|
tesseract
v4.0.0-17-g361f3264
Open Source OCR Engine
|
|
|
tesseract
v4.0.0-17-g361f3264
Open Source OCR Engine
|
|
This is the complete list of members for tesseract::Wordrec, including all inherited members.
| AdaptableWord(WERD_RES *word) | tesseract::Classify | |
| AdaptedTemplates | tesseract::Classify | |
| AdaptiveClassifier(TBLOB *Blob, BLOB_CHOICE_LIST *Choices) | tesseract::Classify | |
| AdaptiveClassifierIsEmpty() const | tesseract::Classify | inline |
| AdaptiveClassifierIsFull() const | tesseract::Classify | inline |
| AdaptToChar(TBLOB *Blob, CLASS_ID ClassId, int FontinfoId, float Threshold, ADAPT_TEMPLATES adaptive_templates) | tesseract::Classify | |
| add_point_to_list(PointHeap *point_heap, EDGEPT *point) | tesseract::Wordrec | |
| add_seam_to_queue(float new_priority, SEAM *new_seam, SeamQueue *seams) | tesseract::Wordrec | |
| AddLargeSpeckleTo(int blob_length, BLOB_CHOICE_LIST *choices) | tesseract::Classify | |
| AddNewResult(const UnicharRating &new_result, ADAPT_RESULTS *results) | tesseract::Classify | |
| AllConfigsOff | tesseract::Classify | |
| AllConfigsOn | tesseract::Classify | |
| AllProtosOn | tesseract::Classify | |
| AmbigClassifier(const GenericVector< INT_FEATURE_STRUCT > &int_features, const INT_FX_RESULT_STRUCT &fx_info, const TBLOB *blob, INT_TEMPLATES templates, ADAPT_CLASS *classes, UNICHAR_ID *ambiguities, ADAPT_RESULTS *results) | tesseract::Classify | |
| ambigs_debug_level | tesseract::CCUtil | |
| angle_change(EDGEPT *point1, EDGEPT *point2, EDGEPT *point3) | tesseract::Wordrec | |
| attempt_blob_chop(TWERD *word, TBLOB *blob, int32_t blob_number, bool italic_blob, const GenericVector< SEAM *> &seams) | tesseract::Wordrec | |
| BackupAdaptedTemplates | tesseract::Classify | |
| BaselineClassifier(TBLOB *Blob, const GenericVector< INT_FEATURE_STRUCT > &int_features, const INT_FX_RESULT_STRUCT &fx_info, ADAPT_TEMPLATES Templates, ADAPT_RESULTS *Results) | tesseract::Classify | |
| blame_reasons_ | tesseract::Wordrec | |
| BOOL_VAR_H(merge_fragments_in_matrix, TRUE, "Merge the fragments in the ratings matrix and delete them " "after merging") | tesseract::Wordrec | |
| BOOL_VAR_H(wordrec_no_block, FALSE, "Don't output block information") | tesseract::Wordrec | |
| BOOL_VAR_H(wordrec_enable_assoc, TRUE, "Associator Enable") | tesseract::Wordrec | |
| BOOL_VAR_H(force_word_assoc, FALSE, "force associator to run regardless of what enable_assoc is." "This is used for CJK where component grouping is necessary.") | tesseract::Wordrec | |
| BOOL_VAR_H(fragments_guide_chopper, FALSE, "Use information from fragments to guide chopping process") | tesseract::Wordrec | |
| BOOL_VAR_H(chop_enable, 1, "Chop enable") | tesseract::Wordrec | |
| BOOL_VAR_H(chop_vertical_creep, 0, "Vertical creep") | tesseract::Wordrec | |
| BOOL_VAR_H(chop_new_seam_pile, 1, "Use new seam_pile") | tesseract::Wordrec | |
| BOOL_VAR_H(assume_fixed_pitch_char_segment, FALSE, "include fixed-pitch heuristics in char segmentation") | tesseract::Wordrec | |
| BOOL_VAR_H(wordrec_skip_no_truth_words, false, "Only run OCR for words that had truth recorded in BlamerBundle") | tesseract::Wordrec | |
| BOOL_VAR_H(wordrec_debug_blamer, false, "Print blamer debug messages") | tesseract::Wordrec | |
| BOOL_VAR_H(wordrec_run_blamer, false, "Try to set the blame for errors") | tesseract::Wordrec | |
| BOOL_VAR_H(save_alt_choices, true, "Save alternative paths found during chopping " "and segmentation search") | tesseract::Wordrec | |
| tesseract::Classify::BOOL_VAR_H(allow_blob_division, true, "Use divisible blobs chopping") | tesseract::Classify | |
| tesseract::Classify::BOOL_VAR_H(prioritize_division, FALSE, "Prioritize blob division over chopping") | tesseract::Classify | |
| tesseract::Classify::BOOL_VAR_H(classify_enable_learning, true, "Enable adaptive classifier") | tesseract::Classify | |
| tesseract::Classify::BOOL_VAR_H(tess_cn_matching, 0, "Character Normalized Matching") | tesseract::Classify | |
| tesseract::Classify::BOOL_VAR_H(tess_bn_matching, 0, "Baseline Normalized Matching") | tesseract::Classify | |
| tesseract::Classify::BOOL_VAR_H(classify_enable_adaptive_matcher, 1, "Enable adaptive classifier") | tesseract::Classify | |
| tesseract::Classify::BOOL_VAR_H(classify_use_pre_adapted_templates, 0, "Use pre-adapted classifier templates") | tesseract::Classify | |
| tesseract::Classify::BOOL_VAR_H(classify_save_adapted_templates, 0, "Save adapted templates to a file") | tesseract::Classify | |
| tesseract::Classify::BOOL_VAR_H(classify_enable_adaptive_debugger, 0, "Enable match debugger") | tesseract::Classify | |
| tesseract::Classify::BOOL_VAR_H(classify_nonlinear_norm, 0, "Non-linear stroke-density normalization") | tesseract::Classify | |
| tesseract::Classify::BOOL_VAR_H(disable_character_fragments, TRUE, "Do not include character fragments in the" " results of the classifier") | tesseract::Classify | |
| tesseract::Classify::BOOL_VAR_H(classify_debug_character_fragments, FALSE, "Bring up graphical debugging windows for fragments training") | tesseract::Classify | |
| tesseract::Classify::BOOL_VAR_H(matcher_debug_separate_windows, FALSE, "Use two different windows for debugging the matching: " "One for the protos and one for the features.") | tesseract::Classify | |
| tesseract::Classify::BOOL_VAR_H(classify_bln_numeric_mode, 0, "Assume the input is numbers [0-9].") | tesseract::Classify | |
| call_matcher(TBLOB *blob) | tesseract::Wordrec | |
| CallFillLattice(const MATRIX &ratings, const WERD_CHOICE_LIST &best_choices, const UNICHARSET &unicharset, BlamerBundle *blamer_bundle) | tesseract::Wordrec | inline |
| cc_recog(WERD_RES *word) | tesseract::Wordrec | |
| CCStruct()=default | tesseract::CCStruct | |
| CCUtil() | tesseract::CCUtil | |
| CharNormClassifier(TBLOB *blob, const TrainingSample &sample, ADAPT_RESULTS *adapt_results) | tesseract::Classify | |
| CharNormTrainingSample(bool pruner_only, int keep_this, const TrainingSample &sample, GenericVector< UnicharRating > *results) | tesseract::Classify | |
| choose_best_seam(SeamQueue *seam_queue, const SPLIT *split, PRIORITY priority, SEAM **seam_result, TBLOB *blob, SeamPile *seam_pile) | tesseract::Wordrec | |
| chop_numbered_blob(TWERD *word, int32_t blob_number, bool italic_blob, const GenericVector< SEAM *> &seams) | tesseract::Wordrec | |
| chop_one_blob(const GenericVector< TBOX > &boxes, const GenericVector< BLOB_CHOICE *> &blob_choices, WERD_RES *word_res, int *blob_number) | tesseract::Wordrec | |
| chop_overlapping_blob(const GenericVector< TBOX > &boxes, bool italic_blob, WERD_RES *word_res, int *blob_number) | tesseract::Wordrec | |
| chop_word_main(WERD_RES *word) | tesseract::Wordrec | |
| ClassAndConfigIDToFontOrShapeID(int class_id, int int_result_config) const | tesseract::Classify | |
| ClassIDToDebugStr(const INT_TEMPLATES_STRUCT *templates, int class_id, int config_id) const | tesseract::Classify | |
| Classify() | tesseract::Classify | |
| classify_blob(TBLOB *blob, const char *string, C_COL color, BlamerBundle *blamer_bundle) | tesseract::Wordrec | |
| classify_piece(const GenericVector< SEAM *> &seams, int16_t start, int16_t end, const char *description, TWERD *word, BlamerBundle *blamer_bundle) | tesseract::Wordrec | virtual |
| ClassifyAsNoise(ADAPT_RESULTS *Results) | tesseract::Classify | |
| ClearCharNormArray(uint8_t *char_norm_array) | tesseract::Classify | |
| combine_seam(const SeamPile &seam_pile, const SEAM *seam, SeamQueue *seam_queue) | tesseract::Wordrec | |
| ComputeCharNormArrays(FEATURE_STRUCT *norm_feature, INT_TEMPLATES_STRUCT *templates, uint8_t *char_norm_array, uint8_t *pruner_array) | tesseract::Classify | |
| ComputeCorrectedRating(bool debug, int unichar_id, double cp_rating, double im_rating, int feature_misses, int bottom, int top, int blob_length, int matcher_multiplier, const uint8_t *cn_factors) | tesseract::Classify | |
| ComputeIntCharNormArray(const FEATURE_STRUCT &norm_feature, uint8_t *char_norm_array) | tesseract::Classify | |
| ComputeIntFeatures(FEATURE_SET Features, INT_FEATURE_ARRAY IntFeatures) | tesseract::Classify | |
| ComputeNormMatch(CLASS_ID ClassId, const FEATURE_STRUCT &feature, bool DebugMatch) | tesseract::Classify | |
| ConvertMatchesToChoices(const DENORM &denorm, const TBOX &box, ADAPT_RESULTS *Results, BLOB_CHOICE_LIST *Choices) | tesseract::Classify | |
| ConvertProto(PROTO Proto, int ProtoId, INT_CLASS Class) | tesseract::Classify | |
| CreateIntTemplates(CLASSES FloatProtos, const UNICHARSET &target_unicharset) | tesseract::Classify | |
| CUtil()=default | tesseract::CUtil | |
| datadir | tesseract::CCUtil | |
| DebugAdaptiveClassifier(TBLOB *Blob, ADAPT_RESULTS *Results) | tesseract::Classify | |
| dict_word(const WERD_CHOICE &word) | tesseract::Wordrec | |
| directory | tesseract::CCUtil | |
| DisplayAdaptedChar(TBLOB *blob, INT_CLASS_STRUCT *int_class) | tesseract::Classify | |
| DoAdaptiveMatch(TBLOB *Blob, ADAPT_RESULTS *Results) | tesseract::Classify | |
| DoSegSearch(WERD_RES *word_res) | tesseract::Wordrec | |
| double_VAR_H(wordrec_worst_state, 1, "Worst segmentation state") | tesseract::Wordrec | |
| double_VAR_H(tessedit_certainty_threshold, -2.25, "Good blob limit") | tesseract::Wordrec | |
| double_VAR_H(chop_split_dist_knob, 0.5, "Split length adjustment") | tesseract::Wordrec | |
| double_VAR_H(chop_overlap_knob, 0.9, "Split overlap adjustment") | tesseract::Wordrec | |
| double_VAR_H(chop_center_knob, 0.15, "Split center adjustment") | tesseract::Wordrec | |
| double_VAR_H(chop_sharpness_knob, 0.06, "Split sharpness adjustment") | tesseract::Wordrec | |
| double_VAR_H(chop_width_change_knob, 5.0, "Width change adjustment") | tesseract::Wordrec | |
| double_VAR_H(chop_ok_split, 100.0, "OK split limit") | tesseract::Wordrec | |
| double_VAR_H(chop_good_split, 50.0, "Good split limit") | tesseract::Wordrec | |
| double_VAR_H(segsearch_max_char_wh_ratio, 2.0, "Maximum character width-to-height ratio") | tesseract::Wordrec | |
| tesseract::Classify::double_VAR_H(classify_char_norm_range, 0.2, "Character Normalization Range ...") | tesseract::Classify | |
| tesseract::Classify::double_VAR_H(classify_min_norm_scale_x, 0.0, "Min char x-norm scale ...") | tesseract::Classify | |
| tesseract::Classify::double_VAR_H(classify_max_norm_scale_x, 0.325, "Max char x-norm scale ...") | tesseract::Classify | |
| tesseract::Classify::double_VAR_H(classify_min_norm_scale_y, 0.0, "Min char y-norm scale ...") | tesseract::Classify | |
| tesseract::Classify::double_VAR_H(classify_max_norm_scale_y, 0.325, "Max char y-norm scale ...") | tesseract::Classify | |
| tesseract::Classify::double_VAR_H(classify_max_rating_ratio, 1.5, "Veto ratio between classifier ratings") | tesseract::Classify | |
| tesseract::Classify::double_VAR_H(classify_max_certainty_margin, 5.5, "Veto difference between classifier certainties") | tesseract::Classify | |
| tesseract::Classify::double_VAR_H(matcher_good_threshold, 0.125, "Good Match (0-1)") | tesseract::Classify | |
| tesseract::Classify::double_VAR_H(matcher_reliable_adaptive_result, 0.0, "Great Match (0-1)") | tesseract::Classify | |
| tesseract::Classify::double_VAR_H(matcher_perfect_threshold, 0.02, "Perfect Match (0-1)") | tesseract::Classify | |
| tesseract::Classify::double_VAR_H(matcher_bad_match_pad, 0.15, "Bad Match Pad (0-1)") | tesseract::Classify | |
| tesseract::Classify::double_VAR_H(matcher_rating_margin, 0.1, "New template margin (0-1)") | tesseract::Classify | |
| tesseract::Classify::double_VAR_H(matcher_avg_noise_size, 12.0, "Avg. noise blob length: ") | tesseract::Classify | |
| tesseract::Classify::double_VAR_H(matcher_clustering_max_angle_delta, 0.015, "Maximum angle delta for prototype clustering") | tesseract::Classify | |
| tesseract::Classify::double_VAR_H(classify_misfit_junk_penalty, 0.0, "Penalty to apply when a non-alnum is vertically out of " "its expected textline position") | tesseract::Classify | |
| tesseract::Classify::double_VAR_H(rating_scale, 1.5, "Rating scaling factor") | tesseract::Classify | |
| tesseract::Classify::double_VAR_H(certainty_scale, 20.0, "Certainty scaling factor") | tesseract::Classify | |
| tesseract::Classify::double_VAR_H(tessedit_class_miss_scale, 0.00390625, "Scale factor for features not used") | tesseract::Classify | |
| tesseract::Classify::double_VAR_H(classify_adapted_pruning_factor, 2.5, "Prune poor adapted results this much worse than best result") | tesseract::Classify | |
| tesseract::Classify::double_VAR_H(classify_adapted_pruning_threshold, -1.0, "Threshold at which classify_adapted_pruning_factor starts") | tesseract::Classify | |
| tesseract::Classify::double_VAR_H(classify_character_fragments_garbage_certainty_threshold, -3.0, "Exclude fragments that do not match any whole character" " with at least this certainty") | tesseract::Classify | |
| tesseract::Classify::double_VAR_H(speckle_large_max_size, 0.30, "Max large speckle size") | tesseract::Classify | |
| tesseract::Classify::double_VAR_H(speckle_rating_penalty, 10.0, "Penalty to add to worst rating for noise") | tesseract::Classify | |
| EnableLearning | tesseract::Classify | |
| end_recog() | tesseract::Wordrec | |
| EndAdaptiveClassifier() | tesseract::Classify | |
| ExpandShapesAndApplyCorrections(ADAPT_CLASS *classes, bool debug, int class_id, int bottom, int top, float cp_rating, int blob_length, int matcher_multiplier, const uint8_t *cn_factors, UnicharRating *int_result, ADAPT_RESULTS *final_results) | tesseract::Classify | |
| ExtractFeatures(const TBLOB &blob, bool nonlinear_norm, GenericVector< INT_FEATURE_STRUCT > *bl_features, GenericVector< INT_FEATURE_STRUCT > *cn_features, INT_FX_RESULT_STRUCT *results, GenericVector< int > *outline_cn_counts) | tesseract::Classify | static |
| ExtractIntCNFeatures(const TBLOB &blob, const INT_FX_RESULT_STRUCT &fx_info) | tesseract::Classify | |
| ExtractIntGeoFeatures(const TBLOB &blob, const INT_FX_RESULT_STRUCT &fx_info) | tesseract::Classify | |
| ExtractOutlineFeatures(TBLOB *Blob) | tesseract::Classify | |
| ExtractPicoFeatures(TBLOB *Blob) | tesseract::Classify | |
| feature_defs_ | tesseract::Classify | protected |
| fill_filtered_fragment_list(BLOB_CHOICE_LIST *choices, int fragment_pos, int num_frag_parts, BLOB_CHOICE_LIST *filtered_choices) | tesseract::Wordrec | |
| fill_lattice_ | tesseract::Wordrec | |
| FillLattice(const MATRIX &ratings, const WERD_CHOICE_LIST &best_choices, const UNICHARSET &unicharset, BlamerBundle *blamer_bundle) | tesseract::Wordrec | |
| fontinfo_table_ | tesseract::Classify | |
| fontset_table_ | tesseract::Classify | |
| FreeNormProtos() | tesseract::Classify | |
| get_fontinfo_table() | tesseract::Classify | inline |
| get_fontinfo_table() const | tesseract::Classify | inline |
| get_fontset_table() | tesseract::Classify | inline |
| get_fragment_lists(int16_t current_frag, int16_t current_row, int16_t start, int16_t num_frag_parts, int16_t num_blobs, MATRIX *ratings, BLOB_CHOICE_LIST *choice_lists) | tesseract::Wordrec | |
| GetAdaptiveFeatures(TBLOB *Blob, INT_FEATURE_ARRAY IntFeatures, FEATURE_SET *FloatFeatures) | tesseract::Classify | |
| GetAmbiguities(TBLOB *Blob, CLASS_ID CorrectClass) | tesseract::Classify | |
| GetCharNormFeature(const INT_FX_RESULT_STRUCT &fx_info, INT_TEMPLATES templates, uint8_t *pruner_norm_array, uint8_t *char_norm_array) | tesseract::Classify | |
| GetClassToDebug(const char *Prompt, bool *adaptive_on, bool *pretrained_on, int *shape_id) | tesseract::Classify | |
| getDict() | tesseract::Classify | inlinevirtual |
| GetFontinfoId(ADAPT_CLASS Class, uint8_t ConfigId) | tesseract::Classify | |
| grade_sharpness(SPLIT *split) | tesseract::Wordrec | |
| grade_split_length(SPLIT *split) | tesseract::Wordrec | |
| im_ | tesseract::Classify | protected |
| imagebasename | tesseract::CCUtil | |
| imagefile | tesseract::CCUtil | |
| improve_by_chopping(float rating_cert_scale, WERD_RES *word, BestChoiceBundle *best_choice_bundle, BlamerBundle *blamer_bundle, LMPainPoints *pain_points, GenericVector< SegSearchPending > *pending) | tesseract::Wordrec | |
| improve_one_blob(const GenericVector< BLOB_CHOICE *> &blob_choices, DANGERR *fixpt, bool split_next_to_fragment, bool italic_blob, WERD_RES *word, int *blob_number) | tesseract::Wordrec | |
| InitAdaptedClass(TBLOB *Blob, CLASS_ID ClassId, int FontinfoId, ADAPT_CLASS Class, ADAPT_TEMPLATES Templates) | tesseract::Classify | |
| InitAdaptiveClassifier(TessdataManager *mgr) | tesseract::Classify | |
| InitBlamerForSegSearch(WERD_RES *word_res, LMPainPoints *pain_points, BlamerBundle *blamer_bundle, STRING *blamer_debug) | tesseract::Wordrec | protected |
| InitialSegSearch(WERD_RES *word_res, LMPainPoints *pain_points, GenericVector< SegSearchPending > *pending, BestChoiceBundle *best_choice_bundle, BlamerBundle *blamer_bundle) | tesseract::Wordrec | |
| INT_VAR_H(repair_unchopped_blobs, 1, "Fix blobs that aren't chopped") | tesseract::Wordrec | |
| INT_VAR_H(chop_debug, 0, "Chop debug") | tesseract::Wordrec | |
| INT_VAR_H(chop_split_length, 10000, "Split Length") | tesseract::Wordrec | |
| INT_VAR_H(chop_same_distance, 2, "Same distance") | tesseract::Wordrec | |
| INT_VAR_H(chop_min_outline_points, 6, "Min Number of Points on Outline") | tesseract::Wordrec | |
| INT_VAR_H(chop_seam_pile_size, 150, "Max number of seams in seam_pile") | tesseract::Wordrec | |
| INT_VAR_H(chop_inside_angle, -50, "Min Inside Angle Bend") | tesseract::Wordrec | |
| INT_VAR_H(chop_min_outline_area, 2000, "Min Outline Area") | tesseract::Wordrec | |
| INT_VAR_H(chop_centered_maxwidth, 90, "Width of (smaller) chopped blobs " "above which we don't care that a chop is not near the center.") | tesseract::Wordrec | |
| INT_VAR_H(chop_x_y_weight, 3, "X / Y length weight") | tesseract::Wordrec | |
| INT_VAR_H(segment_adjust_debug, 0, "Segmentation adjustment debug") | tesseract::Wordrec | |
| INT_VAR_H(wordrec_debug_level, 0, "Debug level for wordrec") | tesseract::Wordrec | |
| INT_VAR_H(wordrec_max_join_chunks, 4, "Max number of broken pieces to associate") | tesseract::Wordrec | |
| INT_VAR_H(segsearch_debug_level, 0, "SegSearch debug level") | tesseract::Wordrec | |
| INT_VAR_H(segsearch_max_pain_points, 2000, "Maximum number of pain points stored in the queue") | tesseract::Wordrec | |
| INT_VAR_H(segsearch_max_futile_classifications, 10, "Maximum number of pain point classifications per word.") | tesseract::Wordrec | |
| tesseract::Classify::INT_VAR_H(tessedit_single_match, FALSE, "Top choice only from CP") | tesseract::Classify | |
| tesseract::Classify::INT_VAR_H(classify_debug_level, 0, "Classify debug level") | tesseract::Classify | |
| tesseract::Classify::INT_VAR_H(classify_norm_method, character, "Normalization Method ...") | tesseract::Classify | |
| tesseract::Classify::INT_VAR_H(matcher_debug_level, 0, "Matcher Debug Level") | tesseract::Classify | |
| tesseract::Classify::INT_VAR_H(matcher_debug_flags, 0, "Matcher Debug Flags") | tesseract::Classify | |
| tesseract::Classify::INT_VAR_H(classify_learning_debug_level, 0, "Learning Debug Level: ") | tesseract::Classify | |
| tesseract::Classify::INT_VAR_H(matcher_permanent_classes_min, 1, "Min # of permanent classes") | tesseract::Classify | |
| tesseract::Classify::INT_VAR_H(matcher_min_examples_for_prototyping, 3, "Reliable Config Threshold") | tesseract::Classify | |
| tesseract::Classify::INT_VAR_H(matcher_sufficient_examples_for_prototyping, 5, "Enable adaption even if the ambiguities have not been seen") | tesseract::Classify | |
| tesseract::Classify::INT_VAR_H(classify_adapt_proto_threshold, 230, "Threshold for good protos during adaptive 0-255") | tesseract::Classify | |
| tesseract::Classify::INT_VAR_H(classify_adapt_feature_threshold, 230, "Threshold for good features during adaptive 0-255") | tesseract::Classify | |
| tesseract::Classify::INT_VAR_H(classify_class_pruner_threshold, 229, "Class Pruner Threshold 0-255") | tesseract::Classify | |
| tesseract::Classify::INT_VAR_H(classify_class_pruner_multiplier, 15, "Class Pruner Multiplier 0-255: ") | tesseract::Classify | |
| tesseract::Classify::INT_VAR_H(classify_cp_cutoff_strength, 7, "Class Pruner CutoffStrength: ") | tesseract::Classify | |
| tesseract::Classify::INT_VAR_H(classify_integer_matcher_multiplier, 10, "Integer Matcher Multiplier 0-255: ") | tesseract::Classify | |
| tesseract::Classify::INT_VAR_H(il1_adaption_test, 0, "Don't adapt to i/I at beginning of word") | tesseract::Classify | |
| is_inside_angle(EDGEPT *pt) | tesseract::Wordrec | |
| kAscenderFraction | tesseract::CCStruct | static |
| kDescenderFraction | tesseract::CCStruct | static |
| kXHeightCapRatio | tesseract::CCStruct | static |
| kXHeightFraction | tesseract::CCStruct | static |
| lang | tesseract::CCUtil | |
| language_data_path_prefix | tesseract::CCUtil | |
| language_model_ | tesseract::Wordrec | |
| LargeSpeckle(const TBLOB &blob) | tesseract::Classify | |
| LearnBlob(const STRING &fontname, TBLOB *Blob, const DENORM &cn_denorm, const INT_FX_RESULT_STRUCT &fx_info, const char *blob_text) | tesseract::Classify | |
| LearnPieces(const char *fontname, int start, int length, float threshold, CharSegmentationType segmentation, const char *correct_text, WERD_RES *word) | tesseract::Classify | |
| LearnWord(const char *fontname, WERD_RES *word) | tesseract::Classify | |
| LooksLikeGarbage(TBLOB *blob) | tesseract::Classify | |
| main_setup(const char *argv0, const char *basename) | tesseract::CCUtil | |
| MakeNewTemporaryConfig(ADAPT_TEMPLATES Templates, CLASS_ID ClassId, int FontinfoId, int NumFeatures, INT_FEATURE_ARRAY Features, FEATURE_SET FloatFeatures) | tesseract::Classify | |
| MakeNewTempProtos(FEATURE_SET Features, int NumBadFeat, FEATURE_ID BadFeat[], INT_CLASS IClass, ADAPT_CLASS Class, BIT_VECTOR TempProtoMask) | tesseract::Classify | |
| MakePermanent(ADAPT_TEMPLATES Templates, CLASS_ID ClassId, int ConfigId, TBLOB *Blob) | tesseract::Classify | |
| MasterMatcher(INT_TEMPLATES templates, int16_t num_features, const INT_FEATURE_STRUCT *features, const uint8_t *norm_factors, ADAPT_CLASS *classes, int debug, int matcher_multiplier, const TBOX &blob_box, const GenericVector< CP_RESULT_STRUCT > &results, ADAPT_RESULTS *final_results) | tesseract::Classify | |
| merge_and_put_fragment_lists(int16_t row, int16_t column, int16_t num_frag_parts, BLOB_CHOICE_LIST *choice_lists, MATRIX *ratings) | tesseract::Wordrec | |
| merge_fragments(MATRIX *ratings, int16_t num_blobs) | tesseract::Wordrec | |
| near_point(EDGEPT *point, EDGEPT *line_pt_0, EDGEPT *line_pt_1, EDGEPT **near_pt) | tesseract::Wordrec | |
| new_max_point(EDGEPT *local_max, PointHeap *points) | tesseract::Wordrec | |
| new_min_point(EDGEPT *local_min, PointHeap *points) | tesseract::Wordrec | |
| NewAdaptedTemplates(bool InitFromUnicharset) | tesseract::Classify | |
| NormalizeOutlines(LIST Outlines, float *XScale, float *YScale) | tesseract::Classify | |
| NormProtos | tesseract::Classify | |
| params() | tesseract::CCUtil | inline |
| pass2_ok_split | tesseract::Wordrec | |
| pick_close_point(EDGEPT *critical_point, EDGEPT *vertical_point, int *best_dist) | tesseract::Wordrec | |
| pick_good_seam(TBLOB *blob) | tesseract::Wordrec | |
| point_priority(EDGEPT *point) | tesseract::Wordrec | |
| PreTrainedTemplates | tesseract::Classify | |
| prev_word_best_choice_ | tesseract::Wordrec | |
| PrintAdaptedTemplates(FILE *File, ADAPT_TEMPLATES Templates) | tesseract::Classify | |
| PrintAdaptiveMatchResults(const ADAPT_RESULTS &results) | tesseract::Classify | |
| prioritize_points(TESSLINE *outline, PointHeap *points) | tesseract::Wordrec | |
| ProcessSegSearchPainPoint(float pain_point_priority, const MATRIX_COORD &pain_point, const char *pain_point_type, GenericVector< SegSearchPending > *pending, WERD_RES *word_res, LMPainPoints *pain_points, BlamerBundle *blamer_bundle) | tesseract::Wordrec | protected |
| program_editdown(int32_t elasped_time) | tesseract::Wordrec | |
| program_editup(const char *textbase, TessdataManager *init_classifier, TessdataManager *init_dict) | tesseract::Wordrec | |
| PruneClasses(const INT_TEMPLATES_STRUCT *int_templates, int num_features, int keep_this, const INT_FEATURE_STRUCT *features, const uint8_t *normalization_factors, const uint16_t *expected_num_features, GenericVector< CP_RESULT_STRUCT > *results) | tesseract::Classify | |
| read_variables(const char *filename, bool global_only) | tesseract::CUtil | |
| ReadAdaptedTemplates(TFile *File) | tesseract::Classify | |
| ReadIntTemplates(TFile *fp) | tesseract::Classify | |
| ReadNewCutoffs(TFile *fp, CLASS_CUTOFF_ARRAY Cutoffs) | tesseract::Classify | |
| ReadNormProtos(TFile *fp) | tesseract::Classify | |
| RefreshDebugWindow(ScrollView **win, const char *msg, int y_offset, const TBOX &wbox) | tesseract::Classify | |
| RemoveBadMatches(ADAPT_RESULTS *Results) | tesseract::Classify | |
| RemoveExtraPuncs(ADAPT_RESULTS *Results) | tesseract::Classify | |
| ResetAdaptiveClassifierInternal() | tesseract::Classify | |
| ResetNGramSearch(WERD_RES *word_res, BestChoiceBundle *best_choice_bundle, GenericVector< SegSearchPending > *pending) | tesseract::Wordrec | protected |
| SaveAltChoices(const LIST &best_choices, WERD_RES *word) | tesseract::Wordrec | |
| SegSearch(WERD_RES *word_res, BestChoiceBundle *best_choice_bundle, BlamerBundle *blamer_bundle) | tesseract::Wordrec | |
| SegSearchDone(int num_futile_classifications) | tesseract::Wordrec | inlineprotected |
| select_blob_to_split(const GenericVector< BLOB_CHOICE *> &blob_choices, float rating_ceiling, bool split_next_to_fragment) | tesseract::Wordrec | |
| select_blob_to_split_from_fixpt(DANGERR *fixpt) | tesseract::Wordrec | |
| set_pass1() | tesseract::Wordrec | |
| set_pass2() | tesseract::Wordrec | |
| SetAdaptiveThreshold(float Threshold) | tesseract::Classify | |
| SetStaticClassifier(ShapeClassifier *static_classifier) | tesseract::Classify | |
| SettupPass1() | tesseract::Classify | |
| SettupPass2() | tesseract::Classify | |
| SetupBLCNDenorms(const TBLOB &blob, bool nonlinear_norm, DENORM *bl_denorm, DENORM *cn_denorm, INT_FX_RESULT_STRUCT *fx_info) | tesseract::Classify | static |
| shape_table() const | tesseract::Classify | inline |
| shape_table_ | tesseract::Classify | protected |
| ShapeIDToClassID(int shape_id) const | tesseract::Classify | |
| ShowBestMatchFor(int shape_id, const INT_FEATURE_STRUCT *features, int num_features) | tesseract::Classify | |
| ShowMatchDisplay() | tesseract::Classify | |
| StartBackupAdaptiveClassifier() | tesseract::Classify | |
| STRING_VAR_H(classify_learn_debug_str, "", "Class str to debug learning") | tesseract::Classify | |
| SwitchAdaptiveClassifier() | tesseract::Classify | |
| TempConfigReliable(CLASS_ID class_id, const TEMP_CONFIG &config) | tesseract::Classify | |
| TempProtoMask | tesseract::Classify | |
| try_point_pairs(EDGEPT *points[50], int16_t num_points, SeamQueue *seam_queue, SeamPile *seam_pile, SEAM **seam, TBLOB *blob) | tesseract::Wordrec | |
| try_vertical_splits(EDGEPT *points[50], int16_t num_points, EDGEPT_CLIST *new_points, SeamQueue *seam_queue, SeamPile *seam_pile, SEAM **seam, TBLOB *blob) | tesseract::Wordrec | |
| unichar_ambigs | tesseract::CCUtil | |
| unicharset | tesseract::CCUtil | |
| UpdateAmbigsGroup(CLASS_ID class_id, TBLOB *Blob) | tesseract::Classify | |
| UpdateSegSearchNodes(float rating_cert_scale, int starting_col, GenericVector< SegSearchPending > *pending, WERD_RES *word_res, LMPainPoints *pain_points, BestChoiceBundle *best_choice_bundle, BlamerBundle *blamer_bundle) | tesseract::Wordrec | protected |
| use_ambigs_for_adaption | tesseract::CCUtil | |
| use_definite_ambigs_for_classifier | tesseract::CCUtil | |
| vertical_projection_point(EDGEPT *split_point, EDGEPT *target_point, EDGEPT **best_point, EDGEPT_CLIST *new_points) | tesseract::Wordrec | |
| Wordrec() | tesseract::Wordrec | |
| WriteAdaptedTemplates(FILE *File, ADAPT_TEMPLATES Templates) | tesseract::Classify | |
| WriteIntTemplates(FILE *File, INT_TEMPLATES Templates, const UNICHARSET &target_unicharset) | tesseract::Classify | |
| WriteTRFile(const STRING &filename) | tesseract::Classify | |
| ~CCStruct() | tesseract::CCStruct | virtual |
| ~CCUtil() | tesseract::CCUtil | virtual |
| ~Classify() | tesseract::Classify | virtual |
| ~CUtil() | tesseract::CUtil | virtual |
| ~Wordrec()=default | tesseract::Wordrec | virtual |
1.8.13