void 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) {
if (segsearch_debug_level > 0) {
tprintf("Classifying pain point %s priority=%.4f, col=%d, row=%d\n",
pain_point_type, pain_point_priority,
pain_point.col, pain_point.row);
}
ASSERT_HOST(pain_points != NULL);
MATRIX *ratings = word_res->ratings;
// Classify blob [pain_point.col pain_point.row]
if (!pain_point.Valid(*ratings)) {
ratings->IncreaseBandSize(pain_point.row + 1 - pain_point.col);
}
ASSERT_HOST(pain_point.Valid(*ratings));
BLOB_CHOICE_LIST *classified = classify_piece(word_res->seam_array,
pain_point.col, pain_point.row,
pain_point_type,
word_res->chopped_word,
blamer_bundle);
BLOB_CHOICE_LIST *lst = ratings->get(pain_point.col, pain_point.row);
if (lst == NULL) {
ratings->put(pain_point.col, pain_point.row, classified);
} else {
// We can not delete old BLOB_CHOICEs, since they might contain
// ViterbiStateEntries that are parents of other "active" entries.
// Thus if the matrix cell already contains classifications we add
// the new ones to the beginning of the list.
BLOB_CHOICE_IT it(lst);
it.add_list_before(classified);
delete classified; // safe to delete, since empty after add_list_before()
classified = NULL;
}
if (segsearch_debug_level > 0) {
print_ratings_list("Updated ratings matrix with a new entry:",
ratings->get(pain_point.col, pain_point.row),
getDict().getUnicharset());
ratings->print(getDict().getUnicharset());
}
// Insert initial "pain points" to join the newly classified blob
// with its left and right neighbors.
if (classified != NULL && !classified->empty()) {
if (pain_point.col > 0) {
pain_points->GeneratePainPoint(
pain_point.col - 1, pain_point.row, LM_PPTYPE_SHAPE, 0.0,
true, segsearch_max_char_wh_ratio, word_res);
}
if (pain_point.row + 1 < ratings->dimension()) {
pain_points->GeneratePainPoint(
pain_point.col, pain_point.row + 1, LM_PPTYPE_SHAPE, 0.0,
true, segsearch_max_char_wh_ratio, word_res);
}
}
(*pending)[pain_point.col].SetBlobClassified(pain_point.row);
}
/**
* @name chop_word_main
*
* Classify the blobs in this word and permute the results. Find the
* worst blob in the word and chop it up. Continue this process until
* a good answer has been found or all the blobs have been chopped up
* enough. Return the word level ratings.
*/
BLOB_CHOICE_LIST_VECTOR *Wordrec::chop_word_main(WERD_RES *word) {
TBLOB *blob;
int index;
int did_chopping;
STATE state;
BLOB_CHOICE_LIST *match_result;
MATRIX *ratings = NULL;
DANGERR fixpt; /*dangerous ambig */
inT32 bit_count; //no of bits
set_denorm(&word->denorm);
BLOB_CHOICE_LIST_VECTOR *char_choices = new BLOB_CHOICE_LIST_VECTOR();
BLOB_CHOICE_LIST_VECTOR *best_char_choices = new BLOB_CHOICE_LIST_VECTOR();
did_chopping = 0;
for (blob = word->chopped_word->blobs, index = 0;
blob != NULL; blob = blob->next, index++) {
match_result = classify_blob(blob, "chop_word:", Green);
if (match_result == NULL)
cprintf("Null classifier output!\n");
*char_choices += match_result;
}
bit_count = index - 1;
set_n_ones(&state, char_choices->length() - 1);
bool acceptable = false;
bool replaced = false;
bool best_choice_updated =
getDict().permute_characters(*char_choices, word->best_choice,
word->raw_choice);
if (best_choice_updated &&
getDict().AcceptableChoice(char_choices, word->best_choice, &fixpt,
CHOPPER_CALLER, &replaced)) {
acceptable = true;
}
if (replaced)
update_blob_classifications(word->chopped_word, *char_choices);
CopyCharChoices(*char_choices, best_char_choices);
if (!acceptable) { // do more work to find a better choice
did_chopping = 1;
bool best_choice_acceptable = false;
if (chop_enable)
improve_by_chopping(word,
char_choices,
&state,
best_char_choices,
&fixpt,
&best_choice_acceptable);
if (chop_debug)
print_seams ("Final seam list:", word->seam_array);
// The force_word_assoc is almost redundant to enable_assoc. However,
// it is not conditioned on the dict behavior. For CJK, we need to force
// the associator to be invoked. When we figure out the exact behavior
// of dict on CJK, we can remove the flag if it turns out to be redundant.
if ((wordrec_enable_assoc && !best_choice_acceptable) || force_word_assoc) {
ratings = word_associator(word, &state, best_char_choices,
&fixpt, &state);
}
}
best_char_choices = rebuild_current_state(word, &state, best_char_choices,
ratings);
if (ratings != NULL) {
if (wordrec_debug_level > 0) {
tprintf("Final Ratings Matrix:\n");
ratings->print(getDict().getUnicharset());
}
ratings->delete_matrix_pointers();
delete ratings;
}
getDict().FilterWordChoices();
char_choices->delete_data_pointers();
delete char_choices;
return best_char_choices;
}
