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tesseract
v4.0.0-17-g361f3264
Open Source OCR Engine
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tesseract
v4.0.0-17-g361f3264
Open Source OCR Engine
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This is the complete list of members for tesseract::LanguageModel, including all inherited members.
| acceptable_choice_found_ | tesseract::LanguageModel | protected |
| AcceptableChoiceFound() | tesseract::LanguageModel | inline |
| AcceptablePath(const ViterbiStateEntry &vse) | tesseract::LanguageModel | inlineprotected |
| AddViterbiStateEntry(LanguageModelFlagsType top_choice_flags, float denom, bool word_end, int curr_col, int curr_row, BLOB_CHOICE *b, LanguageModelState *curr_state, ViterbiStateEntry *parent_vse, LMPainPoints *pain_points, WERD_RES *word_res, BestChoiceBundle *best_choice_bundle, BlamerBundle *blamer_bundle) | tesseract::LanguageModel | protected |
| beginning_active_dawgs_ | tesseract::LanguageModel | protected |
| BOOL_VAR_H(language_model_ngram_on, false, "Turn on/off the use of character ngram model") | tesseract::LanguageModel | |
| BOOL_VAR_H(language_model_ngram_use_only_first_uft8_step, false, "Use only the first UTF8 step of the given string" " when computing log probabilities") | tesseract::LanguageModel | |
| BOOL_VAR_H(language_model_ngram_space_delimited_language, true, "Words are delimited by space") | tesseract::LanguageModel | |
| BOOL_VAR_H(language_model_use_sigmoidal_certainty, false, "Use sigmoidal score for certainty") | tesseract::LanguageModel | |
| CertaintyScore(float cert) | tesseract::LanguageModel | inlineprotected |
| ComputeAdjustedPathCost(ViterbiStateEntry *vse) | tesseract::LanguageModel | protected |
| ComputeAdjustment(int num_problems, float penalty) | tesseract::LanguageModel | inlineprotected |
| ComputeAssociateStats(int col, int row, float max_char_wh_ratio, ViterbiStateEntry *parent_vse, WERD_RES *word_res, AssociateStats *associate_stats) | tesseract::LanguageModel | inlineprotected |
| ComputeConsistencyAdjustment(const LanguageModelDawgInfo *dawg_info, const LMConsistencyInfo &consistency_info) | tesseract::LanguageModel | inlineprotected |
| 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 |
| ConstructWord(ViterbiStateEntry *vse, WERD_RES *word_res, DANGERR *fixpt, BlamerBundle *blamer_bundle, bool *truth_path) | tesseract::LanguageModel | protected |
| correct_segmentation_explored_ | tesseract::LanguageModel | protected |
| dawg_args_ | tesseract::LanguageModel | protected |
| dict_ | tesseract::LanguageModel | protected |
| double_VAR_H(language_model_ngram_small_prob, 0.000001, "To avoid overly small denominators use this as the floor" " of the probability returned by the ngram model") | tesseract::LanguageModel | |
| double_VAR_H(language_model_ngram_nonmatch_score, -40.0, "Average classifier score of a non-matching unichar") | tesseract::LanguageModel | |
| double_VAR_H(language_model_ngram_scale_factor, 0.03, "Strength of the character ngram model relative to the" " character classifier ") | tesseract::LanguageModel | |
| double_VAR_H(language_model_ngram_rating_factor, 16.0, "Factor to bring log-probs into the same range as ratings" " when multiplied by outline length ") | tesseract::LanguageModel | |
| double_VAR_H(language_model_penalty_non_freq_dict_word, 0.1, "Penalty for words not in the frequent word dictionary") | tesseract::LanguageModel | |
| double_VAR_H(language_model_penalty_non_dict_word, 0.15, "Penalty for non-dictionary words") | tesseract::LanguageModel | |
| double_VAR_H(language_model_penalty_punc, 0.2, "Penalty for inconsistent punctuation") | tesseract::LanguageModel | |
| double_VAR_H(language_model_penalty_case, 0.1, "Penalty for inconsistent case") | tesseract::LanguageModel | |
| double_VAR_H(language_model_penalty_script, 0.5, "Penalty for inconsistent script") | tesseract::LanguageModel | |
| double_VAR_H(language_model_penalty_chartype, 0.3, "Penalty for inconsistent character type") | tesseract::LanguageModel | |
| double_VAR_H(language_model_penalty_font, 0.00, "Penalty for inconsistent font") | tesseract::LanguageModel | |
| double_VAR_H(language_model_penalty_spacing, 0.05, "Penalty for inconsistent spacing") | tesseract::LanguageModel | |
| double_VAR_H(language_model_penalty_increment, 0.01, "Penalty increment") | tesseract::LanguageModel | |
| ExtractFeaturesFromPath(const ViterbiStateEntry &vse, float features[]) | tesseract::LanguageModel | static |
| FillConsistencyInfo(int curr_col, bool word_end, BLOB_CHOICE *b, ViterbiStateEntry *parent_vse, WERD_RES *word_res, LMConsistencyInfo *consistency_info) | tesseract::LanguageModel | protected |
| fixed_pitch_ | tesseract::LanguageModel | protected |
| fontinfo_table_ | tesseract::LanguageModel | protected |
| GenerateDawgInfo(bool word_end, int curr_col, int curr_row, const BLOB_CHOICE &b, const ViterbiStateEntry *parent_vse) | tesseract::LanguageModel | protected |
| GenerateNgramInfo(const char *unichar, float certainty, float denom, int curr_col, int curr_row, float outline_length, const ViterbiStateEntry *parent_vse) | tesseract::LanguageModel | protected |
| GenerateTopChoiceInfo(ViterbiStateEntry *new_vse, const ViterbiStateEntry *parent_vse, LanguageModelState *lms) | tesseract::LanguageModel | protected |
| GetNextParentVSE(bool just_classified, bool mixed_alnum, const BLOB_CHOICE *bc, LanguageModelFlagsType blob_choice_flags, const UNICHARSET &unicharset, WERD_RES *word_res, ViterbiStateEntry_IT *vse_it, LanguageModelFlagsType *top_choice_flags) const | tesseract::LanguageModel | protected |
| getParamsModel() | tesseract::LanguageModel | inline |
| GetTopLowerUpperDigit(BLOB_CHOICE_LIST *curr_list, BLOB_CHOICE **first_lower, BLOB_CHOICE **first_upper, BLOB_CHOICE **first_digit) const | tesseract::LanguageModel | protected |
| InitForWord(const WERD_CHOICE *prev_word, bool fixed_pitch, float max_char_wh_ratio, float rating_cert_scale) | tesseract::LanguageModel | |
| INT_VAR_H(language_model_debug_level, 0, "Language model debug level") | tesseract::LanguageModel | |
| INT_VAR_H(language_model_ngram_order, 8, "Maximum order of the character ngram model") | tesseract::LanguageModel | |
| INT_VAR_H(language_model_viterbi_list_max_num_prunable, 10, "Maximum number of prunable (those for which PrunablePath() is" " true) entries in each viterbi list recorded in BLOB_CHOICEs") | tesseract::LanguageModel | |
| INT_VAR_H(language_model_viterbi_list_max_size, 500, "Maximum size of viterbi lists recorded in BLOB_CHOICEs") | tesseract::LanguageModel | |
| INT_VAR_H(language_model_min_compound_length, 3, "Minimum length of compound words") | tesseract::LanguageModel | |
| INT_VAR_H(wordrec_display_segmentations, 0, "Display Segmentations") | tesseract::LanguageModel | |
| kDigitFlag | tesseract::LanguageModel | static |
| kLowerCaseFlag | tesseract::LanguageModel | static |
| kMaxAvgNgramCost | tesseract::LanguageModel | static |
| kSmallestRatingFlag | tesseract::LanguageModel | static |
| kUpperCaseFlag | tesseract::LanguageModel | static |
| kXhtConsistentFlag | tesseract::LanguageModel | static |
| LanguageModel(const UnicityTable< FontInfo > *fontinfo_table, Dict *dict) | tesseract::LanguageModel | |
| max_char_wh_ratio_ | tesseract::LanguageModel | protected |
| params_model_ | tesseract::LanguageModel | protected |
| prev_word_str_ | tesseract::LanguageModel | protected |
| prev_word_unichar_step_len_ | tesseract::LanguageModel | protected |
| PrunablePath(const ViterbiStateEntry &vse) | tesseract::LanguageModel | inlineprotected |
| rating_cert_scale_ | tesseract::LanguageModel | protected |
| SetAcceptableChoiceFound(bool val) | tesseract::LanguageModel | inline |
| SetTopParentLowerUpperDigit(LanguageModelState *parent_node) const | tesseract::LanguageModel | protected |
| UpdateBestChoice(ViterbiStateEntry *vse, LMPainPoints *pain_points, WERD_RES *word_res, BestChoiceBundle *best_choice_bundle, BlamerBundle *blamer_bundle) | tesseract::LanguageModel | protected |
| UpdateState(bool just_classified, int curr_col, int curr_row, BLOB_CHOICE_LIST *curr_list, LanguageModelState *parent_node, LMPainPoints *pain_points, WERD_RES *word_res, BestChoiceBundle *best_choice_bundle, BlamerBundle *blamer_bundle) | tesseract::LanguageModel | |
| very_beginning_active_dawgs_ | tesseract::LanguageModel | protected |
| ~LanguageModel() | tesseract::LanguageModel |
1.8.13