/********************************************************************** * File: paragraphs_internal.h * Description: Paragraph Detection internal data structures. * Author: David Eger * Created: 11 March 2011 * * (C) Copyright 2011, Google Inc. ** Licensed under the Apache License, Version 2.0 (the "License"); ** you may not use this file except in compliance with the License. ** You may obtain a copy of the License at ** http://www.apache.org/licenses/LICENSE-2.0 ** Unless required by applicable law or agreed to in writing, software ** distributed under the License is distributed on an "AS IS" BASIS, ** WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. ** See the License for the specific language governing permissions and ** limitations under the License. * **********************************************************************/ #ifndef TESSERACT_CCMAIN_PARAGRAPHS_INTERNAL_H_ #define TESSERACT_CCMAIN_PARAGRAPHS_INTERNAL_H_ #include "paragraphs.h" #ifdef _MSC_VER #include #else #include "strings.h" #endif // NO CODE OUTSIDE OF paragraphs.cpp AND TESTS SHOULD NEED TO ACCESS // DATA STRUCTURES OR FUNCTIONS IN THIS FILE. class WERD_CHOICE; namespace tesseract { // Return whether the given word is likely to be a list item start word. bool AsciiLikelyListItem(const STRING &word); // Return the first Unicode Codepoint from werd[pos]. int UnicodeFor(const UNICHARSET *u, const WERD_CHOICE *werd, int pos); // Set right word attributes given either a unicharset and werd or a utf8 // string. void RightWordAttributes(const UNICHARSET *unicharset, const WERD_CHOICE *werd, const STRING &utf8, bool *is_list, bool *starts_idea, bool *ends_idea); // Set left word attributes given either a unicharset and werd or a utf8 string. void LeftWordAttributes(const UNICHARSET *unicharset, const WERD_CHOICE *werd, const STRING &utf8, bool *is_list, bool *starts_idea, bool *ends_idea); enum LineType { LT_START = 'S', // First line of a paragraph. LT_BODY = 'C', // Continuation line of a paragraph. LT_UNKNOWN = 'U', // No clues. LT_MULTIPLE = 'M', // Matches for both LT_START and LT_BODY. }; // The first paragraph in a page of body text is often un-indented. // This is a typographic convention which is common to indicate either that: // (1) The paragraph is the continuation of a previous paragraph, or // (2) The paragraph is the first paragraph in a chapter. // // I refer to such paragraphs as "crown"s, and the output of the paragraph // detection algorithm attempts to give them the same paragraph model as // the rest of the body text. // // Nonetheless, while building hypotheses, it is useful to mark the lines // of crown paragraphs temporarily as crowns, either aligned left or right. extern const ParagraphModel *kCrownLeft; extern const ParagraphModel *kCrownRight; inline bool StrongModel(const ParagraphModel *model) { return model != nullptr && model != kCrownLeft && model != kCrownRight; } struct LineHypothesis { LineHypothesis() : ty(LT_UNKNOWN), model(nullptr) {} LineHypothesis(LineType line_type, const ParagraphModel *m) : ty(line_type), model(m) {} LineHypothesis(const LineHypothesis &other) : ty(other.ty), model(other.model) {} bool operator==(const LineHypothesis &other) const { return ty == other.ty && model == other.model; } LineType ty; const ParagraphModel *model; }; class ParagraphTheory; // Forward Declaration typedef GenericVectorEqEq SetOfModels; // Row Scratch Registers are data generated by the paragraph detection // algorithm based on a RowInfo input. class RowScratchRegisters { public: // We presume row will outlive us. void Init(const RowInfo &row); LineType GetLineType() const; LineType GetLineType(const ParagraphModel *model) const; // Mark this as a start line type, sans model. This is useful for the // initial marking of probable body lines or paragraph start lines. void SetStartLine(); // Mark this as a body line type, sans model. This is useful for the // initial marking of probably body lines or paragraph start lines. void SetBodyLine(); // Record that this row fits as a paragraph start line in the given model, void AddStartLine(const ParagraphModel *model); // Record that this row fits as a paragraph body line in the given model, void AddBodyLine(const ParagraphModel *model); // Clear all hypotheses about this line. void SetUnknown() { hypotheses_.truncate(0); } // Append all hypotheses of strong models that match this row as a start. void StartHypotheses(SetOfModels *models) const; // Append all hypotheses of strong models matching this row. void StrongHypotheses(SetOfModels *models) const; // Append all hypotheses for this row. void NonNullHypotheses(SetOfModels *models) const; // Discard any hypotheses whose model is not in the given list. void DiscardNonMatchingHypotheses(const SetOfModels &models); // If we have only one hypothesis and that is that this line is a paragraph // start line of a certain model, return that model. Else return nullptr. const ParagraphModel *UniqueStartHypothesis() const; // If we have only one hypothesis and that is that this line is a paragraph // body line of a certain model, return that model. Else return nullptr. const ParagraphModel *UniqueBodyHypothesis() const; // Return the indentation for the side opposite of the aligned side. int OffsideIndent(tesseract::ParagraphJustification just) const { switch (just) { case tesseract::JUSTIFICATION_RIGHT: return lindent_; case tesseract::JUSTIFICATION_LEFT: return rindent_; default: return lindent_ > rindent_ ? lindent_ : rindent_; } } // Return the indentation for the side the text is aligned to. int AlignsideIndent(tesseract::ParagraphJustification just) const { switch (just) { case tesseract::JUSTIFICATION_RIGHT: return rindent_; case tesseract::JUSTIFICATION_LEFT: return lindent_; default: return lindent_ > rindent_ ? lindent_ : rindent_; } } // Append header fields to a vector of row headings. static void AppendDebugHeaderFields(GenericVector *header); // Append data for this row to a vector of debug strings. void AppendDebugInfo(const ParagraphTheory &theory, GenericVector *dbg) const; const RowInfo *ri_; // These four constants form a horizontal box model for the white space // on the edges of each line. At each point in the algorithm, the following // shall hold: // ri_->pix_ldistance = lmargin_ + lindent_ // ri_->pix_rdistance = rindent_ + rmargin_ int lmargin_; int lindent_; int rindent_; int rmargin_; private: // Hypotheses of either LT_START or LT_BODY GenericVectorEqEq hypotheses_; }; // A collection of convenience functions for wrapping the set of // Paragraph Models we believe correctly model the paragraphs in the image. class ParagraphTheory { public: // We presume models will outlive us, and that models will take ownership // of any ParagraphModel *'s we add. explicit ParagraphTheory(GenericVector *models) : models_(models) {} GenericVector &models() { return *models_; } const GenericVector &models() const { return *models_; } // Return an existing model if one that is Comparable() can be found. // Else, allocate a new copy of model to save and return a pointer to it. const ParagraphModel *AddModel(const ParagraphModel &model); // Discard any models we've made that are not in the list of used models. void DiscardUnusedModels(const SetOfModels &used_models); // Return the set of all non-centered models. void NonCenteredModels(SetOfModels *models); // If any of the non-centered paragraph models we know about fit // rows[start, end), return it. Else nullptr. const ParagraphModel *Fits(const GenericVector *rows, int start, int end) const; int IndexOf(const ParagraphModel *model) const; private: GenericVector *models_; GenericVectorEqEq models_we_added_; }; bool ValidFirstLine(const GenericVector *rows, int row, const ParagraphModel *model); bool ValidBodyLine(const GenericVector *rows, int row, const ParagraphModel *model); bool CrownCompatible(const GenericVector *rows, int a, int b, const ParagraphModel *model); // A class for smearing Paragraph Model hypotheses to surrounding rows. // The idea here is that StrongEvidenceClassify first marks only exceedingly // obvious start and body rows and constructs models of them. Thereafter, // we may have left over unmarked lines (mostly end-of-paragraph lines) which // were too short to have much confidence about, but which fit the models we've // constructed perfectly and which we ought to mark. This class is used to // "smear" our models over the text. class ParagraphModelSmearer { public: ParagraphModelSmearer(GenericVector *rows, int row_start, int row_end, ParagraphTheory *theory); // Smear forward paragraph models from existing row markings to subsequent // text lines if they fit, and mark any thereafter still unmodeled rows // with any model in the theory that fits them. void Smear(); private: // Record in open_models_ for rows [start_row, end_row) the list of models // currently open at each row. // A model is still open in a row if some previous row has said model as a // start hypothesis, and all rows since (including this row) would fit as // either a body or start line in that model. void CalculateOpenModels(int row_start, int row_end); SetOfModels &OpenModels(int row) { return open_models_[row - row_start_ + 1]; } ParagraphTheory *theory_; GenericVector *rows_; int row_start_; int row_end_; // open_models_ corresponds to rows[start_row_ - 1, end_row_] // // open_models_: Contains models which there was an active (open) paragraph // as of the previous line and for which the left and right // indents admit the possibility that this text line continues // to fit the same model. // TODO(eger): Think about whether we can get rid of "Open" models and just // use the current hypotheses on RowScratchRegisters. GenericVector open_models_; }; // Clear all hypotheses about lines [start, end) and reset the margins to the // percentile (0..100) value of the left and right row edges for this run of // rows. void RecomputeMarginsAndClearHypotheses( GenericVector *rows, int start, int end, int percentile); // Return the median inter-word space in rows[row_start, row_end). int InterwordSpace(const GenericVector &rows, int row_start, int row_end); // Return whether the first word on the after line can fit in the space at // the end of the before line (knowing which way the text is aligned and read). bool FirstWordWouldHaveFit(const RowScratchRegisters &before, const RowScratchRegisters &after, tesseract::ParagraphJustification justification); // Return whether the first word on the after line can fit in the space at // the end of the before line (not knowing the text alignment). bool FirstWordWouldHaveFit(const RowScratchRegisters &before, const RowScratchRegisters &after); // Do rows[start, end) form a single instance of the given paragraph model? bool RowsFitModel(const GenericVector *rows, int start, int end, const ParagraphModel *model); // Do the text and geometry of two rows support a paragraph break between them? bool LikelyParagraphStart(const RowScratchRegisters &before, const RowScratchRegisters &after, tesseract::ParagraphJustification j); // Given a set of row_owners pointing to PARAs or nullptr (no paragraph known), // normalize each row_owner to point to an actual PARA, and output the // paragraphs in order onto paragraphs. void CanonicalizeDetectionResults( GenericVector *row_owners, PARA_LIST *paragraphs); } // namespace #endif // TESSERACT_CCMAIN_PARAGRAPHS_INTERNAL_H_