Ejemplo n.º 1
0
/**********************************************************************
 * save_best_state
 *
 * Save this state away to be compared later.
 **********************************************************************/
void save_best_state(CHUNKS_RECORD *chunks_record) {
  STATE state;
  SEARCH_STATE chunk_groups;
  int num_joints;

  if (save_priorities) {
    num_joints = chunks_record->ratings->dimension() - 1;

    state.part1 = 0xffffffff;
    state.part2 = 0xffffffff;

    chunk_groups = bin_to_chunks (&state, num_joints);
    display_segmentation (chunks_record->chunks, chunk_groups);
    memfree(chunk_groups);

    cprintf ("Enter the correct segmentation > ");
    fflush(stdout);
    state.part1 = 0;
    scanf ("%x", &state.part2);

    chunk_groups = bin_to_chunks (&state, num_joints);
    display_segmentation (chunks_record->chunks, chunk_groups);
    memfree(chunk_groups);
    window_wait(segm_window);  /* == 'n') */

    if (known_best_state)
      free_state(known_best_state);
    known_best_state = new_state (&state);
  }
}
Ejemplo n.º 2
0
BLOB_CHOICE_LIST *Wordrec::classify_piece(TBLOB *pieces,
                                          const DENORM& denorm,
                                          SEAMS seams,
                                          inT16 start,
                                          inT16 end,
                                          BlamerBundle *blamer_bundle) {
  BLOB_CHOICE_LIST *choices;
  TBLOB *blob;
  inT16 x;

  join_pieces(pieces, seams, start, end);
  for (blob = pieces, x = 0; x < start; x++) {
    blob = blob->next;
  }
  choices = classify_blob(blob, denorm, "pieces:", White, blamer_bundle);

  break_pieces(blob, seams, start, end);
#ifndef GRAPHICS_DISABLED
  if (wordrec_display_segmentations > 2) {
    STATE current_state;
    SEARCH_STATE chunk_groups;
    set_n_ones (&current_state, array_count(seams));
    chunk_groups = bin_to_chunks(&current_state, array_count(seams));
    display_segmentation(pieces, chunk_groups);
    window_wait(segm_window);
    memfree(chunk_groups);
  }
#endif

  return (choices);
}
Ejemplo n.º 3
0
BLOB_CHOICE_LIST *Wordrec::classify_piece(TBLOB *pieces,
                                          SEAMS seams,
                                          inT16 start,
                                          inT16 end) {
  STATE current_state;
  BLOB_CHOICE_LIST *choices;
  TBLOB *pblob;
  TBLOB *blob;
  TBLOB *nblob;
  inT16 x;
  SEARCH_STATE chunk_groups;

  set_n_ones (&current_state, array_count (seams));

  join_pieces(pieces, seams, start, end);
  for (blob = pieces, pblob = NULL, x = 0; x < start; x++) {
    pblob = blob;
    blob = blob->next;
  }
  for (nblob = blob->next; x < end; x++)
    nblob = nblob->next;
  choices = classify_blob (pblob, blob, nblob, NULL, "pieces:", White);

  break_pieces(blob, seams, start, end);
#ifndef GRAPHICS_DISABLED
  if (wordrec_display_segmentations > 2) {
    chunk_groups = bin_to_chunks (&current_state, array_count (seams));
    display_segmentation(pieces, chunk_groups);
    window_wait(segm_window);
    memfree(chunk_groups);
  }
#endif

  return (choices);
}
Ejemplo n.º 4
0
/**
 * @name evaluate_state
 *
 * Evaluate the segmentation that is represented by this state in the
 * best first search.  Add this state to the "states_seen" list.
 */
inT16 Wordrec::evaluate_state(CHUNKS_RECORD *chunks_record,
                              SEARCH_RECORD *the_search,
                              DANGERR *fixpt) {
  BLOB_CHOICE_LIST_VECTOR *char_choices;
  SEARCH_STATE chunk_groups;
  float rating_limit = the_search->best_choice->rating();
  inT16 keep_going = TRUE;
  PIECES_STATE widths;

  the_search->num_states++;
  chunk_groups = bin_to_chunks(the_search->this_state,
                               the_search->num_joints);
  bin_to_pieces (the_search->this_state, the_search->num_joints, widths);
  getDict().LogNewSegmentation(widths);

  char_choices = evaluate_chunks(chunks_record, chunk_groups);
  wordseg_rating_adjust_factor = -1.0f;
  if (char_choices != NULL && char_choices->length() > 0) {
    // Compute the segmentation cost and include the cost in word rating.
    // TODO(dsl): We should change the SEARCH_RECORD to store this cost
    // from state evaluation and avoid recomputing it here.
    prioritize_state(chunks_record, the_search);
    wordseg_rating_adjust_factor = the_search->segcost_bias;
    getDict().permute_characters(*char_choices, rating_limit,
                                 the_search->best_choice,
                                 the_search->raw_choice);
    bool replaced = false;
    if (getDict().AcceptableChoice(char_choices, the_search->best_choice,
                                   *(the_search->raw_choice), fixpt,
                                   ASSOCIATOR_CALLER, &replaced)) {
      keep_going = FALSE;
    }
  }
  wordseg_rating_adjust_factor = -1.0f;

#ifndef GRAPHICS_DISABLED
  if (wordrec_display_segmentations) {
    display_segmentation (chunks_record->chunks, chunk_groups);
    if (wordrec_display_segmentations > 1)
      window_wait(segm_window);
  }
#endif

  if (rating_limit != the_search->best_choice->rating()) {
    the_search->before_best = the_search->num_states;
    the_search->best_state->part1 = the_search->this_state->part1;
    the_search->best_state->part2 = the_search->this_state->part2;
    replace_char_widths(chunks_record, chunk_groups);
  }
  else if (char_choices != NULL)
    fixpt->index = -1;

  if (char_choices != NULL) delete char_choices;
  memfree(chunk_groups);

  return (keep_going);
}
Ejemplo n.º 5
0
/**********************************************************************
 * classify_piece
 *
 * Create a larger piece from a collection of smaller ones.  Classify
 * it and return the results.  Take the large piece apart to leave
 * the collection of small pieces un modified.
 **********************************************************************/
CHOICES classify_piece(TBLOB *pieces,
                       SEAMS seams,
                       INT16 start,
                       INT16 end,
                       INT32 fx,
                       STATE *this_state,
                       STATE *best_state,
                       INT32 pass,
                       INT32 blob_index) {
  STATE current_state;
  CHOICES choices;
  TBLOB *pblob;
  TBLOB *blob;
  TBLOB *nblob;
  INT16 x;
  SEARCH_STATE chunk_groups;

  set_n_ones (&current_state, array_count (seams));

  join_pieces(pieces, seams, start, end); 
  for (blob = pieces, pblob = NULL, x = 0; x < start; x++) {
    pblob = blob;
    blob = blob->next;
  }
  for (nblob = blob->next; x < end; x++)
    nblob = nblob->next;
  choices = classify_blob (pblob, blob, nblob, NULL, fx, "pieces:", White,
    this_state, best_state, pass, blob_index);

  break_pieces(blob, seams, start, end); 
#ifndef GRAPHICS_DISABLED
  if (display_segmentations > 2) {
    chunk_groups = bin_to_chunks (&current_state, array_count (seams));
    display_segmentation(pieces, chunk_groups); 
    window_wait(segm_window); 
    memfree(chunk_groups); 
  }
#endif

  return (choices);
}
Ejemplo n.º 6
0
/**
 * @name evaluate_state
 *
 * Evaluate the segmentation that is represented by this state in the
 * best first search.  Add this state to the "states_seen" list.
 */
inT16 Wordrec::evaluate_state(CHUNKS_RECORD *chunks_record,
                              SEARCH_RECORD *the_search,
                              DANGERR *fixpt,
                              BlamerBundle *blamer_bundle) {
  BLOB_CHOICE_LIST_VECTOR *char_choices;
  SEARCH_STATE chunk_groups;
  float rating_limit = the_search->best_choice->rating();
  bool keep_going = true;
  PIECES_STATE widths;

  the_search->num_states++;
  chunk_groups = bin_to_chunks(the_search->this_state,
                               the_search->num_joints);
  bin_to_pieces (the_search->this_state, the_search->num_joints, widths);
  if (wordrec_debug_level > 1) {
    log_state("Evaluating state", the_search->num_joints,
              the_search->this_state);
  }
  getDict().LogNewSegmentation(widths);

  char_choices = evaluate_chunks(chunks_record, chunk_groups, blamer_bundle);
  getDict().SetWordsegRatingAdjustFactor(-1.0f);
  bool updated_best_choice = false;
  if (char_choices != NULL && char_choices->length() > 0) {
    // Compute the segmentation cost and include the cost in word rating.
    // TODO(dsl): We should change the SEARCH_RECORD to store this cost
    // from state evaluation and avoid recomputing it here.
    prioritize_state(chunks_record, the_search);
    getDict().SetWordsegRatingAdjustFactor(the_search->segcost_bias);
    updated_best_choice =
      getDict().permute_characters(*char_choices,
                                   the_search->best_choice,
                                   the_search->raw_choice);
    bool replaced = false;
    if (updated_best_choice) {
      if (getDict().AcceptableChoice(char_choices, the_search->best_choice,
                                     NULL, ASSOCIATOR_CALLER, &replaced)) {
        keep_going = false;
      }
      CopyCharChoices(*char_choices, the_search->best_char_choices);
    }
  }
  getDict().SetWordsegRatingAdjustFactor(-1.0f);

#ifndef GRAPHICS_DISABLED
  if (wordrec_display_segmentations) {
    display_segmentation (chunks_record->chunks, chunk_groups);
    if (wordrec_display_segmentations > 1)
      window_wait(segm_window);
  }
#endif

  if (rating_limit != the_search->best_choice->rating()) {
    ASSERT_HOST(updated_best_choice);
    the_search->before_best = the_search->num_states;
    the_search->best_state->part1 = the_search->this_state->part1;
    the_search->best_state->part2 = the_search->this_state->part2;
    replace_char_widths(chunks_record, chunk_groups);
  } else {
    ASSERT_HOST(!updated_best_choice);
    if (char_choices != NULL) fixpt->clear();
  }

  if (char_choices != NULL) delete char_choices;
  memfree(chunk_groups);

  return (keep_going);
}