount of margin to put in template.
void FindClassifierErrors(FLOAT32 MinRating,
FLOAT32 MaxRating,
FLOAT32 RatingMargin,
FLOAT32 Thresholds[]);
/// Initializes the data structures used to keep track the good word choices
/// found for a word.
void InitChoiceAccum();
/// Clears best_choices_ list accumulated by the stopper.
void ClearBestChoiceAccum();
/// Updates the blob widths in current_segmentation_ to be the same as
/// provided in BlobWidth. BlobWidth[] contains the number of chunks in each
/// blob in the current segmentation.
void LogNewSegmentation(PIECES_STATE BlobWidth);
/// Given Blob (the index of the blob that was split), adds 1 chunk to the
/// specified blob for each choice in best_choices_ and for best_raw_choice_.
void LogNewSplit(int Blob);
/// Increments the chunk count of the character in Choice which corresponds
/// to Blob (index of the blob being split).
void AddNewChunk(VIABLE_CHOICE Choice, int Blob);
/// 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);
/// 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.
void Load();
void End();
/**
* 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 two relevant input vectors: active_dawgs and
* constraints. 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. Each entry in the constraints vector contains
* an index into the dawgs_ vector and an EDGE_REF that indicates an edge
* in a pattern dawg followed to match a pattern. Currently constraints
* are used to save the state of punctuation dawgs after leading
* punctuation was found.
*
* Input:
* At word_index 0 dawg_args->active_dawgs should contain an entry for each
* dawg whose type has a bit set in kBeginningDawgsType,
* dawg_args->constraints should be empty. EDGE_REFs in active_dawgs and
* constraints vectors should be initialized to NO_EDGE. If hyphen state
* needs to be applied, initial dawg_args->active_dawgs and
* dawg_args->constrains can be copied from the saved hyphen state
* (maintained by Dict).
* For word_index > 0 the corresponding state (active_dawgs and constraints)
* can be obtained from dawg_args->updated_* passed to def_letter_is_okay
* for word_index-1.
* Note: the function assumes that active_dags, constraints and updated_*
* member variables of dawg_args are not NULL.
*
* Output:
* The function fills in dawg_args->updated_active_dawgs vector with the
* entries for dawgs that contain the word up to the letter at word_index.
* The new constraints (if any) are added to dawg_args->updated_constraints,
* the constraints from dawg_args->constraints are also copied into it.
*
* Detailed description:
* In order to determine whether the word is still valid after considering
* all the letters up to the one at word_index the following is done for
* each entry in dawg_args->active_dawgs:
*
* - next starting node is obtained from entry.ref and edge_char_of() is
* called to obtain the next edge
* - if a valid edge is found, the function returns the updated permuter
* code true and an entry [entry.dawg_index, edge] is inserted in
* dawg_args->updated_active_dawgs
* otherwise:
* - if we are dealing with dawg of type DAWG_TYPE_PUNCTUATION,
* edge_char_of() is called again, but now with kPatternUnicharID
* as unichar_id; if a valid edge is found it is recorded in
* dawg_args->updated_constraints
* - the function checks whether the word can end with the previous
* letter
* - each successor of the dawg (e.g. dawgs with type DAWG_TYPE_WORD
* could be successors to dawgs with type DAWG_TYPE_PUNCTUATION; the
* successors are defined by successors_ vector) is explored and if
* a letter is found in the successor dawg, a new entry is inserted
* into dawg_args->updated_active_dawgs with EDGE_REF being either
* NO_EDGE or an EDGE_REF recorded in constraints vector for the
* corresponding dawg index
*/
//
int def_letter_is_okay(void* void_dawg_args,
UNICHAR_ID unichar_id, bool word_end);
int (Dict::*letter_is_okay_)(void* void_dawg_args,
UNICHAR_ID unichar_id, bool word_end);
/// Calls letter_is_okay_ member function.
int LetterIsOkay(void* void_dawg_args,
UNICHAR_ID unichar_id, bool word_end) {
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_)(
getImage()->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) 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);
/// Return the number of dawgs in the dawgs_ vector.
inline const 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 pointer to the Dawg that contains words of length word_length.
inline const Dawg *GetFixedLengthDawg(int word_length) const {
if (word_length > max_fixed_length_dawgs_wdlen_) return NULL;
assert(dawgs_.size() > word_length);
return dawgs_[word_length];
}
inline const int GetMaxFixedLengthDawgIndex() const {
return max_fixed_length_dawgs_wdlen_;
}
/// 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;
}
/// At word ending make sure all the recorded constraints are satisfied.
/// Each constraint signifies that we found a beginning pattern in a
/// pattern dawg. Check that this pattern can end here (e.g. if some
/// leading punctuation is found this would ensure that we are not
/// expecting any particular trailing punctuation after the word).
inline bool ConstraintsOk(const DawgInfoVector &constraints,
int word_end, DawgType current_dawg_type) {
if (!word_end) return true;
if (current_dawg_type == DAWG_TYPE_PUNCTUATION) return true;
for (int c = 0; c < constraints.length(); ++c) {
const DawgInfo &cinfo = constraints[c];
Dawg *cdawg = dawgs_[cinfo.dawg_index];
if (!cdawg->end_of_word(cinfo.ref)) {
if (dawg_debug_level >= 3) {
tprintf("Constraint [%d, " REFFORMAT "] is not satisfied\n",
cinfo.dawg_index, cinfo.ref);
}
return false;
}
}
return true;
}
/// 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 DawgInfo &info,
UNICHAR_ID unichar_id, bool word_end,
DawgArgs *dawg_args, PermuterType *current_permuter);
/// Read/Write/Access special purpose dawgs which contain words
/// only of a certain length (used for phrase search for
/// non-space-delimited languages).
/// Reads a sequence of dawgs from the given file.
/// Appends the constructed dawgs to the given dawg_vec.
/// Fills the given table with indices of the dawgs in the
/// dawg_vec corresponding to the dawgs with words
/// of a particular length.
static void ReadFixedLengthDawgs(DawgType type, const STRING &lang,
PermuterType perm, int debug_level,
FILE *file, DawgVector *dawg_vec,
int *max_wdlen);
/// Writes the dawgs in the dawgs_vec to a file. Updates the given table with
/// the indices of dawgs in the dawg_vec for the corresponding word lengths.
static void WriteFixedLengthDawgs(
const GenericVector<SquishedDawg *> &dawg_vec,
int num_dawgs, int debug_level, FILE *output_file);
/// Check all the DAWGs to see if this word is in any of them.
inline 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 || (numbers_ok && perm == NUMBER_PERM));
}
int valid_word(const WERD_CHOICE &word, bool numbers_ok);
int valid_word(const WERD_CHOICE &word) {
return valid_word(word, false); // return NO_PERM for words with digits
}
int valid_word_or_number(const WERD_CHOICE &word) {
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) {
WERD_CHOICE word(string, getUnicharset());
return valid_word(word);
}
/// 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);
int get_top_word_script(const BLOB_CHOICE_LIST_VECTOR &char_choices,
const UNICHARSET &unicharset);
/// Adjusts the rating of the given word.
void adjust_word(WERD_CHOICE *word, float *certainty_array,
const BLOB_CHOICE_LIST_VECTOR *char_choices,
bool nonword, float additional_adjust, bool debug);
void adjust_word(WERD_CHOICE *word, float *certainty_array, bool debug) {
adjust_word(word, certainty_array, NULL, false, 0.0f, debug);
}
void adjust_non_word(WERD_CHOICE *word, float *certainty_array, bool debug) {
adjust_word(word, certainty_array, NULL, true, 0.0f, debug);
}
/// Set wordseg_rating_adjust_factor_ to the given value.
inline void SetWordsegRatingAdjustFactor(float f) {
wordseg_rating_adjust_factor_ = f;
}
private:
/** Private member variables. */
Image* image_ptr_;
/**
* 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_;
/**
* Flag used to disable accumulation of word choices
* during compound word permutation.
*/
bool keep_word_choices_;
/** Additional certainty padding allowed before a word is rejected. */
FLOAT32 reject_offset_;
/** Current word segmentation. */
PIECES_STATE current_segmentation_;
/** Variables to keep track of best/raw word choices. */
VIABLE_CHOICE best_raw_choice_;
LIST raw_choices_;
LIST best_choices_;
// Hyphen-related variables.
UNICHAR_ID hyphen_unichar_id_;
WERD_CHOICE *hyphen_word_;
DawgInfoVector hyphen_active_dawgs_;
DawgInfoVector hyphen_constraints_;
bool last_word_on_line_;
// 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.
// 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 *punc_dawg_;
Trie *document_words_;
/// Maximum word length of fixed-length word dawgs.
/// A value < 1 indicates that no fixed-length dawgs are loaded.
int max_fixed_length_dawgs_wdlen_;
/// Current segmentation cost adjust factor for word rating.
/// See comments in incorporate_segcost.
float wordseg_rating_adjust_factor_;
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_suffix, "", "A list of user-provided words.");
STRING_VAR_H(user_patterns_suffix, "",
"A list of user-provided patterns.");
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_punc_dawg, true,
"Load dawg with punctuation patterns.");
BOOL_VAR_H(load_number_dawg, true, "Load dawg with number patterns.");
BOOL_VAR_H(load_fixed_length_dawgs, true, "Load fixed length"
" dawgs (e.g. for non-space delimited languages)");
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).");
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, "Save all explored raw choices");
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");
INT_VAR_H(segment_debug, 0, "Debug the whole segmentation process");
BOOL_VAR_H(permute_debug, 0, "Debug char permutation process");
double_VAR_H(bestrate_pruning_factor, 2.0, "Multiplying factor of"
" current best rate to prune other hypotheses");
BOOL_VAR_H(permute_script_word, 0,
"Turn on word script consistency permuter");
BOOL_VAR_H(segment_segcost_rating, 0,
"incorporate segmentation cost in word rating?");
double_VAR_H(segment_reward_script, 0.95,
"Score multipler for script consistency within a word. "
"Being a 'reward' factor, it should be <= 1. "
"Smaller value implies bigger reward.");
BOOL_VAR_H(permute_fixed_length_dawg, 0,
"Turn on fixed-length phrasebook search permuter");
BOOL_VAR_H(permute_chartype_word, 0,
"Turn on character type (property) consistency permuter");
double_VAR_H(segment_reward_chartype, 0.97,
"Score multipler for char type consistency within a word. ");
// TODO(daria): remove this param when ngram permuter is deprecated.
double_VAR_H(segment_reward_ngram_best_choice, 0.99,
"Score multipler for ngram permuter's best choice"
" (only used in the Han script path).");
BOOL_VAR_H(save_doc_words, 0, "Save Document Words");
BOOL_VAR_H(doc_dict_enable, 1, "Enable Document Dictionary ");
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");
BOOL_VAR_H(ngram_permuter_activated, false,
"Activate character-level n-gram-based permuter");
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.");
BOOL_VAR_H(permute_only_top, false, "Run only the top choice permuter");
};
} // namespace tesseract
#endif // THIRD_PARTY_TESSERACT_DICT_DICT_H_
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