Merge pull request #3835 from Yulv-git/typos1

Fix some typos.
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zdenop 2022-06-05 14:46:17 +02:00 committed by GitHub
commit d1912d7010
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19 changed files with 22 additions and 22 deletions

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@ -181,7 +181,7 @@ class TESS_API ChoiceIterator {
public:
// Construction is from a LTRResultIterator that points to the symbol of
// interest. The ChoiceIterator allows a one-shot iteration over the
// choices for this symbol and after that is is useless.
// choices for this symbol and after that it is useless.
explicit ChoiceIterator(const LTRResultIterator &result_it);
~ChoiceIterator();

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@ -225,7 +225,7 @@ bool PageIterator::IsAtFinalElement(PageIteratorLevel level,
return true; // Already at the end!
}
// The result is true if we step forward by element and find we are
// at the the end of the page or at beginning of *all* levels in:
// at the end of the page or at beginning of *all* levels in:
// [level, element).
// When there is more than one level difference between element and level,
// we could for instance move forward one symbol and still be at the first

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@ -616,7 +616,7 @@ bool ResultIterator::IsAtFinalElement(PageIteratorLevel level, PageIteratorLevel
return true; // Already at the end!
}
// The result is true if we step forward by element and find we are
// at the the end of the page or at beginning of *all* levels in:
// at the end of the page or at beginning of *all* levels in:
// [level, element).
// When there is more than one level difference between element and level,
// we could for instance move forward one symbol and still be at the first

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@ -769,7 +769,7 @@ public:
#ifndef GRAPHICS_DISABLED
// Draw the noise blobs from all lists in red.
void plot_noise_blobs(ScrollView *to_win);
// Draw the blobs on on the various lists in the block in different colors.
// Draw the blobs on the various lists in the block in different colors.
void plot_graded_blobs(ScrollView *to_win);
#endif

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@ -871,7 +871,7 @@ void C_OUTLINE::ComputeBinaryOffsets() {
increment_step(s, 1, &head_pos, dir_counts, pos_totals);
}
for (int s = 0; s < stepcount; pos += step(s++)) {
// At step s, s in in the middle of [s-2, s+2].
// At step s, s in the middle of [s-2, s+2].
increment_step(s + 2, 1, &head_pos, dir_counts, pos_totals);
int dir_index = chain_code(s);
ICOORD step_vec = step(s);

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@ -180,7 +180,7 @@ static void ComputeRunlengthImage(const TBOX &box,
++y;
}
}
// Now set the image pixels the the MIN of the x and y runlengths.
// Now set the image pixels the MIN of the x and y runlengths.
for (int iy = 0; iy < height; ++iy) {
int x = 0;
for (auto x_coord : x_coords[iy]) {

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@ -347,7 +347,7 @@ void BLOCK_RECT_IT::forward() { // next rectangle
/**********************************************************************
* BLOCK_LINE_IT::get_line
*
* Get the the start and width of a line in the block.
* Get the start and width of a line in the block.
**********************************************************************/
TDimension BLOCK_LINE_IT::get_line( // get a line

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@ -116,7 +116,7 @@ public:
// Comparator function for sorting AmbigSpec_LISTs. The lists will
// be sorted by their wrong_ngram arrays. Example of wrong_ngram vectors
// in a a sorted AmbigSpec_LIST: [9 1 3], [9 3 4], [9 8], [9, 8 1].
// in a sorted AmbigSpec_LIST: [9 1 3], [9 3 4], [9 8], [9, 8 1].
static int compare_ambig_specs(const void *spec1, const void *spec2) {
const AmbigSpec *s1 = *static_cast<const AmbigSpec *const *>(spec1);
const AmbigSpec *s2 = *static_cast<const AmbigSpec *const *>(spec2);

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@ -48,7 +48,7 @@ TessdataManager::TessdataManager(FileReader reader)
SetVersionString(TESSERACT_VERSION_STR);
}
// Lazily loads from the the given filename. Won't actually read the file
// Lazily loads from the given filename. Won't actually read the file
// until it needs it.
void TessdataManager::LoadFileLater(const char *data_file_name) {
Clear();

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@ -138,7 +138,7 @@ public:
return is_loaded_;
}
// Lazily loads from the the given filename. Won't actually read the file
// Lazily loads from the given filename. Won't actually read the file
// until it needs it.
void LoadFileLater(const char *data_file_name);
/**

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@ -66,7 +66,7 @@ class FCOORD;
/* The first 3 dimensions of the CLASS_PRUNER_STRUCT are the
* 3 axes of the quantized feature space.
* The position of the the bits recorded for each class in the
* The position of the bits recorded for each class in the
* 4th dimension is determined by using CPrunerWordIndexFor(c),
* where c is the corresponding class id. */
struct CLASS_PRUNER_STRUCT {

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@ -333,7 +333,7 @@ protected:
// Finds the edge with the given direction, word_end and unichar_id
// in the node indicated by node_ref. Fills in the pointer to the
// EDGE_RECORD and the index of the edge with the the values
// EDGE_RECORD and the index of the edge with the values
// corresponding to the edge found. Returns true if an edge was found.
bool edge_char_of(NODE_REF node_ref, NODE_REF next_node, int direction, bool word_end,
UNICHAR_ID unichar_id, EDGE_RECORD **edge_ptr, EDGE_INDEX *edge_index) const;

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@ -87,7 +87,7 @@ public:
// 6. Destruction. Use of a single column finder for multiple images does not
// make sense.
// Throughout these steps, the ColPartitions are owned by part_grid_, which
// means that that it must be kept correct. Exception: big_parts_ owns its
// means that it must be kept correct. Exception: big_parts_ owns its
// own ColPartitions.
// The BLOBNBOXes are owned by the input TO_BLOCK for the whole time, except
// for a phase in FindBlocks before TransformToBlocks, when they become

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@ -1378,7 +1378,7 @@ bool ColPartition::HasGoodBaseline() {
} else {
// Horizontal lines use the bottom as the baseline.
TBOX box(it.data()->bounding_box());
// Use the bottom-left of the first box, the the bottom-right of the last,
// Use the bottom-left of the first box, the bottom-right of the last,
// and the middle of all others.
ICOORD first_pt(box.left(), box.bottom());
linepoints.Add(first_pt);
@ -1623,7 +1623,7 @@ static TO_BLOCK *MoveBlobsToBlock(bool vertical_text, int line_spacing,
ColPartition_LIST *used_parts) {
// Make a matching TO_BLOCK and put all the BLOBNBOXes from the parts in it.
// Move all the parts to a done list as they are no longer needed, except
// that have have to continue to exist until the part grid is deleted.
// that have to continue to exist until the part grid is deleted.
// Compute the median blob size as we go, as the block needs to know.
TBOX block_box(block->pdblk.bounding_box());
STATS sizes(0, std::max(block_box.width(), block_box.height()) - 1);
@ -1780,7 +1780,7 @@ TO_BLOCK *ColPartition::MakeVerticalTextBlock(const ICOORD &bleft,
}
// Makes a TO_ROW matching this and moves all the blobs to it, transferring
// ownership to to returned TO_ROW.
// ownership to returned TO_ROW.
TO_ROW *ColPartition::MakeToRow() {
BLOBNBOX_C_IT blob_it(&boxes_);
TO_ROW *row = nullptr;

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@ -671,7 +671,7 @@ public:
ColPartition_LIST *used_parts);
// Makes a TO_ROW matching this and moves all the blobs to it, transferring
// ownership to to returned TO_ROW.
// ownership to returned TO_ROW.
TO_ROW *MakeToRow();
// Returns a copy of everything except the list of boxes. The resulting

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@ -199,7 +199,7 @@ int ShiroRekhaSplitter::GetXheightForCC(Box *cc_bbox) {
int baseline = static_cast<int>(row->base_line(box_middle) + 0.5);
TBOX test_box(box_middle - row->x_height() / 2, baseline, box_middle + row->x_height() / 2,
static_cast<int>(baseline + row->x_height()));
// Compute overlap. If it is is a major overlap, this is the right row.
// Compute overlap. If it is a major overlap, this is the right row.
if (bbox.major_overlap(test_box)) {
return row->x_height();
}

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@ -787,7 +787,7 @@ void Textord::improve_row_threshold(TO_ROW *row, STATS *all_gap_stats) {
/*
Look for the first region of all 0's in the histogram which is wider than
max(3, (sp - kn) / 3) and starts between kn and sp. If found, and current
threshold is not within it, move the threshold so that is is just inside it.
threshold is not within it, move the threshold so that is just inside it.
*/
reqd_zero_width = static_cast<int16_t>(floor((sp - kn) / 3 + 0.5));
if (reqd_zero_width < 3) {

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@ -466,7 +466,7 @@ protected:
// significant learning. learning_iteration_ <= training_iteration_.
// learning_iteration_ is used to measure rate of learning progress.
int learning_iteration_;
// Saved value of sample_iteration_ before looking for the the next sample.
// Saved value of sample_iteration_ before looking for the next sample.
int prev_sample_iteration_;
// How often to include a PERFECT training sample in backprop.
// A PERFECT training sample is used if the current

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@ -236,7 +236,7 @@ protected:
// Constructs WERD_CHOICE by recording unichar_ids of the BLOB_CHOICEs
// on the path represented by the given BLOB_CHOICE and language model
// state entries (lmse, dse). The path is re-constructed by following
// the parent pointers in the the lang model state entries). If the
// the parent pointers in the lang model state entries). If the
// constructed WERD_CHOICE is better than the best/raw choice recorded
// in the best_choice_bundle, this function updates the corresponding
// fields and sets best_choice_bunldle->updated to true.
@ -367,7 +367,7 @@ protected:
// Set to true if a choice representing correct segmentation was explored.
bool correct_segmentation_explored_ = false;
// Params models containing weights for for computing ViterbiStateEntry costs.
// Params models containing weights for computing ViterbiStateEntry costs.
ParamsModel params_model_;
};