, including all inherited members.
acceptable_choice_found_ | tesseract::LanguageModel | [protected] |
AcceptableChoiceFound() | tesseract::LanguageModel | [inline] |
AcceptablePath(const ViterbiStateEntry &vse) | tesseract::LanguageModel | [inline, protected] |
AddViterbiStateEntry(LanguageModelFlagsType top_choice_flags, float denom, bool word_end, int curr_col, int curr_row, BLOB_CHOICE *b, BLOB_CHOICE *parent_b, ViterbiStateEntry *parent_vse, HEAP *pain_points, BestPathByColumn *best_path_by_column[], CHUNKS_RECORD *chunks_record, BestChoiceBundle *best_choice_bundle, BlamerBundle *blamer_bundle) | tesseract::LanguageModel | [protected] |
beginning_active_dawgs_ | tesseract::LanguageModel | [protected] |
beginning_constraints_ | tesseract::LanguageModel | [protected] |
CertaintyScore(float cert) | tesseract::LanguageModel | [inline, protected] |
CleanUp() | tesseract::LanguageModel | |
ComputeAdjustedPathCost(float ratings_sum, int length, float dawg_score, const LanguageModelDawgInfo *dawg_info, const LanguageModelNgramInfo *ngram_info, const LanguageModelConsistencyInfo &consistency_info, const AssociateStats &associate_stats, ViterbiStateEntry *parent_vse) | tesseract::LanguageModel | [protected] |
ComputeAdjustment(int num_problems, float penalty) | tesseract::LanguageModel | [inline, protected] |
ComputeAssociateStats(int col, int row, float max_char_wh_ratio, ViterbiStateEntry *parent_vse, CHUNKS_RECORD *chunks_record, AssociateStats *associate_stats) | tesseract::LanguageModel | [inline, protected] |
ComputeConsistencyAdjustedRatingsSum(float ratings_sum, const LanguageModelDawgInfo *dawg_info, const LanguageModelConsistencyInfo &consistency_info) | tesseract::LanguageModel | [inline, protected] |
ComputeConsistencyAdjustment(const LanguageModelDawgInfo *dawg_info, const LanguageModelConsistencyInfo &consistency_info) | tesseract::LanguageModel | [inline, protected] |
ComputeDenom(BLOB_CHOICE_LIST *curr_list) | tesseract::LanguageModel | [protected] |
ComputeNgramCost(const char *unichar, float certainty, float denom, const char *context, int *unichar_step_len, bool *found_small_prob, float *ngram_prob) | tesseract::LanguageModel | [protected] |
ComputeOutlineLength(BLOB_CHOICE *b) | tesseract::LanguageModel | [inline] |
ConstructWord(BLOB_CHOICE *b, ViterbiStateEntry *vse, CHUNKS_RECORD *chunks_record, BLOB_CHOICE_LIST_VECTOR *best_char_choices, float certainties[], float *dawg_score, STATE *state, BlamerBundle *blamer_bundle, bool *truth_path) | tesseract::LanguageModel | [protected] |
correct_segmentation_explored_ | tesseract::LanguageModel | [protected] |
dawg_args_ | tesseract::LanguageModel | [protected] |
DeleteState(BLOB_CHOICE_LIST *choices) | tesseract::LanguageModel | |
dict_ | tesseract::LanguageModel | [protected] |
empty_dawg_info_vec_ | tesseract::LanguageModel | [protected] |
ExtractRawFeaturesFromPath(const ViterbiStateEntry &vse, float *features) | tesseract::LanguageModel | [protected] |
FillConsistencyInfo(int curr_col, bool word_end, BLOB_CHOICE *b, ViterbiStateEntry *parent_vse, BLOB_CHOICE *parent_b, CHUNKS_RECORD *chunks_record, LanguageModelConsistencyInfo *consistency_info) | tesseract::LanguageModel | [protected] |
fixed_length_beginning_active_dawgs_ | tesseract::LanguageModel | [protected] |
fixed_pitch_ | tesseract::LanguageModel | [protected] |
fontinfo_table_ | tesseract::LanguageModel | [protected] |
GenerateDawgInfo(bool word_end, int script_id, int curr_col, int curr_row, const BLOB_CHOICE &b, const ViterbiStateEntry *parent_vse, LanguageModelFlagsType *changed) | tesseract::LanguageModel | [protected] |
GenerateNgramInfo(const char *unichar, float certainty, float denom, int curr_col, int curr_row, const ViterbiStateEntry *parent_vse, BLOB_CHOICE *parent_b, LanguageModelFlagsType *changed) | tesseract::LanguageModel | [protected] |
GenerateNgramModelPainPointsFromColumn(int col, int row, HEAP *pain_points, CHUNKS_RECORD *chunks_record) | tesseract::LanguageModel | |
GeneratePainPoint(int col, int row, bool ok_to_extend, float priority_adjustment, float worst_piece_cert, bool fragmented, float best_choice_cert, float max_char_wh_ratio, BLOB_CHOICE *parent_b, ViterbiStateEntry *parent_vse, CHUNKS_RECORD *chunks_record, HEAP *pain_points) | tesseract::LanguageModel | |
GeneratePainPointsFromBestChoice(HEAP *pain_points, CHUNKS_RECORD *chunks_record, BestChoiceBundle *best_choice_bundle) | tesseract::LanguageModel | |
GeneratePainPointsFromColumn(int col, const GenericVector< int > &non_empty_rows, float best_choice_cert, HEAP *pain_points, BestPathByColumn *best_path_by_column[], CHUNKS_RECORD *chunks_record) | tesseract::LanguageModel | |
GenerateProblematicPathPainPointsFromColumn(int col, int row, float best_choice_cert, HEAP *pain_points, BestPathByColumn *best_path_by_column[], CHUNKS_RECORD *chunks_record) | tesseract::LanguageModel | |
GenerateTopChoiceInfo(float ratings_sum, const LanguageModelDawgInfo *dawg_info, const LanguageModelConsistencyInfo &consistency_info, const ViterbiStateEntry *parent_vse, BLOB_CHOICE *b, LanguageModelFlagsType *top_choice_flags, LanguageModelFlagsType *changed) | tesseract::LanguageModel | [protected] |
GetPieceCertainty(BLOB_CHOICE_LIST *blist, float *cert, bool *fragmented) | tesseract::LanguageModel | [inline, protected] |
GetTopChoiceLowerUpper(LanguageModelFlagsType changed, BLOB_CHOICE_LIST *curr_list, BLOB_CHOICE **first_lower, BLOB_CHOICE **first_upper) | tesseract::LanguageModel | [protected] |
GetWorstPieceCertainty(int col, int row, MATRIX *ratings, float *cert, bool *fragmented) | tesseract::LanguageModel | [inline] |
InitForWord(const WERD_CHOICE *prev_word, bool fixed_pitch, float best_choice_cert, float max_char_wh_ratio, float rating_cert_scale, HEAP *pain_points, CHUNKS_RECORD *chunks_record, BlamerBundle *blamer_bundle, bool debug_blamer) | tesseract::LanguageModel | |
IsFragment(BLOB_CHOICE *b) | tesseract::LanguageModel | [inline, protected] |
IsHan(int script_id) | tesseract::LanguageModel | [inline, protected] |
kAllChangedFlag | tesseract::LanguageModel | [static] |
kBestChoicePainPointPriorityAdjustment | tesseract::LanguageModel | [static] |
kConsistentFlag | tesseract::LanguageModel | [static] |
kCriticalPainPointPriorityAdjustment | tesseract::LanguageModel | [static] |
kDawgFlag | tesseract::LanguageModel | [static] |
kDefaultPainPointPriorityAdjustment | tesseract::LanguageModel | [static] |
kInitialPainPointPriorityAdjustment | tesseract::LanguageModel | [static] |
kJustClassifiedFlag | tesseract::LanguageModel | [static] |
kLooseMaxCharWhRatio | tesseract::LanguageModel | [static] |
kLowerCaseFlag | tesseract::LanguageModel | [static] |
kMaxAvgNgramCost | tesseract::LanguageModel | [static] |
kMinFixedLengthDawgLength | tesseract::LanguageModel | [static] |
kNgramFlag | tesseract::LanguageModel | [static] |
kSmallestRatingFlag | tesseract::LanguageModel | [static] |
kUpperCaseFlag | tesseract::LanguageModel | [static] |
language_model_debug_level | tesseract::LanguageModel | |
language_model_fixed_length_choices_depth | tesseract::LanguageModel | |
language_model_min_compound_length | tesseract::LanguageModel | |
language_model_ngram_nonmatch_score | tesseract::LanguageModel | |
language_model_ngram_on | tesseract::LanguageModel | |
language_model_ngram_order | tesseract::LanguageModel | |
language_model_ngram_scale_factor | tesseract::LanguageModel | |
language_model_ngram_small_prob | tesseract::LanguageModel | |
language_model_ngram_space_delimited_language | tesseract::LanguageModel | |
language_model_ngram_use_only_first_uft8_step | tesseract::LanguageModel | |
language_model_penalty_case | tesseract::LanguageModel | |
language_model_penalty_chartype | tesseract::LanguageModel | |
language_model_penalty_font | tesseract::LanguageModel | |
language_model_penalty_increment | tesseract::LanguageModel | |
language_model_penalty_non_dict_word | tesseract::LanguageModel | |
language_model_penalty_non_freq_dict_word | tesseract::LanguageModel | |
language_model_penalty_punc | tesseract::LanguageModel | |
language_model_penalty_script | tesseract::LanguageModel | |
language_model_penalty_spacing | tesseract::LanguageModel | |
language_model_use_sigmoidal_certainty | tesseract::LanguageModel | |
language_model_viterbi_list_max_num_prunable | tesseract::LanguageModel | |
language_model_viterbi_list_max_size | tesseract::LanguageModel | |
LanguageModel(const UnicityTable< FontInfo > *fontinfo_table, Dict *dict) | tesseract::LanguageModel | |
max_char_wh_ratio_ | tesseract::LanguageModel | [protected] |
max_penalty_adjust_ | tesseract::LanguageModel | [protected] |
NonAlphaOrDigitMiddle(int col, int row, int dimension, UNICHAR_ID unichar_id) | tesseract::LanguageModel | [inline, protected] |
prev_word_str_ | tesseract::LanguageModel | [protected] |
prev_word_unichar_step_len_ | tesseract::LanguageModel | [protected] |
PrintViterbiStateEntry(const char *msg, ViterbiStateEntry *vse, BLOB_CHOICE *b, CHUNKS_RECORD *chunks_record) | tesseract::LanguageModel | [protected] |
ProblematicPath(const ViterbiStateEntry &vse, UNICHAR_ID unichar_id, bool word_end) | tesseract::LanguageModel | [protected] |
PrunablePath(LanguageModelFlagsType top_choice_flags, const LanguageModelDawgInfo *dawg_info) | tesseract::LanguageModel | [inline, protected] |
rating_cert_scale_ | tesseract::LanguageModel | [protected] |
UpdateBestChoice(BLOB_CHOICE *b, ViterbiStateEntry *vse, HEAP *pain_points, CHUNKS_RECORD *chunks_record, BestChoiceBundle *best_choice_bundle, BlamerBundle *blamer_bundle) | tesseract::LanguageModel | [protected] |
UpdateCoveredByFixedLengthDawgs(const DawgInfoVector &active_dawgs, int word_index, int word_length, int *skip, int *covered, float *dawg_score, bool *dawg_score_done) | tesseract::LanguageModel | [protected] |
updated_flags_ | tesseract::LanguageModel | [protected] |
UpdateState(LanguageModelFlagsType changed, int curr_col, int curr_row, BLOB_CHOICE_LIST *curr_list, BLOB_CHOICE_LIST *parent_list, HEAP *pain_points, BestPathByColumn *best_path_by_column[], CHUNKS_RECORD *chunks_record, BestChoiceBundle *best_choice_bundle, BlamerBundle *blamer_bundle) | tesseract::LanguageModel | |
~LanguageModel() | tesseract::LanguageModel | |