Fixed blob division params to fix CJK training speed.

tesseract-ocr · Jun 12, 2015 · d74c625 · d74c625
1 parent 4c7ab0c
commit d74c625
Show file tree

Hide file tree

Showing 3 changed files with 128 additions and 114 deletions.
diff --git a/classify/classify.cpp b/classify/classify.cpp
@@ -33,127 +33,135 @@
 
 namespace tesseract {
 Classify::Classify()
-  : BOOL_MEMBER(prioritize_division, FALSE,
-                "Prioritize blob division over chopping", this->params()),
-    INT_MEMBER(tessedit_single_match, FALSE,
-               "Top choice only from CP", this->params()),
-    BOOL_MEMBER(classify_enable_learning, true,
-                "Enable adaptive classifier", this->params()),
-    INT_MEMBER(classify_debug_level, 0, "Classify debug level",
-               this->params()),
-    INT_MEMBER(classify_norm_method, character, "Normalization Method   ...",
-               this->params()),
-    double_MEMBER(classify_char_norm_range, 0.2,
-                  "Character Normalization Range ...", this->params()),
-    double_MEMBER(classify_min_norm_scale_x, 0.0, "Min char x-norm scale ...",
-                  this->params()),  /* PREV DEFAULT 0.1 */
-    double_MEMBER(classify_max_norm_scale_x, 0.325, "Max char x-norm scale ...",
-                  this->params()),  /* PREV DEFAULT 0.3 */
-    double_MEMBER(classify_min_norm_scale_y, 0.0, "Min char y-norm scale ...",
-                  this->params()),  /* PREV DEFAULT 0.1 */
-    double_MEMBER(classify_max_norm_scale_y, 0.325, "Max char y-norm scale ...",
-                  this->params()),  /* PREV DEFAULT 0.3 */
-    double_MEMBER(classify_max_rating_ratio, 1.5,
-                  "Veto ratio between classifier ratings", this->params()),
-    double_MEMBER(classify_max_certainty_margin, 5.5,
-                  "Veto difference between classifier certainties",
+    : BOOL_MEMBER(allow_blob_division, true, "Use divisible blobs chopping",
                   this->params()),
-    BOOL_MEMBER(tess_cn_matching, 0, "Character Normalized Matching",
-                this->params()),
-    BOOL_MEMBER(tess_bn_matching, 0, "Baseline Normalized Matching",
-                this->params()),
-    BOOL_MEMBER(classify_enable_adaptive_matcher, 1,
-                "Enable adaptive classifier",
-                this->params()),
-    BOOL_MEMBER(classify_use_pre_adapted_templates, 0,
-                "Use pre-adapted classifier templates", this->params()),
-    BOOL_MEMBER(classify_save_adapted_templates, 0,
-               "Save adapted templates to a file", this->params()),
-    BOOL_MEMBER(classify_enable_adaptive_debugger, 0, "Enable match debugger",
-                this->params()),
-    BOOL_MEMBER(classify_nonlinear_norm, 0,
-                "Non-linear stroke-density normalization", this->params()),
-    INT_MEMBER(matcher_debug_level, 0, "Matcher Debug Level", this->params()),
-    INT_MEMBER(matcher_debug_flags, 0, "Matcher Debug Flags", this->params()),
-    INT_MEMBER(classify_learning_debug_level, 0, "Learning Debug Level: ",
-               this->params()),
-    double_MEMBER(matcher_good_threshold, 0.125, "Good Match (0-1)",
+      BOOL_MEMBER(prioritize_division, FALSE,
+                  "Prioritize blob division over chopping", this->params()),
+      INT_MEMBER(tessedit_single_match, FALSE, "Top choice only from CP",
+                 this->params()),
+      BOOL_MEMBER(classify_enable_learning, true, "Enable adaptive classifier",
                   this->params()),
-    double_MEMBER(matcher_great_threshold, 0.0, "Great Match (0-1)",
+      INT_MEMBER(classify_debug_level, 0, "Classify debug level",
+                 this->params()),
+      INT_MEMBER(classify_norm_method, character, "Normalization Method   ...",
+                 this->params()),
+      double_MEMBER(classify_char_norm_range, 0.2,
+                    "Character Normalization Range ...", this->params()),
+      double_MEMBER(classify_min_norm_scale_x, 0.0, "Min char x-norm scale ...",
+                    this->params()), /* PREV DEFAULT 0.1 */
+      double_MEMBER(classify_max_norm_scale_x, 0.325,
+                    "Max char x-norm scale ...",
+                    this->params()), /* PREV DEFAULT 0.3 */
+      double_MEMBER(classify_min_norm_scale_y, 0.0, "Min char y-norm scale ...",
+                    this->params()), /* PREV DEFAULT 0.1 */
+      double_MEMBER(classify_max_norm_scale_y, 0.325,
+                    "Max char y-norm scale ...",
+                    this->params()), /* PREV DEFAULT 0.3 */
+      double_MEMBER(classify_max_rating_ratio, 1.5,
+                    "Veto ratio between classifier ratings", this->params()),
+      double_MEMBER(classify_max_certainty_margin, 5.5,
+                    "Veto difference between classifier certainties",
+                    this->params()),
+      BOOL_MEMBER(tess_cn_matching, 0, "Character Normalized Matching",
                   this->params()),
-    double_MEMBER(matcher_perfect_threshold, 0.02, "Perfect Match (0-1)",
+      BOOL_MEMBER(tess_bn_matching, 0, "Baseline Normalized Matching",
                   this->params()),
-    double_MEMBER(matcher_bad_match_pad, 0.15, "Bad Match Pad (0-1)",
+      BOOL_MEMBER(classify_enable_adaptive_matcher, 1,
+                  "Enable adaptive classifier", this->params()),
+      BOOL_MEMBER(classify_use_pre_adapted_templates, 0,
+                  "Use pre-adapted classifier templates", this->params()),
+      BOOL_MEMBER(classify_save_adapted_templates, 0,
+                  "Save adapted templates to a file", this->params()),
+      BOOL_MEMBER(classify_enable_adaptive_debugger, 0, "Enable match debugger",
                   this->params()),
-    double_MEMBER(matcher_rating_margin, 0.1, "New template margin (0-1)",
+      BOOL_MEMBER(classify_nonlinear_norm, 0,
+                  "Non-linear stroke-density normalization", this->params()),
+      INT_MEMBER(matcher_debug_level, 0, "Matcher Debug Level", this->params()),
+      INT_MEMBER(matcher_debug_flags, 0, "Matcher Debug Flags", this->params()),
+      INT_MEMBER(classify_learning_debug_level, 0, "Learning Debug Level: ",
+                 this->params()),
+      double_MEMBER(matcher_good_threshold, 0.125, "Good Match (0-1)",
+                    this->params()),
+      double_MEMBER(matcher_reliable_adaptive_result, 0.0, "Great Match (0-1)",
+                    this->params()),
+      double_MEMBER(matcher_perfect_threshold, 0.02, "Perfect Match (0-1)",
+                    this->params()),
+      double_MEMBER(matcher_bad_match_pad, 0.15, "Bad Match Pad (0-1)",
+                    this->params()),
+      double_MEMBER(matcher_rating_margin, 0.1, "New template margin (0-1)",
+                    this->params()),
+      double_MEMBER(matcher_avg_noise_size, 12.0, "Avg. noise blob length",
+                    this->params()),
+      INT_MEMBER(matcher_permanent_classes_min, 1, "Min # of permanent classes",
+                 this->params()),
+      INT_MEMBER(matcher_min_examples_for_prototyping, 3,
+                 "Reliable Config Threshold", this->params()),
+      INT_MEMBER(matcher_sufficient_examples_for_prototyping, 5,
+                 "Enable adaption even if the ambiguities have not been seen",
+                 this->params()),
+      double_MEMBER(matcher_clustering_max_angle_delta, 0.015,
+                    "Maximum angle delta for prototype clustering",
+                    this->params()),
+      double_MEMBER(classify_misfit_junk_penalty, 0.0,
+                    "Penalty to apply when a non-alnum is vertically out of "
+                    "its expected textline position",
+                    this->params()),
+      double_MEMBER(rating_scale, 1.5, "Rating scaling factor", this->params()),
+      double_MEMBER(certainty_scale, 20.0, "Certainty scaling factor",
+                    this->params()),
+      double_MEMBER(tessedit_class_miss_scale, 0.00390625,
+                    "Scale factor for features not used", this->params()),
+      double_MEMBER(
+          classify_adapted_pruning_factor, 2.5,
+          "Prune poor adapted results this much worse than best result",
+          this->params()),
+      double_MEMBER(classify_adapted_pruning_threshold, -1.0,
+                    "Threshold at which classify_adapted_pruning_factor starts",
+                    this->params()),
+      INT_MEMBER(classify_adapt_proto_threshold, 230,
+                 "Threshold for good protos during adaptive 0-255",
+                 this->params()),
+      INT_MEMBER(classify_adapt_feature_threshold, 230,
+                 "Threshold for good features during adaptive 0-255",
+                 this->params()),
+      BOOL_MEMBER(disable_character_fragments, TRUE,
+                  "Do not include character fragments in the"
+                  " results of the classifier",
                   this->params()),
-    double_MEMBER(matcher_avg_noise_size, 12.0, "Avg. noise blob length",
+      double_MEMBER(classify_character_fragments_garbage_certainty_threshold,
+                    -3.0,
+                    "Exclude fragments that do not look like whole"
+                    " characters from training and adaption",
+                    this->params()),
+      BOOL_MEMBER(classify_debug_character_fragments, FALSE,
+                  "Bring up graphical debugging windows for fragments training",
                   this->params()),
-    INT_MEMBER(matcher_permanent_classes_min, 1, "Min # of permanent classes",
-               this->params()),
-    INT_MEMBER(matcher_min_examples_for_prototyping, 3,
-               "Reliable Config Threshold", this->params()),
-    INT_MEMBER(matcher_sufficient_examples_for_prototyping, 5,
-               "Enable adaption even if the ambiguities have not been seen",
-               this->params()),
-    double_MEMBER(matcher_clustering_max_angle_delta, 0.015,
-                  "Maximum angle delta for prototype clustering",
+      BOOL_MEMBER(matcher_debug_separate_windows, FALSE,
+                  "Use two different windows for debugging the matching: "
+                  "One for the protos and one for the features.",
                   this->params()),
-    double_MEMBER(classify_misfit_junk_penalty, 0.0,
-                  "Penalty to apply when a non-alnum is vertically out of "
-                  "its expected textline position",
-                  this->params()),
-    double_MEMBER(rating_scale, 1.5, "Rating scaling factor", this->params()),
-    double_MEMBER(certainty_scale, 20.0, "Certainty scaling factor",
-                  this->params()),
-    double_MEMBER(tessedit_class_miss_scale, 0.00390625,
-                  "Scale factor for features not used", this->params()),
-    double_MEMBER(classify_adapted_pruning_factor, 2.5,
-                  "Prune poor adapted results this much worse than best result",
-                  this->params()),
-    double_MEMBER(classify_adapted_pruning_threshold, -1.0,
-                  "Threshold at which classify_adapted_pruning_factor starts",
-                  this->params()),
-    INT_MEMBER(classify_adapt_proto_threshold, 230,
-               "Threshold for good protos during adaptive 0-255",
-               this->params()),
-    INT_MEMBER(classify_adapt_feature_threshold, 230,
-               "Threshold for good features during adaptive 0-255",
-               this->params()),
-    BOOL_MEMBER(disable_character_fragments, TRUE,
-                "Do not include character fragments in the"
-                " results of the classifier", this->params()),
-    double_MEMBER(classify_character_fragments_garbage_certainty_threshold,
-                  -3.0, "Exclude fragments that do not look like whole"
-                  " characters from training and adaption", this->params()),
-    BOOL_MEMBER(classify_debug_character_fragments, FALSE,
-                "Bring up graphical debugging windows for fragments training",
-                this->params()),
-    BOOL_MEMBER(matcher_debug_separate_windows, FALSE,
-                "Use two different windows for debugging the matching: "
-                "One for the protos and one for the features.", this->params()),
-    STRING_MEMBER(classify_learn_debug_str, "", "Class str to debug learning",
-                  this->params()),
-    INT_MEMBER(classify_class_pruner_threshold, 229,
-               "Class Pruner Threshold 0-255", this->params()),
-    INT_MEMBER(classify_class_pruner_multiplier, 15,
-               "Class Pruner Multiplier 0-255:       ", this->params()),
-    INT_MEMBER(classify_cp_cutoff_strength, 7,
-               "Class Pruner CutoffStrength:         ", this->params()),
-    INT_MEMBER(classify_integer_matcher_multiplier, 10,
-               "Integer Matcher Multiplier  0-255:   ", this->params()),
-    EnableLearning(true),
-    INT_MEMBER(il1_adaption_test, 0, "Dont adapt to i/I at beginning of word",
-               this->params()),
-    BOOL_MEMBER(classify_bln_numeric_mode, 0,
-                "Assume the input is numbers [0-9].", this->params()),
-    double_MEMBER(speckle_large_max_size, 0.30, "Max large speckle size",
-                  this->params()),
-    double_MEMBER(speckle_rating_penalty, 10.0,
-                  "Penalty to add to worst rating for noise", this->params()),
-    shape_table_(NULL),
-    dict_(this),
-    static_classifier_(NULL) {
+      STRING_MEMBER(classify_learn_debug_str, "", "Class str to debug learning",
+                    this->params()),
+      INT_MEMBER(classify_class_pruner_threshold, 229,
+                 "Class Pruner Threshold 0-255", this->params()),
+      INT_MEMBER(classify_class_pruner_multiplier, 15,
+                 "Class Pruner Multiplier 0-255:       ", this->params()),
+      INT_MEMBER(classify_cp_cutoff_strength, 7,
+                 "Class Pruner CutoffStrength:         ", this->params()),
+      INT_MEMBER(classify_integer_matcher_multiplier, 10,
+                 "Integer Matcher Multiplier  0-255:   ", this->params()),
+      EnableLearning(true),
+      INT_MEMBER(il1_adaption_test, 0, "Dont adapt to i/I at beginning of word",
+                 this->params()),
+      BOOL_MEMBER(classify_bln_numeric_mode, 0,
+                  "Assume the input is numbers [0-9].", this->params()),
+      double_MEMBER(speckle_large_max_size, 0.30, "Max large speckle size",
+                    this->params()),
+      double_MEMBER(speckle_rating_penalty, 10.0,
+                    "Penalty to add to worst rating for noise", this->params()),
+      shape_table_(NULL),
+      dict_(this),
+      static_classifier_(NULL) {
   fontinfo_table_.set_compare_callback(
       NewPermanentTessCallback(CompareFontInfo));
   fontinfo_table_.set_clear_callback(

diff --git a/classify/classify.h b/classify/classify.h
@@ -374,6 +374,12 @@ class Classify : public CCStruct {
   // Member variables.
 
   // Parameters.
+  // Set during training (in lang.config) to indicate whether the divisible
+  // blobs chopper should be used (true for latin script.)
+  BOOL_VAR_H(allow_blob_division, true, "Use divisible blobs chopping");
+  // Set during training (in lang.config) to indicate whether the divisible
+  // blobs chopper should be used in preference to chopping. Set to true for
+  // southern Indic scripts.
   BOOL_VAR_H(prioritize_division, FALSE,
              "Prioritize blob division over chopping");
   INT_VAR_H(tessedit_single_match, FALSE, "Top choice only from CP");

diff --git a/wordrec/chopper.cpp b/wordrec/chopper.cpp
@@ -200,7 +200,7 @@ SEAM *Wordrec::attempt_blob_chop(TWERD *word, TBLOB *blob, inT32 blob_number,
   if (seam == NULL) {
     if (repair_unchopped_blobs)
       restore_outline_tree(blob->outlines);
-    if (word->latin_script) {
+    if (allow_blob_division && !prioritize_division) {
       // If the blob can simply be divided into outlines, then do that.
       TPOINT location;
       if (divisible_blob(blob, italic_blob, &location)) {