// Helper to compute edge offsets for all the blobs on the list.
// See coutln.h for an explanation of edge offsets.
void BLOBNBOX::ComputeEdgeOffsets(Pix* thresholds, Pix* grey,
BLOBNBOX_LIST* blobs) {
int grey_height = 0;
int thr_height = 0;
int scale_factor = 1;
if (thresholds != NULL && grey != NULL) {
grey_height = pixGetHeight(grey);
thr_height = pixGetHeight(thresholds);
scale_factor =
IntCastRounded(static_cast<double>(grey_height) / thr_height);
}
BLOBNBOX_IT blob_it(blobs);
for (blob_it.mark_cycle_pt(); !blob_it.cycled_list(); blob_it.forward()) {
BLOBNBOX* blob = blob_it.data();
if (blob->cblob() != NULL) {
// Get the threshold that applies to this blob.
l_uint32 threshold = 128;
if (thresholds != NULL && grey != NULL) {
const TBOX& box = blob->cblob()->bounding_box();
// Transform the coordinates if required.
TPOINT pt((box.left() + box.right()) / 2,
(box.top() + box.bottom()) / 2);
pixGetPixel(thresholds, pt.x / scale_factor,
thr_height - 1 - pt.y / scale_factor, &threshold);
}
blob->cblob()->ComputeEdgeOffsets(threshold, grey);
}
}
}
// Reorganize the blob lists with a different definition of small, medium
// and large, compared to the original definition.
// Height is still the primary filter key, but medium width blobs of small
// height become small, and very wide blobs of small height stay noise, along
// with small dot-shaped blobs.
void StrokeWidth::ReFilterBlobs(TO_BLOCK* block) {
int min_height =
static_cast<int>(textord_strokewidth_minsize * block->line_size + 0.5);
int max_height =
static_cast<int>(textord_strokewidth_maxsize * block->line_size + 0.5);
BLOBNBOX_LIST noise_list;
BLOBNBOX_LIST small_list;
BLOBNBOX_LIST medium_list;
BLOBNBOX_LIST large_list;
SizeFilterBlobs(min_height, max_height, &block->blobs,
&noise_list, &small_list, &medium_list, &large_list);
SizeFilterBlobs(min_height, max_height, &block->large_blobs,
&noise_list, &small_list, &medium_list, &large_list);
SizeFilterBlobs(min_height, max_height, &block->small_blobs,
&noise_list, &small_list, &medium_list, &large_list);
SizeFilterBlobs(min_height, max_height, &block->noise_blobs,
&noise_list, &small_list, &medium_list, &large_list);
BLOBNBOX_IT blob_it(&block->blobs);
blob_it.add_list_after(&medium_list);
blob_it.set_to_list(&block->large_blobs);
blob_it.add_list_after(&large_list);
blob_it.set_to_list(&block->small_blobs);
blob_it.add_list_after(&small_list);
blob_it.set_to_list(&block->noise_blobs);
blob_it.add_list_after(&noise_list);
}
// Converts the Boxa array to a list of C_BLOB, getting rid of severely
// overlapping outlines and those that are children of a bigger one.
// The output is a list of C_BLOBs that are owned by the list.
// The C_OUTLINEs in the C_BLOBs contain no outline data - just empty
// bounding boxes. The Boxa is consumed and destroyed.
void LineFinder::ConvertBoxaToBlobs(int image_width, int image_height,
Boxa** boxes, C_BLOB_LIST* blobs) {
#ifdef HAVE_LIBLEPT
C_OUTLINE_LIST outlines;
C_OUTLINE_IT ol_it = &outlines;
// Iterate the boxes to convert to outlines.
int nboxes = boxaGetCount(*boxes);
for (int i = 0; i < nboxes; ++i) {
l_int32 x, y, width, height;
boxaGetBoxGeometry(*boxes, i, &x, &y, &width, &height);
// Make a C_OUTLINE from the leptonica box. This is a bit of a hack,
// as there is no outline, just a bounding box, but with some very
// small changes to coutln.cpp, it works nicely.
ICOORD top_left(x, image_height - y);
ICOORD bot_right(x + width, image_height - (y + height));
CRACKEDGE startpt;
startpt.pos = top_left;
C_OUTLINE* outline = new C_OUTLINE(&startpt, top_left, bot_right, 0);
ol_it.add_after_then_move(outline);
}
// Use outlines_to_blobs to convert the outlines to blobs and find
// overlapping and contained objects. The output list of blobs in the block
// has all the bad ones filtered out and deleted.
BLOCK block;
ICOORD page_tl(0, 0);
ICOORD page_br(image_width, image_height);
outlines_to_blobs(&block, page_tl, page_br, &outlines);
// Transfer the created blobs to the output list.
C_BLOB_IT blob_it(blobs);
blob_it.add_list_after(block.blob_list());
// The boxes aren't needed any more.
boxaDestroy(boxes);
#endif
}
// Remove outlines that are a tiny fraction in either width or height
// of the word height.
void Textord::clean_small_noise_from_words(ROW *row) {
WERD_IT word_it(row->word_list());
for (word_it.mark_cycle_pt(); !word_it.cycled_list(); word_it.forward()) {
WERD* word = word_it.data();
int min_size = static_cast<int>(
textord_noise_hfract * word->bounding_box().height() + 0.5);
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();
C_OUTLINE_IT out_it(blob->out_list());
for (out_it.mark_cycle_pt(); !out_it.cycled_list(); out_it.forward()) {
C_OUTLINE* outline = out_it.data();
outline->RemoveSmallRecursive(min_size, &out_it);
}
if (blob->out_list()->empty()) {
delete blob_it.extract();
}
}
if (word->cblob_list()->empty()) {
if (!word_it.at_last()) {
// The next word is no longer a fuzzy non space if it was before,
// since the word before is about to be deleted.
WERD* next_word = word_it.data_relative(1);
if (next_word->flag(W_FUZZY_NON)) {
next_word->set_flag(W_FUZZY_NON, false);
}
}
delete word_it.extract();
}
}
}
PAGE_RES_IT* make_pseudo_word(PAGE_RES* page_res, const TBOX& selection_box) {
PAGE_RES_IT pr_it(page_res);
C_BLOB_LIST new_blobs; // list of gathered blobs
C_BLOB_IT new_blob_it = &new_blobs; // iterator
for (WERD_RES* word_res = pr_it.word(); word_res != NULL;
word_res = pr_it.forward()) {
WERD* word = word_res->word;
if (word->bounding_box().overlap(selection_box)) {
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();
if (blob->bounding_box().overlap(selection_box)) {
new_blob_it.add_after_then_move(C_BLOB::deep_copy(blob));
}
}
if (!new_blobs.empty()) {
WERD* pseudo_word = new WERD(&new_blobs, 1, NULL);
word_res = pr_it.InsertSimpleCloneWord(*word_res, pseudo_word);
PAGE_RES_IT* it = new PAGE_RES_IT(page_res);
while (it->word() != word_res && it->word() != NULL) it->forward();
ASSERT_HOST(it->word() == word_res);
return it;
}
}
}
return NULL;
}
// Computes the noise_density_ by summing the number of elements in a
// neighbourhood of each grid cell.
void StrokeWidth::ComputeNoiseDensity(TO_BLOCK* block, TabFind* line_grid) {
// Run a preliminary strokewidth neighbour detection on the medium blobs.
line_grid->InsertBlobList(true, true, false, &block->blobs, false, this);
BLOBNBOX_IT blob_it(&block->blobs);
for (blob_it.mark_cycle_pt(); !blob_it.cycled_list(); blob_it.forward()) {
SetNeighbours(false, blob_it.data());
}
// Remove blobs with a good strokewidth neighbour from the grid.
for (blob_it.mark_cycle_pt(); !blob_it.cycled_list(); blob_it.forward()) {
BLOBNBOX* blob = blob_it.data();
if (blob->GoodTextBlob() > 0)
RemoveBBox(blob);
blob->ClearNeighbours();
}
// Insert the smaller blobs into the grid.
line_grid->InsertBlobList(true, true, false, &block->small_blobs,
false, this);
line_grid->InsertBlobList(true, true, false, &block->noise_blobs,
false, this);
if (noise_density_ != NULL)
delete noise_density_;
IntGrid* cell_counts = CountCellElements();
noise_density_ = cell_counts->NeighbourhoodSum();
delete cell_counts;
// Clear the grid as we don't want the small stuff hanging around in it.
Clear();
}
// Inserts a list of blobs into the projection.
// Rotation is a multiple of 90 degrees to get from blob coords to
// nontext_map coords, nontext_map_box is the bounds of the nontext_map.
// Blobs are spread horizontally or vertically according to their internal
// flags, but the spreading is truncated by set pixels in the nontext_map
// and also by the horizontal rule line limits on the blobs.
void TextlineProjection::ProjectBlobs(BLOBNBOX_LIST* blobs,
const FCOORD& rotation,
const TBOX& nontext_map_box,
Pix* nontext_map) {
BLOBNBOX_IT blob_it(blobs);
for (blob_it.mark_cycle_pt(); !blob_it.cycled_list(); blob_it.forward()) {
BLOBNBOX* blob = blob_it.data();
TBOX bbox = blob->bounding_box();
ICOORD middle((bbox.left() + bbox.right()) / 2,
(bbox.bottom() + bbox.top()) / 2);
bool spreading_horizontally = PadBlobBox(blob, &bbox);
// Rotate to match the nontext_map.
bbox.rotate(rotation);
middle.rotate(rotation);
if (rotation.x() == 0.0f)
spreading_horizontally = !spreading_horizontally;
// Clip to the image before applying the increments.
bbox &= nontext_map_box; // This is in-place box intersection.
// Check for image pixels before spreading.
TruncateBoxToMissNonText(middle.x(), middle.y(), spreading_horizontally,
nontext_map, &bbox);
if (bbox.area() > 0) {
IncrementRectangle8Bit(bbox);
}
}
}
// Inserts all the blobs from the given list, with x and y spreading,
// without removing from the source list, so ownership remains with the
// source list.
void BlobGrid::InsertBlobList(BLOBNBOX_LIST * blobs) {
BLOBNBOX_IT blob_it(blobs);
for (blob_it.mark_cycle_pt(); !blob_it.cycled_list(); blob_it.forward()) {
BLOBNBOX *blob = blob_it.data();
if (!blob->joined_to_prev())
InsertBBox(true, true, blob);
}
}
BOOL8 suspect_em(WERD_RES *word, inT16 index) {
PBLOB_LIST *blobs = word->outword->blob_list ();
PBLOB_IT blob_it(blobs);
inT16 j;
for (j = 0; j < index; j++)
blob_it.forward ();
return (blob_it.data ()->out_list ()->length () != 1);
}
// Helper to delete all the deletable blobs on the list.
void BLOBNBOX::DeleteNoiseBlobs(BLOBNBOX_LIST* blobs) {
BLOBNBOX_IT blob_it(blobs);
for (blob_it.mark_cycle_pt(); !blob_it.cycled_list(); blob_it.forward()) {
BLOBNBOX* blob = blob_it.data();
if (blob->DeletableNoise()) {
delete blob->cblob();
delete blob_it.extract();
}
}
}
// Finds horizontal line objects in the given pix.
// Uses the given resolution to determine size thresholds instead of any
// that may be present in the pix.
// The output vectors are owned by the list and Frozen (cannot refit) by
// having no boxes, as there is no need to refit or merge separator lines.
void LineFinder::FindHorizontalLines(int resolution, Pix* pix,
TabVector_LIST* vectors) {
#ifdef HAVE_LIBLEPT
Pix* line_pix;
Boxa* boxes = GetHLineBoxes(resolution, pix, &line_pix);
C_BLOB_LIST line_cblobs;
int width = pixGetWidth(pix);
int height = pixGetHeight(pix);
ConvertBoxaToBlobs(height, width, &boxes, &line_cblobs);
// Make the BLOBNBOXes from the C_BLOBs.
BLOBNBOX_LIST line_bblobs;
C_BLOB_IT blob_it(&line_cblobs);
BLOBNBOX_IT bbox_it(&line_bblobs);
for (blob_it.mark_cycle_pt(); !blob_it.cycled_list(); blob_it.forward()) {
C_BLOB* cblob = blob_it.data();
BLOBNBOX* bblob = new BLOBNBOX(cblob);
bbox_it.add_to_end(bblob);
}
ICOORD bleft(0, 0);
ICOORD tright(height, width);
int vertical_x, vertical_y;
FindLineVectors(bleft, tright, &line_bblobs, &vertical_x, &vertical_y,
vectors);
if (!vectors->empty()) {
// Some lines were found, so erase the unused blobs from the line image
// and then subtract the line image from the source.
bbox_it.move_to_first();
for (bbox_it.mark_cycle_pt(); !bbox_it.cycled_list(); bbox_it.forward()) {
BLOBNBOX* blob = bbox_it.data();
if (blob->left_tab_type() == TT_UNCONFIRMED) {
const TBOX& box = blob->bounding_box();
// Coords are in tess format so filp x and y and then covert
// to leptonica by height -y.
Box* pixbox = boxCreate(box.bottom(), height - box.right(),
box.height(), box.width());
pixClearInRect(line_pix, pixbox);
boxDestroy(&pixbox);
}
}
pixDilateBrick(line_pix, line_pix, 3, 1);
pixSubtract(pix, pix, line_pix);
if (textord_tabfind_show_vlines)
pixWrite("hlinesclean.png", line_pix, IFF_PNG);
ICOORD vertical;
vertical.set_with_shrink(vertical_x, vertical_y);
TabVector::MergeSimilarTabVectors(vertical, vectors, NULL);
// Iterate the vectors to flip them.
TabVector_IT h_it(vectors);
for (h_it.mark_cycle_pt(); !h_it.cycled_list(); h_it.forward()) {
h_it.data()->XYFlip();
}
}
pixDestroy(&line_pix);
#endif
}
// Tests each blob in the list to see if it is certain non-text using 2
// conditions:
// 1. blob overlaps a cell with high value in noise_density_ (previously set
// by ComputeNoiseDensity).
// OR 2. The blob overlaps more than max_blob_overlaps in *this grid. This
// condition is disabled with max_blob_overlaps == -1.
// If it does, the blob is declared non-text, and is used to mark up the
// nontext_mask. Such blobs are fully deleted, and non-noise blobs have their
// neighbours reset, as they may now point to deleted data.
// WARNING: The blobs list blobs may be in the *this grid, but they are
// not removed. If any deleted blobs might be in *this, then this must be
// Clear()ed immediately after MarkAndDeleteNonTextBlobs is called.
// If the win is not NULL, deleted blobs are drawn on it in red, and kept
// blobs are drawn on it in ok_color.
void CCNonTextDetect::MarkAndDeleteNonTextBlobs(BLOBNBOX_LIST* blobs,
int max_blob_overlaps,
ScrollView* win,
ScrollView::Color ok_color,
Pix* nontext_mask) {
int imageheight = tright().y() - bleft().x();
BLOBNBOX_IT blob_it(blobs);
BLOBNBOX_LIST dead_blobs;
BLOBNBOX_IT dead_it(&dead_blobs);
for (blob_it.mark_cycle_pt(); !blob_it.cycled_list(); blob_it.forward()) {
BLOBNBOX* blob = blob_it.data();
TBOX box = blob->bounding_box();
if (!noise_density_->RectMostlyOverThreshold(box, max_noise_count_) &&
(max_blob_overlaps < 0 ||
!BlobOverlapsTooMuch(blob, max_blob_overlaps))) {
blob->ClearNeighbours();
#ifndef GRAPHICS_DISABLED
if (win != NULL)
blob->plot(win, ok_color, ok_color);
#endif // GRAPHICS_DISABLED
} else {
if (noise_density_->AnyZeroInRect(box)) {
// There is a danger that the bounding box may overlap real text, so
// we need to render the outline.
Pix* blob_pix = blob->cblob()->render_outline();
pixRasterop(nontext_mask, box.left(), imageheight - box.top(),
box.width(), box.height(), PIX_SRC | PIX_DST,
blob_pix, 0, 0);
pixDestroy(&blob_pix);
} else {
if (box.area() < gridsize() * gridsize()) {
// It is a really bad idea to make lots of small components in the
// photo mask, so try to join it to a bigger area by expanding the
// box in a way that does not touch any zero noise density cell.
box = AttemptBoxExpansion(box, *noise_density_, gridsize());
}
// All overlapped cells are non-zero, so just mark the rectangle.
pixRasterop(nontext_mask, box.left(), imageheight - box.top(),
box.width(), box.height(), PIX_SET, NULL, 0, 0);
}
#ifndef GRAPHICS_DISABLED
if (win != NULL)
blob->plot(win, ScrollView::RED, ScrollView::RED);
#endif // GRAPHICS_DISABLED
// It is safe to delete the cblob now, as it isn't used by the grid
// or BlobOverlapsTooMuch, and the BLOBNBOXes will go away with the
// dead_blobs list.
// TODO(rays) delete the delete when the BLOBNBOX destructor deletes
// the cblob.
delete blob->cblob();
dead_it.add_to_end(blob_it.extract());
}
}
}
// Adds the selected outlines to the indcated real blobs, and puts the rest
// back in rej_cblobs where they came from. Where the target_blobs entry is
// nullptr, a run of wanted outlines is put into a single new blob.
// Ownership of the outlines is transferred back to the word. (Hence
// GenericVector and not PointerVector.)
// Returns true if any new blob was added to the start of the word, which
// suggests that it might need joining to the word before it, and likewise
// sets make_next_word_fuzzy true if any new blob was added to the end.
bool WERD::AddSelectedOutlines(const GenericVector<bool>& wanted,
const GenericVector<C_BLOB*>& target_blobs,
const GenericVector<C_OUTLINE*>& outlines,
bool* make_next_word_fuzzy) {
bool outline_added_to_start = false;
if (make_next_word_fuzzy != nullptr) *make_next_word_fuzzy = false;
C_BLOB_IT rej_it(&rej_cblobs);
for (int i = 0; i < outlines.size(); ++i) {
C_OUTLINE* outline = outlines[i];
if (outline == nullptr) continue; // Already used it.
if (wanted[i]) {
C_BLOB* target_blob = target_blobs[i];
TBOX noise_box = outline->bounding_box();
if (target_blob == nullptr) {
target_blob = new C_BLOB(outline);
// Need to find the insertion point.
C_BLOB_IT blob_it(&cblobs);
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.left() > noise_box.left()) {
if (blob_it.at_first() && !flag(W_FUZZY_SP) && !flag(W_FUZZY_NON)) {
// We might want to join this word to its predecessor.
outline_added_to_start = true;
}
blob_it.add_before_stay_put(target_blob);
break;
}
}
if (blob_it.cycled_list()) {
blob_it.add_to_end(target_blob);
if (make_next_word_fuzzy != nullptr) *make_next_word_fuzzy = true;
}
// Add all consecutive wanted, but null-blob outlines to same blob.
C_OUTLINE_IT ol_it(target_blob->out_list());
while (i + 1 < outlines.size() && wanted[i + 1] &&
target_blobs[i + 1] == nullptr) {
++i;
ol_it.add_to_end(outlines[i]);
}
} else {
// Insert outline into this blob.
C_OUTLINE_IT ol_it(target_blob->out_list());
ol_it.add_to_end(outline);
}
} else {
// Put back on noise list.
rej_it.add_to_end(new C_BLOB(outline));
}
}
return outline_added_to_start;
}
void WERD::join_on(WERD* other) {
C_BLOB_IT blob_it(&cblobs);
C_BLOB_IT src_it(&other->cblobs);
C_BLOB_IT rej_cblob_it(&rej_cblobs);
C_BLOB_IT src_rej_it(&other->rej_cblobs);
while (!src_it.empty()) {
blob_it.add_to_end(src_it.extract());
src_it.forward();
}
while (!src_rej_it.empty()) {
rej_cblob_it.add_to_end(src_rej_it.extract());
src_rej_it.forward();
}
}
// Finds vertical line objects in the given pix.
// Uses the given resolution to determine size thresholds instead of any
// that may be present in the pix.
// The output vertical_x and vertical_y contain a sum of the output vectors,
// thereby giving the mean vertical direction.
// The output vectors are owned by the list and Frozen (cannot refit) by
// having no boxes, as there is no need to refit or merge separator lines.
void LineFinder::FindVerticalLines(int resolution, Pix* pix,
int* vertical_x, int* vertical_y,
TabVector_LIST* vectors) {
#ifdef HAVE_LIBLEPT
Pix* line_pix;
Boxa* boxes = GetVLineBoxes(resolution, pix, &line_pix);
C_BLOB_LIST line_cblobs;
int width = pixGetWidth(pix);
int height = pixGetHeight(pix);
ConvertBoxaToBlobs(width, height, &boxes, &line_cblobs);
// Make the BLOBNBOXes from the C_BLOBs.
BLOBNBOX_LIST line_bblobs;
C_BLOB_IT blob_it(&line_cblobs);
BLOBNBOX_IT bbox_it(&line_bblobs);
for (blob_it.mark_cycle_pt(); !blob_it.cycled_list(); blob_it.forward()) {
C_BLOB* cblob = blob_it.data();
BLOBNBOX* bblob = new BLOBNBOX(cblob);
bbox_it.add_to_end(bblob);
}
ICOORD bleft(0, 0);
ICOORD tright(width, height);
FindLineVectors(bleft, tright, &line_bblobs, vertical_x, vertical_y, vectors);
if (!vectors->empty()) {
// Some lines were found, so erase the unused blobs from the line image
// and then subtract the line image from the source.
bbox_it.move_to_first();
for (bbox_it.mark_cycle_pt(); !bbox_it.cycled_list(); bbox_it.forward()) {
BLOBNBOX* blob = bbox_it.data();
if (blob->left_tab_type() == TT_UNCONFIRMED) {
const TBOX& box = blob->bounding_box();
Box* pixbox = boxCreate(box.left(), height - box.top(),
box.width(), box.height());
pixClearInRect(line_pix, pixbox);
boxDestroy(&pixbox);
}
}
pixDilateBrick(line_pix, line_pix, 1, 3);
pixSubtract(pix, pix, line_pix);
if (textord_tabfind_show_vlines)
pixWrite("vlinesclean.png", line_pix, IFF_PNG);
ICOORD vertical;
vertical.set_with_shrink(*vertical_x, *vertical_y);
TabVector::MergeSimilarTabVectors(vertical, vectors, NULL);
}
pixDestroy(&line_pix);
#endif
}
// Sets up displacement_modes_ with the top few modes of the perpendicular
// distance of each blob from the given direction vector, after rounding.
void BaselineRow::SetupBlobDisplacements(const FCOORD& direction) {
// Set of perpendicular displacements of the blob bottoms from the required
// baseline direction.
GenericVector<double> perp_blob_dists;
displacement_modes_.truncate(0);
// Gather the skew-corrected position of every blob.
double min_dist = MAX_FLOAT32;
double max_dist = -MAX_FLOAT32;
BLOBNBOX_IT blob_it(blobs_);
bool debug = false;
for (blob_it.mark_cycle_pt(); !blob_it.cycled_list(); blob_it.forward()) {
BLOBNBOX* blob = blob_it.data();
const TBOX& box = blob->bounding_box();
#ifdef kDebugYCoord
if (box.bottom() < kDebugYCoord && box.top() > kDebugYCoord) debug = true;
#endif
FCOORD blob_pos((box.left() + box.right()) / 2.0f,
blob->baseline_position());
double offset = direction * blob_pos;
perp_blob_dists.push_back(offset);
if (debug) {
tprintf("Displacement %g for blob at:", offset);
box.print();
}
UpdateRange(offset, &min_dist, &max_dist);
}
// Set up a histogram using disp_quant_factor_ as the bucket size.
STATS dist_stats(IntCastRounded(min_dist / disp_quant_factor_),
IntCastRounded(max_dist / disp_quant_factor_) + 1);
for (int i = 0; i < perp_blob_dists.size(); ++i) {
dist_stats.add(IntCastRounded(perp_blob_dists[i] / disp_quant_factor_), 1);
}
GenericVector<KDPairInc<float, int> > scaled_modes;
dist_stats.top_n_modes(kMaxDisplacementsModes, &scaled_modes);
if (debug) {
for (int i = 0; i < scaled_modes.size(); ++i) {
tprintf("Top mode = %g * %d\n",
scaled_modes[i].key * disp_quant_factor_, scaled_modes[i].data);
}
}
for (int i = 0; i < scaled_modes.size(); ++i)
displacement_modes_.push_back(disp_quant_factor_ * scaled_modes[i].key);
}
// Removes noise from the word by moving small outlines to the rej_cblobs
// list, based on the size_threshold.
void WERD::CleanNoise(float size_threshold) {
C_BLOB_IT blob_it(&cblobs);
C_BLOB_IT rej_it(&rej_cblobs);
for (blob_it.mark_cycle_pt(); !blob_it.cycled_list(); blob_it.forward()) {
C_BLOB* blob = blob_it.data();
C_OUTLINE_IT ol_it(blob->out_list());
for (ol_it.mark_cycle_pt(); !ol_it.cycled_list(); ol_it.forward()) {
C_OUTLINE* outline = ol_it.data();
TBOX ol_box = outline->bounding_box();
int ol_size =
ol_box.width() > ol_box.height() ? ol_box.width() : ol_box.height();
if (ol_size < size_threshold) {
// This outline is too small. Move it to a separate blob in the
// reject blobs list.
C_BLOB* rej_blob = new C_BLOB(ol_it.extract());
rej_it.add_after_then_move(rej_blob);
}
}
if (blob->out_list()->empty()) delete blob_it.extract();
}
}
BOOL8 suspect_fullstop(WERD_RES *word, inT16 i) {
float aspect_ratio;
PBLOB_LIST *blobs = word->outword->blob_list ();
PBLOB_IT blob_it(blobs);
inT16 j;
TBOX box;
inT16 width;
inT16 height;
for (j = 0; j < i; j++)
blob_it.forward ();
box = blob_it.data ()->bounding_box ();
width = box.width ();
height = box.height ();
aspect_ratio = ((width > height) ? ((float) width) / height :
((float) height) / width);
return (aspect_ratio > tessed_fullstop_aspect_ratio);
}
// Fixes the block so it obeys all the rules:
// Must have at least one ROW.
// Must have at least one WERD.
// WERDs contain a fake blob.
void Textord::cleanup_nontext_block(BLOCK* block) {
// Non-text blocks must contain at least one row.
ROW_IT row_it(block->row_list());
if (row_it.empty()) {
const TBOX& box = block->pdblk.bounding_box();
float height = box.height();
int32_t xstarts[2] = {box.left(), box.right()};
double coeffs[3] = {0.0, 0.0, static_cast<double>(box.bottom())};
ROW* row = new ROW(1, xstarts, coeffs, height / 2.0f, height / 4.0f,
height / 4.0f, 0, 1);
row_it.add_after_then_move(row);
}
// Each row must contain at least one word.
for (row_it.mark_cycle_pt(); !row_it.cycled_list(); row_it.forward()) {
ROW* row = row_it.data();
WERD_IT w_it(row->word_list());
if (w_it.empty()) {
// Make a fake blob to put in the word.
TBOX box = block->row_list()->singleton() ? block->pdblk.bounding_box()
: row->bounding_box();
C_BLOB* blob = C_BLOB::FakeBlob(box);
C_BLOB_LIST blobs;
C_BLOB_IT blob_it(&blobs);
blob_it.add_after_then_move(blob);
WERD* word = new WERD(&blobs, 0, nullptr);
w_it.add_after_then_move(word);
}
// Each word must contain a fake blob.
for (w_it.mark_cycle_pt(); !w_it.cycled_list(); w_it.forward()) {
WERD* word = w_it.data();
// Just assert that this is true, as it would be useful to find
// out why it isn't.
ASSERT_HOST(!word->cblob_list()->empty());
}
row->recalc_bounding_box();
}
}
// Reorganize the blob lists with a different definition of small, medium
// and large, compared to the original definition.
// Height is still the primary filter key, but medium width blobs of small
// height become small, and very wide blobs of small height stay noise, along
// with small dot-shaped blobs.
void TO_BLOCK::ReSetAndReFilterBlobs() {
int min_height = IntCastRounded(kMinMediumSizeRatio * line_size);
int max_height = IntCastRounded(kMaxMediumSizeRatio * line_size);
BLOBNBOX_LIST noise_list;
BLOBNBOX_LIST small_list;
BLOBNBOX_LIST medium_list;
BLOBNBOX_LIST large_list;
SizeFilterBlobs(min_height, max_height, &blobs,
&noise_list, &small_list, &medium_list, &large_list);
SizeFilterBlobs(min_height, max_height, &large_blobs,
&noise_list, &small_list, &medium_list, &large_list);
SizeFilterBlobs(min_height, max_height, &small_blobs,
&noise_list, &small_list, &medium_list, &large_list);
SizeFilterBlobs(min_height, max_height, &noise_blobs,
&noise_list, &small_list, &medium_list, &large_list);
BLOBNBOX_IT blob_it(&blobs);
blob_it.add_list_after(&medium_list);
blob_it.set_to_list(&large_blobs);
blob_it.add_list_after(&large_list);
blob_it.set_to_list(&small_blobs);
blob_it.add_list_after(&small_list);
blob_it.set_to_list(&noise_blobs);
blob_it.add_list_after(&noise_list);
}
// Helper to call CleanNeighbours on all blobs on the list.
void BLOBNBOX::CleanNeighbours(BLOBNBOX_LIST* blobs) {
BLOBNBOX_IT blob_it(blobs);
for (blob_it.mark_cycle_pt(); !blob_it.cycled_list(); blob_it.forward()) {
blob_it.data()->CleanNeighbours();
}
}
// Fits a straight baseline to the points. Returns true if it had enough
// points to be reasonably sure of the fitted baseline.
// If use_box_bottoms is false, baselines positions are formed by
// considering the outlines of the blobs.
bool BaselineRow::FitBaseline(bool use_box_bottoms) {
// Deterministic fitting is used wherever possible.
fitter_.Clear();
// Linear least squares is a backup if the DetLineFit produces a bad line.
LLSQ llsq;
BLOBNBOX_IT blob_it(blobs_);
for (blob_it.mark_cycle_pt(); !blob_it.cycled_list(); blob_it.forward()) {
BLOBNBOX* blob = blob_it.data();
if (!use_box_bottoms) blob->EstimateBaselinePosition();
const TBOX& box = blob->bounding_box();
int x_middle = (box.left() + box.right()) / 2;
#ifdef kDebugYCoord
if (box.bottom() < kDebugYCoord && box.top() > kDebugYCoord) {
tprintf("Box bottom = %d, baseline pos=%d for box at:",
box.bottom(), blob->baseline_position());
box.print();
}
#endif
fitter_.Add(ICOORD(x_middle, blob->baseline_position()), box.width() / 2);
llsq.add(x_middle, blob->baseline_position());
}
// Fit the line.
ICOORD pt1, pt2;
baseline_error_ = fitter_.Fit(&pt1, &pt2);
baseline_pt1_ = pt1;
baseline_pt2_ = pt2;
if (baseline_error_ > max_baseline_error_ &&
fitter_.SufficientPointsForIndependentFit()) {
// The fit was bad but there were plenty of points, so try skipping
// the first and last few, and use the new line if it dramatically improves
// the error of fit.
double error = fitter_.Fit(kNumSkipPoints, kNumSkipPoints, &pt1, &pt2);
if (error < baseline_error_ / 2.0) {
baseline_error_ = error;
baseline_pt1_ = pt1;
baseline_pt2_ = pt2;
}
}
int debug = 0;
#ifdef kDebugYCoord
Print();
debug = bounding_box_.bottom() < kDebugYCoord &&
bounding_box_.top() > kDebugYCoord
? 3 : 2;
#endif
// Now we obtained a direction from that fit, see if we can improve the
// fit using the same direction and some other start point.
FCOORD direction(pt2 - pt1);
double target_offset = direction * pt1;
good_baseline_ = false;
FitConstrainedIfBetter(debug, direction, 0.0, target_offset);
// Wild lines can be produced because DetLineFit allows vertical lines, but
// vertical text has been rotated so angles over pi/4 should be disallowed.
// Near vertical lines can still be produced by vertically aligned components
// on very short lines.
double angle = BaselineAngle();
if (fabs(angle) > M_PI * 0.25) {
// Use the llsq fit as a backup.
baseline_pt1_ = llsq.mean_point();
baseline_pt2_ = baseline_pt1_ + FCOORD(1.0f, llsq.m());
// TODO(rays) get rid of this when m and c are no longer used.
double m = llsq.m();
double c = llsq.c(m);
baseline_error_ = llsq.rms(m, c);
good_baseline_ = false;
}
return good_baseline_;
}
/// 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;
}
// Places a copy of blobs that are near a word (after applying rotation to the
// blob) in the most appropriate word, unless there is doubt, in which case a
// blob can end up in two words. Source blobs are not touched.
void Textord::TransferDiacriticsToWords(BLOBNBOX_LIST* diacritic_blobs,
const FCOORD& rotation,
WordGrid* word_grid) {
WordSearch ws(word_grid);
BLOBNBOX_IT b_it(diacritic_blobs);
// Apply rotation to each blob before finding the nearest words. The rotation
// allows us to only consider above/below placement and not left/right on
// vertical text, because all text is horizontal here.
for (b_it.mark_cycle_pt(); !b_it.cycled_list(); b_it.forward()) {
BLOBNBOX* blobnbox = b_it.data();
TBOX blob_box = blobnbox->bounding_box();
blob_box.rotate(rotation);
ws.StartRectSearch(blob_box);
// Above/below refer to word position relative to diacritic. Since some
// scripts eg Kannada/Telugu habitually put diacritics below words, and
// others eg Thai/Vietnamese/Latin put most diacritics above words, try
// for both if there isn't much in it.
WordWithBox* best_above_word = nullptr;
WordWithBox* best_below_word = nullptr;
int best_above_distance = 0;
int best_below_distance = 0;
for (WordWithBox* word = ws.NextRectSearch(); word != nullptr;
word = ws.NextRectSearch()) {
if (word->word()->flag(W_REP_CHAR)) continue;
TBOX word_box = word->true_bounding_box();
int x_distance = blob_box.x_gap(word_box);
int y_distance = blob_box.y_gap(word_box);
if (x_distance > 0) {
// Arbitrarily divide x-distance by 2 if there is a major y overlap,
// and the word is to the left of the diacritic. If the
// diacritic is a dropped broken character between two words, this will
// help send all the pieces to a single word, instead of splitting them
// over the 2 words.
if (word_box.major_y_overlap(blob_box) &&
blob_box.left() > word_box.right()) {
x_distance /= 2;
}
y_distance += x_distance;
}
if (word_box.y_middle() > blob_box.y_middle() &&
(best_above_word == nullptr || y_distance < best_above_distance)) {
best_above_word = word;
best_above_distance = y_distance;
}
if (word_box.y_middle() <= blob_box.y_middle() &&
(best_below_word == nullptr || y_distance < best_below_distance)) {
best_below_word = word;
best_below_distance = y_distance;
}
}
bool above_good =
best_above_word != nullptr &&
(best_below_word == nullptr ||
best_above_distance < best_below_distance + blob_box.height());
bool below_good =
best_below_word != nullptr && best_below_word != best_above_word &&
(best_above_word == nullptr ||
best_below_distance < best_above_distance + blob_box.height());
if (below_good) {
C_BLOB* copied_blob = C_BLOB::deep_copy(blobnbox->cblob());
copied_blob->rotate(rotation);
// Put the blob into the word's reject blobs list.
C_BLOB_IT blob_it(best_below_word->RejBlobs());
blob_it.add_to_end(copied_blob);
}
if (above_good) {
C_BLOB* copied_blob = C_BLOB::deep_copy(blobnbox->cblob());
copied_blob->rotate(rotation);
// Put the blob into the word's reject blobs list.
C_BLOB_IT blob_it(best_above_word->RejBlobs());
blob_it.add_to_end(copied_blob);
}
}
}
void collect_ems_for_adaption(WERD_RES *word,
CHAR_SAMPLES_LIST *char_clusters,
CHAR_SAMPLE_LIST *chars_waiting) {
PBLOB_LIST *blobs = word->outword->blob_list ();
PBLOB_IT blob_it(blobs);
inT16 i;
CHAR_SAMPLE *sample;
PIXROW_LIST *pixrow_list;
PIXROW_IT pixrow_it;
IMAGELINE *imlines; // lines of the image
TBOX pix_box; // box of imlines
// extent
WERD copy_outword; // copy to denorm
PBLOB_IT copy_blob_it;
OUTLINE_IT copy_outline_it;
inT32 resolution = page_image.get_res ();
if (tessedit_reject_ems || tessedit_reject_suspect_ems)
return; // Do nothing
if (word->word->bounding_box ().height () > resolution / 3)
return;
if (tessedit_demo_adaption)
// Make sure not set
tessedit_display_mm.set_value (FALSE);
if (word_adaptable (word, tessedit_em_adaption_mode)
&& word->reject_map.reject_count () == 0
&& (strchr (word->best_choice->string ().string (), 'm') != NULL
|| (tessedit_process_rns
&& strstr (word->best_choice->string ().string (),
"rn") != NULL))) {
if (tessedit_process_rns
&& strstr (word->best_choice->string ().string (), "rn") != NULL) {
copy_outword = *(word->outword);
copy_blob_it.set_to_list (copy_outword.blob_list ());
i = 0;
while (word->best_choice->string ()[i] != '\0') {
if (word->best_choice->string ()[i] == 'r'
&& word->best_choice->string ()[i + 1] == 'n') {
copy_outline_it.set_to_list (copy_blob_it.data ()->
out_list ());
copy_outline_it.add_list_after (copy_blob_it.
data_relative (1)->
out_list ());
copy_blob_it.forward ();
delete (copy_blob_it.extract ());
i++;
}
copy_blob_it.forward ();
i++;
}
}
else
copy_outword = *(word->outword);
copy_outword.baseline_denormalise (&word->denorm);
char_clip_word(©_outword, page_image, pixrow_list, imlines, pix_box);
pixrow_it.set_to_list (pixrow_list);
pixrow_it.move_to_first ();
blob_it.move_to_first ();
for (i = 0;
word->best_choice->string ()[i] != '\0';
i++, pixrow_it.forward (), blob_it.forward ()) {
if (word->best_choice->string ()[i] == 'm'
|| (word->best_choice->string ()[i] == 'r'
&& word->best_choice->string ()[i + 1] == 'n')) {
#ifndef SECURE_NAMES
if (tessedit_cluster_debug)
tprintf ("Sample %c for adaption found in %s, index %d\n",
word->best_choice->string ()[i],
word->best_choice->string ().string (), i);
#endif
if (tessedit_matrix_match) {
sample = clip_sample (pixrow_it.data (),
imlines,
pix_box,
copy_outword.flag (W_INVERSE),
word->best_choice->string ()[i]);
if (sample == NULL) { //Clip failed
#ifndef SECURE_NAMES
tprintf ("Unable to clip sample from %s, index %d\n",
word->best_choice->string ().string (), i);
#endif
if (word->best_choice->string ()[i] == 'r')
i++;
continue;
}
}
else
sample = new CHAR_SAMPLE (blob_it.data (),
&word->denorm,
word->best_choice->string ()[i]);
cluster_sample(sample, char_clusters, chars_waiting);
if (word->best_choice->string ()[i] == 'r')
i++; // Skip next character
}
}
delete[]imlines; // Free array of imlines
delete pixrow_list;
}
}
// Creates and returns a Pix with the same resolution as the original
// in which 1 (black) pixels represent likely non text (photo, line drawing)
// areas of the page, deleting from the blob_block the blobs that were
// determined to be non-text.
// The photo_map is used to bias the decision towards non-text, rather than
// supplying definite decision.
// The blob_block is the usual result of connected component analysis,
// holding the detected blobs.
// The returned Pix should be PixDestroyed after use.
Pix* CCNonTextDetect::ComputeNonTextMask(bool debug, Pix* photo_map,
TO_BLOCK* blob_block) {
// Insert the smallest blobs into the grid.
InsertBlobList(&blob_block->small_blobs);
InsertBlobList(&blob_block->noise_blobs);
// Add the medium blobs that don't have a good strokewidth neighbour.
// Those that do go into good_grid as an antidote to spreading beyond the
// real reaches of a noise region.
BlobGrid good_grid(gridsize(), bleft(), tright());
BLOBNBOX_IT blob_it(&blob_block->blobs);
for (blob_it.mark_cycle_pt(); !blob_it.cycled_list(); blob_it.forward()) {
BLOBNBOX* blob = blob_it.data();
double perimeter_area_ratio = blob->cblob()->perimeter() / 4.0;
perimeter_area_ratio *= perimeter_area_ratio / blob->enclosed_area();
if (blob->GoodTextBlob() == 0 || perimeter_area_ratio < kMinGoodTextPARatio)
InsertBBox(true, true, blob);
else
good_grid.InsertBBox(true, true, blob);
}
noise_density_ = ComputeNoiseDensity(debug, photo_map, &good_grid);
good_grid.Clear(); // Not needed any more.
Pix* pix = noise_density_->ThresholdToPix(max_noise_count_);
if (debug) {
pixWrite("junknoisemask.png", pix, IFF_PNG);
}
ScrollView* win = NULL;
#ifndef GRAPHICS_DISABLED
if (debug) {
win = MakeWindow(0, 400, "Photo Mask Blobs");
}
#endif // GRAPHICS_DISABLED
// Large and medium blobs are not text if they overlap with "a lot" of small
// blobs.
MarkAndDeleteNonTextBlobs(&blob_block->large_blobs,
kMaxLargeOverlapsWithSmall,
win, ScrollView::DARK_GREEN, pix);
MarkAndDeleteNonTextBlobs(&blob_block->blobs, kMaxMediumOverlapsWithSmall,
win, ScrollView::WHITE, pix);
// Clear the grid of small blobs and insert the medium blobs.
Clear();
InsertBlobList(&blob_block->blobs);
MarkAndDeleteNonTextBlobs(&blob_block->large_blobs,
kMaxLargeOverlapsWithMedium,
win, ScrollView::DARK_GREEN, pix);
// Clear again before we start deleting the blobs in the grid.
Clear();
MarkAndDeleteNonTextBlobs(&blob_block->noise_blobs, -1,
win, ScrollView::CORAL, pix);
MarkAndDeleteNonTextBlobs(&blob_block->small_blobs, -1,
win, ScrollView::GOLDENROD, pix);
MarkAndDeleteNonTextBlobs(&blob_block->blobs, -1,
win, ScrollView::WHITE, pix);
if (debug) {
#ifndef GRAPHICS_DISABLED
win->Update();
#endif // GRAPHICS_DISABLED
pixWrite("junkccphotomask.png", pix, IFF_PNG);
#ifndef GRAPHICS_DISABLED
delete win->AwaitEvent(SVET_DESTROY);
delete win;
#endif // GRAPHICS_DISABLED
}
return pix;
}
void collect_characters_for_adaption(WERD_RES *word,
CHAR_SAMPLES_LIST *char_clusters,
CHAR_SAMPLE_LIST *chars_waiting) {
PBLOB_LIST *blobs = word->outword->blob_list ();
PBLOB_IT blob_it(blobs);
inT16 i;
CHAR_SAMPLE *sample;
PIXROW_LIST *pixrow_list;
PIXROW_IT pixrow_it;
IMAGELINE *imlines; // lines of the image
TBOX pix_box; // box of imlines
// extent
WERD copy_outword; // copy to denorm
inT32 resolution = page_image.get_res ();
if (word->word->bounding_box ().height () > resolution / 3)
return;
if (tessedit_demo_adaption)
// Make sure not set
tessedit_display_mm.set_value (FALSE);
if ((word_adaptable (word, tessedit_cluster_adaption_mode)
&& word->reject_map.reject_count () == 0) || tessedit_mm_use_rejmap) {
if (tessedit_test_cluster_input && !tessedit_mm_use_rejmap)
return; // Reject map set to acceptable
/* Collect information about good matches */
copy_outword = *(word->outword);
copy_outword.baseline_denormalise (&word->denorm);
char_clip_word(©_outword, page_image, pixrow_list, imlines, pix_box);
pixrow_it.set_to_list (pixrow_list);
pixrow_it.move_to_first ();
blob_it.move_to_first ();
for (i = 0;
word->best_choice->string ()[i] != '\0';
i++, pixrow_it.forward (), blob_it.forward ()) {
if (!(tessedit_mm_use_non_adaption_set
&& STRING (tessedit_non_adaption_set).contains (word->
best_choice->
string ()[i]))
|| (tessedit_mm_use_rejmap && word->reject_map[i].accepted ())) {
#ifndef SECURE_NAMES
if (tessedit_cluster_debug)
tprintf ("Sample %c for adaption found in %s, index %d\n",
word->best_choice->string ()[i],
word->best_choice->string ().string (), i);
#endif
sample = clip_sample (pixrow_it.data (),
imlines,
pix_box,
copy_outword.flag (W_INVERSE),
word->best_choice->string ()[i]);
if (sample == NULL) { //Clip failed
#ifndef SECURE_NAMES
tprintf ("Unable to clip sample from %s, index %d\n",
word->best_choice->string ().string (), i);
#endif
continue;
}
cluster_sample(sample, char_clusters, chars_waiting);
}
}
delete[]imlines; // Free array of imlines
delete pixrow_list;
}
else if (tessedit_test_cluster_input && !tessedit_mm_use_rejmap)
// Set word to all rejects
word->reject_map.rej_word_tess_failure ();
}
void adapt_to_good_samples(WERD_RES *word,
CHAR_SAMPLES_LIST *char_clusters,
CHAR_SAMPLE_LIST *chars_waiting) {
PBLOB_LIST *blobs = word->outword->blob_list ();
PBLOB_IT blob_it(blobs);
inT16 i;
CHAR_SAMPLE *sample;
CHAR_SAMPLES_IT c_it = char_clusters;
CHAR_SAMPLE_IT cw_it = chars_waiting;
float score;
float best_score;
char best_char;
CHAR_SAMPLES *best_cluster;
PIXROW_LIST *pixrow_list;
PIXROW_IT pixrow_it;
IMAGELINE *imlines; // lines of the image
TBOX pix_box; // box of imlines
// extent
WERD copy_outword; // copy to denorm
TBOX b_box;
PBLOB_IT copy_blob_it;
PIXROW *pixrow = NULL;
static inT32 word_number = 0;
#ifndef GRAPHICS_DISABLED
ScrollView* demo_win = NULL;
#endif
inT32 resolution = page_image.get_res ();
word_number++;
if (tessedit_test_cluster_input)
return;
if (word->word->bounding_box ().height () > resolution / 3)
return;
if (char_clusters->length () == 0) {
#ifndef SECURE_NAMES
if (tessedit_cluster_debug)
tprintf ("No clusters to use for adaption\n");
#endif
return;
}
if (!cw_it.empty ()) {
complete_clustering(char_clusters, chars_waiting);
print_em_stats(char_clusters, chars_waiting);
}
if ((!word_adaptable (word, tessedit_cluster_adaption_mode)
&& word->reject_map.reject_count () != 0) || tessedit_mm_use_rejmap) {
if (tessedit_cluster_debug) {
tprintf ("\nChecking: \"%s\" MAP ",
word->best_choice->string ().string ());
word->reject_map.print (debug_fp);
tprintf ("\n");
}
copy_outword = *(word->outword);
copy_outword.baseline_denormalise (&word->denorm);
copy_blob_it.set_to_list (copy_outword.blob_list ());
char_clip_word(©_outword, page_image, pixrow_list, imlines, pix_box);
pixrow_it.set_to_list (pixrow_list);
pixrow_it.move_to_first ();
// For debugging only
b_box = copy_outword.bounding_box ();
pixrow = pixrow_it.data ();
blob_it.move_to_first ();
copy_blob_it.move_to_first ();
for (i = 0;
word->best_choice->string ()[i] != '\0';
i++, pixrow_it.forward (), blob_it.forward (),
copy_blob_it.forward ()) {
if (word->reject_map[i].recoverable ()
|| (tessedit_mm_all_rejects && word->reject_map[i].rejected ())) {
TBOX copy_box = copy_blob_it.data ()->bounding_box ();
if (tessedit_cluster_debug)
tprintf ("Sample %c to check found in %s, index %d\n",
word->best_choice->string ()[i],
word->best_choice->string ().string (), i);
if (tessedit_demo_adaption)
tprintf ("Sample %c to check found in %s (%d), index %d\n",
word->best_choice->string ()[i],
word->best_choice->string ().string (),
word_number, i);
sample = clip_sample (pixrow_it.data (),
imlines,
pix_box,
copy_outword.flag (W_INVERSE),
word->best_choice->string ()[i]);
if (sample == NULL) { //Clip failed
tprintf ("Unable to clip sample from %s, index %d\n",
word->best_choice->string ().string (), i);
#ifndef SECURE_NAMES
if (tessedit_cluster_debug)
tprintf ("Sample rejected (no sample)\n");
#endif
word->reject_map[i].setrej_mm_reject ();
continue;
}
best_score = MAX_INT32;
best_char = '\0';
best_cluster = NULL;
for (c_it.mark_cycle_pt ();
!c_it.cycled_list (); c_it.forward ()) {
if (c_it.data ()->character () != '\0') {
score = c_it.data ()->match_score (sample);
if (score < best_score) {
best_cluster = c_it.data ();
best_score = score;
best_char = c_it.data ()->character ();
}
}
}
if (best_score > tessedit_cluster_t1) {
#ifndef SECURE_NAMES
if (tessedit_cluster_debug)
tprintf ("Sample rejected (score %f)\n", best_score);
if (tessedit_demo_adaption)
tprintf ("Sample rejected (score %f)\n", best_score);
#endif
word->reject_map[i].setrej_mm_reject ();
}
else {
if (word->best_choice->string ()[i] == best_char) {
#ifndef SECURE_NAMES
if (tessedit_cluster_debug)
tprintf ("Sample accepted (score %f)\n", best_score);
if (tessedit_demo_adaption)
tprintf ("Sample accepted (score %f)\n", best_score);
#endif
if (tessedit_test_adaption)
word->reject_map[i].setrej_minimal_rej_accept ();
else
word->reject_map[i].setrej_mm_accept ();
}
else {
#ifndef SECURE_NAMES
if (tessedit_cluster_debug)
tprintf ("Sample rejected (char %c, score %f)\n",
best_char, best_score);
if (tessedit_demo_adaption)
tprintf ("Sample rejected (char %c, score %f)\n",
best_char, best_score);
#endif
word->reject_map[i].setrej_mm_reject ();
}
}
if (tessedit_demo_adaption) {
if (strcmp (imagebasename.string (),
tessedit_demo_file.string ()) != 0
|| word_number == tessedit_demo_word1
|| word_number == tessedit_demo_word2) {
#ifndef GRAPHICS_DISABLED
demo_win =
display_clip_image(©_outword,
page_image,
pixrow_list,
pix_box);
#endif
demo_word = word_number;
best_cluster->match_score (sample);
demo_word = 0;
}
}
}
}
delete[]imlines; // Free array of imlines
delete pixrow_list;
if (tessedit_cluster_debug) {
tprintf ("\nFinal: \"%s\" MAP ",
word->best_choice->string ().string ());
word->reject_map.print (debug_fp);
tprintf ("\n");
}
}
}
