void fixspace_dbg(WERD_RES *word) {
TBOX box = word->word->bounding_box ();
BOOL8 show_map_detail = FALSE;
inT16 i;
box.print ();
#ifndef SECURE_NAMES
tprintf (" \"%s\" ", word->best_choice->string ().string ());
tprintf ("Blob count: %d (word); %d/%d (outword)\n",
word->word->gblob_list ()->length (),
word->outword->gblob_list ()->length (),
word->outword->rej_blob_list ()->length ());
word->reject_map.print (debug_fp);
tprintf ("\n");
if (show_map_detail) {
tprintf ("\"%s\"\n", word->best_choice->string ().string ());
for (i = 0; word->best_choice->string ()[i] != '\0'; i++) {
tprintf ("**** \"%c\" ****\n", word->best_choice->string ()[i]);
word->reject_map[i].full_print (debug_fp);
}
}
tprintf ("Tess Accepted: %s\n", word->tess_accepted ? "TRUE" : "FALSE");
tprintf ("Done flag: %s\n\n", word->done ? "TRUE" : "FALSE");
#endif
}
// Internal version of EvaluateBox returns the unclipped gradients as well
// as the result of EvaluateBox.
// hgrad1 and hgrad2 are the gradients for the horizontal textline.
int TextlineProjection::EvaluateBoxInternal(const TBOX& box,
const DENORM* denorm, bool debug,
int* hgrad1, int* hgrad2,
int* vgrad1, int* vgrad2) const {
int top_gradient = BestMeanGradientInRow(denorm, box.left(), box.right(),
box.top(), true);
int bottom_gradient = -BestMeanGradientInRow(denorm, box.left(), box.right(),
box.bottom(), false);
int left_gradient = BestMeanGradientInColumn(denorm, box.left(), box.bottom(),
box.top(), true);
int right_gradient = -BestMeanGradientInColumn(denorm, box.right(),
box.bottom(), box.top(),
false);
int top_clipped = MAX(top_gradient, 0);
int bottom_clipped = MAX(bottom_gradient, 0);
int left_clipped = MAX(left_gradient, 0);
int right_clipped = MAX(right_gradient, 0);
if (debug) {
tprintf("Gradients: top = %d, bottom = %d, left= %d, right= %d for box:",
top_gradient, bottom_gradient, left_gradient, right_gradient);
box.print();
}
int result = MAX(top_clipped, bottom_clipped) -
MAX(left_clipped, right_clipped);
if (hgrad1 != NULL && hgrad2 != NULL) {
*hgrad1 = top_gradient;
*hgrad2 = bottom_gradient;
}
if (vgrad1 != NULL && vgrad2 != NULL) {
*vgrad1 = left_gradient;
*vgrad2 = right_gradient;
}
return result;
}
// Find a set of blobs that are aligned in the given vertical
// direction with the given blob. Returns a list of aligned
// blobs and the number in the list.
// For other parameters see FindAlignedBlob below.
int AlignedBlob::AlignTabs(const AlignedBlobParams& params,
bool top_to_bottom, BLOBNBOX* bbox,
BLOBNBOX_CLIST* good_points, int* end_y) {
int ptcount = 0;
BLOBNBOX_C_IT it(good_points);
TBOX box = bbox->bounding_box();
bool debug = WithinTestRegion(2, box.left(), box.bottom());
if (debug) {
tprintf("Starting alignment run at blob:");
box.print();
}
int x_start = params.right_tab ? box.right() : box.left();
while (bbox != nullptr) {
// Add the blob to the list if the appropriate side is a tab candidate,
// or if we are working on a ragged tab.
TabType type = params.right_tab ? bbox->right_tab_type()
: bbox->left_tab_type();
if (((type != TT_NONE && type != TT_MAYBE_RAGGED) || params.ragged) &&
(it.empty() || it.data() != bbox)) {
if (top_to_bottom)
it.add_before_then_move(bbox);
else
it.add_after_then_move(bbox);
++ptcount;
}
// Find the next blob that is aligned with the current one.
// FindAlignedBlob guarantees that forward progress will be made in the
// top_to_bottom direction, and therefore eventually it will return nullptr,
// making this while (bbox != nullptr) loop safe.
bbox = FindAlignedBlob(params, top_to_bottom, bbox, x_start, end_y);
if (bbox != nullptr) {
box = bbox->bounding_box();
if (!params.ragged)
x_start = params.right_tab ? box.right() : box.left();
}
}
if (debug) {
tprintf("Alignment run ended with %d pts at blob:", ptcount);
box.print();
}
return ptcount;
}
/// Consume all source blobs that strongly overlap the given box,
/// putting them into a new word, with the correct_text label.
/// Fights over which box owns which blobs are settled by
/// applying the blobs to box or next_box with the least non-overlap.
/// @return false if the box was in error, which can only be caused by
/// failing to find an overlapping blob for a box.
bool Tesseract::ResegmentWordBox(BLOCK_LIST *block_list,
const TBOX& box, const TBOX& next_box,
const char* correct_text) {
if (applybox_debug > 1) {
tprintf("\nAPPLY_BOX: in ResegmentWordBox() for %s\n", correct_text);
}
WERD* new_word = NULL;
BLOCK_IT b_it(block_list);
for (b_it.mark_cycle_pt(); !b_it.cycled_list(); b_it.forward()) {
BLOCK* block = b_it.data();
if (!box.major_overlap(block->bounding_box()))
continue;
ROW_IT r_it(block->row_list());
for (r_it.mark_cycle_pt(); !r_it.cycled_list(); r_it.forward()) {
ROW* row = r_it.data();
if (!box.major_overlap(row->bounding_box()))
continue;
WERD_IT w_it(row->word_list());
for (w_it.mark_cycle_pt(); !w_it.cycled_list(); w_it.forward()) {
WERD* word = w_it.data();
if (applybox_debug > 2) {
tprintf("Checking word:");
word->bounding_box().print();
}
if (word->text() != NULL && word->text()[0] != '\0')
continue; // Ignore words that are already done.
if (!box.major_overlap(word->bounding_box()))
continue;
C_BLOB_IT blob_it(word->cblob_list());
for (blob_it.mark_cycle_pt(); !blob_it.cycled_list();
blob_it.forward()) {
C_BLOB* blob = blob_it.data();
TBOX blob_box = blob->bounding_box();
if (!blob_box.major_overlap(box))
continue;
double current_box_miss_metric = BoxMissMetric(blob_box, box);
double next_box_miss_metric = BoxMissMetric(blob_box, next_box);
if (applybox_debug > 2) {
tprintf("Checking blob:");
blob_box.print();
tprintf("Current miss metric = %g, next = %g\n",
current_box_miss_metric, next_box_miss_metric);
}
if (current_box_miss_metric > next_box_miss_metric)
continue; // Blob is a better match for next box.
if (applybox_debug > 2) {
tprintf("Blob match: blob:");
blob_box.print();
tprintf("Matches box:");
box.print();
tprintf("With next box:");
next_box.print();
}
if (new_word == NULL) {
// Make a new word with a single blob.
new_word = word->shallow_copy();
new_word->set_text(correct_text);
w_it.add_to_end(new_word);
}
C_BLOB_IT new_blob_it(new_word->cblob_list());
new_blob_it.add_to_end(blob_it.extract());
}
}
}
}
if (new_word == NULL && applybox_debug > 0) tprintf("FAIL!\n");
return new_word != NULL;
}
/// Gather consecutive blobs that match the given box into the best_state
/// and corresponding correct_text.
///
/// Fights over which box owns which blobs are settled by pre-chopping and
/// applying the blobs to box or next_box with the least non-overlap.
/// @return false if the box was in error, which can only be caused by
/// failing to find an appropriate blob for a box.
///
/// This means that occasionally, blobs may be incorrectly segmented if the
/// chopper fails to find a suitable chop point.
bool Tesseract::ResegmentCharBox(PAGE_RES* page_res, const TBOX *prev_box,
const TBOX& box, const TBOX& next_box,
const char* correct_text) {
if (applybox_debug > 1) {
tprintf("\nAPPLY_BOX: in ResegmentCharBox() for %s\n", correct_text);
}
PAGE_RES_IT page_res_it(page_res);
WERD_RES* word_res;
for (word_res = page_res_it.word(); word_res != NULL;
word_res = page_res_it.forward()) {
if (!word_res->box_word->bounding_box().major_overlap(box))
continue;
if (applybox_debug > 1) {
tprintf("Checking word box:");
word_res->box_word->bounding_box().print();
}
int word_len = word_res->box_word->length();
for (int i = 0; i < word_len; ++i) {
TBOX char_box = TBOX();
int blob_count = 0;
for (blob_count = 0; i + blob_count < word_len; ++blob_count) {
TBOX blob_box = word_res->box_word->BlobBox(i + blob_count);
if (!blob_box.major_overlap(box))
break;
if (word_res->correct_text[i + blob_count].length() > 0)
break; // Blob is claimed already.
double current_box_miss_metric = BoxMissMetric(blob_box, box);
double next_box_miss_metric = BoxMissMetric(blob_box, next_box);
if (applybox_debug > 2) {
tprintf("Checking blob:");
blob_box.print();
tprintf("Current miss metric = %g, next = %g\n",
current_box_miss_metric, next_box_miss_metric);
}
if (current_box_miss_metric > next_box_miss_metric)
break; // Blob is a better match for next box.
char_box += blob_box;
}
if (blob_count > 0) {
if (applybox_debug > 1) {
tprintf("Index [%d, %d) seem good.\n", i, i + blob_count);
}
if (!char_box.almost_equal(box, 3) &&
(box.x_gap(next_box) < -3 ||
(prev_box != NULL && prev_box->x_gap(box) < -3))) {
return false;
}
// We refine just the box_word, best_state and correct_text here.
// The rebuild_word is made in TidyUp.
// blob_count blobs are put together to match the box. Merge the
// box_word boxes, save the blob_count in the state and the text.
word_res->box_word->MergeBoxes(i, i + blob_count);
word_res->best_state[i] = blob_count;
word_res->correct_text[i] = correct_text;
if (applybox_debug > 2) {
tprintf("%d Blobs match: blob box:", blob_count);
word_res->box_word->BlobBox(i).print();
tprintf("Matches box:");
box.print();
tprintf("With next box:");
next_box.print();
}
// Eliminated best_state and correct_text entries for the consumed
// blobs.
for (int j = 1; j < blob_count; ++j) {
word_res->best_state.remove(i + 1);
word_res->correct_text.remove(i + 1);
}
// Assume that no box spans multiple source words, so we are done with
// this box.
if (applybox_debug > 1) {
tprintf("Best state = ");
for (int j = 0; j < word_res->best_state.size(); ++j) {
tprintf("%d ", word_res->best_state[j]);
}
tprintf("\n");
tprintf("Correct text = [[ ");
for (int j = 0; j < word_res->correct_text.size(); ++j) {
tprintf("%s ", word_res->correct_text[j].string());
}
tprintf("]]\n");
}
return true;
}
}
}
if (applybox_debug > 0) {
tprintf("FAIL!\n");
}
return false; // Failure.
}
