Added the option for character accumulated glyph confidences.

The parameter glyph_confidences is changed from bool to int.
An execution with value 1 outputs the hOCR file enriched with glyph confidences
for every timestep like before. An execution with value 2 outputs the timesteps
accumulated over the recognized characters.

Signed-off-by: Noah Metzger <noah.metzger@bib.uni-mannheim.de>

src/api/baseapi.cpp

@@ -1606,12 +1606,11 @@ char* TessBaseAPI::GetHOCRText(ETEXT_DESC* monitor, int page_number) {
     if (italic) hocr_str += "</em>";
     if (bold) hocr_str += "</strong>";
     // If glyph confidence is required it is added here
-    if (tesseract_->glyph_confidences && confidencemap != nullptr) {
+    if (tesseract_->glyph_confidences == 1 && confidencemap != nullptr) {
       for (size_t i = 0; i < confidencemap->size(); i++) {
         hocr_str += "\n       <span class='ocrx_cinfo'";
         AddIdTohOCR(&hocr_str, "timestep", page_id, wcnt, tcnt);
         hocr_str += ">";
-        //*
         std::vector<std::pair<const char*, float>> timestep = (*confidencemap)[i];
         for (std::pair<const char*, float> conf : timestep) {
           hocr_str += "<span class='ocr_glyph'";
@@ -1623,10 +1622,32 @@ char* TessBaseAPI::GetHOCRText(ETEXT_DESC* monitor, int page_number) {
           hocr_str += "</span>";
           gcnt++;
         }
-        //*/
         hocr_str += "</span>";
         tcnt++;
       }
+    } else if (tesseract_->glyph_confidences == 2 && confidencemap != nullptr) {
+      for (size_t i = 0; i < confidencemap->size(); i++) {
+        std::vector<std::pair<const char*, float>> timestep = (*confidencemap)[i];
+        if (timestep.size() > 0) {
+          hocr_str += "\n       <span class='ocrx_cinfo'";
+          AddIdTohOCR(&hocr_str, "alternative_glyphs", page_id, wcnt, tcnt);
+          hocr_str += " chosen='";
+          hocr_str += timestep[0].first;
+          hocr_str += "'>";
+          for (size_t j = 1; j < timestep.size(); j++) {
+            hocr_str += "<span class='ocr_glyph'";
+            AddIdTohOCR(&hocr_str, "glyph", page_id, wcnt, gcnt);
+            hocr_str.add_str_int(" title='x_confs ", int(timestep[j].second * 100));
+            hocr_str += "'";
+            hocr_str += ">";
+            hocr_str += timestep[j].first;
+            hocr_str += "</span>";
+            gcnt++;
+          }
+          hocr_str += "</span>";
+          tcnt++;
+        }
+      }
     }
     hocr_str += "</span>";
     tcnt = 1;

src/ccmain/tesseractclass.cpp

@@ -508,7 +508,7 @@ Tesseract::Tesseract()
       STRING_MEMBER(page_separator, "\f",
                     "Page separator (default is form feed control character)",
                     this->params()),
-      BOOL_MEMBER(glyph_confidences, false,
+      INT_MEMBER(glyph_confidences, 0,
                   "Allows to include glyph confidences in the hOCR output",
                    this->params()),
 

src/ccmain/tesseractclass.h

@@ -1114,7 +1114,8 @@ class Tesseract : public Wordrec {
              "Preserve multiple interword spaces");
   STRING_VAR_H(page_separator, "\f",
                "Page separator (default is form feed control character)");
-  BOOL_VAR_H(glyph_confidences, false, "Allows to include glyph confidences in the hOCR output");
+  INT_VAR_H(glyph_confidences, 0,
+            "Allows to include glyph confidences in the hOCR output");
 
   //// ambigsrecog.cpp /////////////////////////////////////////////////////////
   FILE *init_recog_training(const STRING &fname);

src/lstm/lstmrecognizer.cpp

@@ -172,7 +172,8 @@ bool LSTMRecognizer::LoadDictionary(const char* lang, TessdataManager* mgr) {
 void LSTMRecognizer::RecognizeLine(const ImageData& image_data, bool invert,
                                    bool debug, double worst_dict_cert,
                                    const TBOX& line_box,
-                                   PointerVector<WERD_RES>* words, bool glyph_confidences) {
+                                   PointerVector<WERD_RES>* words,
+                                   int glyph_confidences) {
   NetworkIO outputs;
   float scale_factor;
   NetworkIO inputs;

src/lstm/lstmrecognizer.h

@@ -185,7 +185,7 @@ class LSTMRecognizer {
   void RecognizeLine(const ImageData& image_data, bool invert, bool debug,
                      double worst_dict_cert, const TBOX& line_box,
                      PointerVector<WERD_RES>* words,
-                     bool glyph_confidences = false);
+                     int glyph_confidences = 0);
 
   // Helper computes min and mean best results in the output.
   void OutputStats(const NetworkIO& outputs,

src/lstm/recodebeam.cpp

@@ -22,6 +22,8 @@
 #include "networkio.h"
 #include "pageres.h"
 #include "unicharcompress.h"
+#include <deque>
+#include <map>
 #include <set>
 #include <vector>
 
@@ -79,7 +81,7 @@ RecodeBeamSearch::RecodeBeamSearch(const UnicharCompress& recoder,
 // Decodes the set of network outputs, storing the lattice internally.
 void RecodeBeamSearch::Decode(const NetworkIO& output, double dict_ratio,
                               double cert_offset, double worst_dict_cert,
-                              const UNICHARSET* charset, bool glyph_confidence) {
+                              const UNICHARSET* charset, int glyph_confidence) {
   beam_size_ = 0;
   int width = output.Width();
   if (glyph_confidence)
@@ -177,7 +179,7 @@ void RecodeBeamSearch::ExtractBestPathAsWords(const TBOX& line_box,
                                               float scale_factor, bool debug,
                                               const UNICHARSET* unicharset,
                                               PointerVector<WERD_RES>* words,
-                                              bool glyph_confidence) {
+                                              int glyph_confidence) {
   words->truncate(0);
   GenericVector<int> unichar_ids;
   GenericVector<float> certs;
@@ -185,6 +187,7 @@ void RecodeBeamSearch::ExtractBestPathAsWords(const TBOX& line_box,
   GenericVector<int> xcoords;
   GenericVector<const RecodeNode*> best_nodes;
   GenericVector<const RecodeNode*> second_nodes;
+  std::deque<std::pair<int,int>> best_glyphs;
   ExtractBestPaths(&best_nodes, &second_nodes);
   if (debug) {
     DebugPath(unicharset, best_nodes);
@@ -194,7 +197,22 @@ void RecodeBeamSearch::ExtractBestPathAsWords(const TBOX& line_box,
     DebugUnicharPath(unicharset, second_nodes, unichar_ids, certs, ratings,
                      xcoords);
   }
-  ExtractPathAsUnicharIds(best_nodes, &unichar_ids, &certs, &ratings, &xcoords);
+  int current_char;
+  int timestepEnd = 0;
+  //if glyph confidence is required in granularity level 2 it stores the x 
+  //Coordinates of every chosen character to match the alternative glyphs to it
+  if (glyph_confidence == 2) {
+    ExtractPathAsUnicharIds(best_nodes, &unichar_ids, &certs, &ratings,
+                            &xcoords, &best_glyphs);   
+    if (best_glyphs.size() > 0) {
+      current_char = best_glyphs.front().first;
+      timestepEnd = best_glyphs.front().second;
+      best_glyphs.pop_front();
+    }      
+  } else {
+    ExtractPathAsUnicharIds(best_nodes, &unichar_ids, &certs, &ratings,
+                            &xcoords);
+  }
   int num_ids = unichar_ids.size();
   if (debug) {
     DebugUnicharPath(unicharset, best_nodes, unichar_ids, certs, ratings,
@@ -202,7 +220,6 @@ void RecodeBeamSearch::ExtractBestPathAsWords(const TBOX& line_box,
   }
   // Convert labels to unichar-ids.
   int word_end = 0;
-  int timestepEnd = 0;
   float prev_space_cert = 0.0f;
   for (int word_start = 0; word_start < num_ids; word_start = word_end) {
     for (word_end = word_start + 1; word_end < num_ids; ++word_end) {
@@ -226,11 +243,55 @@ void RecodeBeamSearch::ExtractBestPathAsWords(const TBOX& line_box,
     WERD_RES* word_res = InitializeWord(
         leading_space, line_box, word_start, word_end,
         std::min(space_cert, prev_space_cert), unicharset, xcoords, scale_factor);
-    if (glyph_confidence) {
+    if (glyph_confidence == 1) {
       for (size_t i = timestepEnd; i < xcoords[word_end]; i++) {
         word_res->timesteps.push_back(timesteps[i]);
       }
       timestepEnd = xcoords[word_end];
+    } else if (glyph_confidence == 2) {
+      float sum = 0;
+      std::vector<std::pair<const char*, float>> glyph_pairs;
+      for (size_t i = timestepEnd; i < xcoords[word_end]; i++) {
+        for (std::pair<const char*, float> glyph : timesteps[i]) {
+          if (std::strcmp(glyph.first, "") != 0) {
+             sum += glyph.second;
+             glyph_pairs.push_back(glyph);
+          }         
+        }
+        if (best_glyphs.size() > 0 &&  i == best_glyphs.front().second-1
+            || i == xcoords[word_end]-1) {
+          std::map<const char*, float> summed_propabilities;
+          for(auto it = glyph_pairs.begin(); it != glyph_pairs.end(); ++it) {
+            summed_propabilities[it->first] += it->second;
+          }
+          std::vector<std::pair<const char*, float>> accumulated_timestep;
+          accumulated_timestep.push_back(std::pair<const char*,float>
+                                        (unicharset->id_to_unichar_ext
+                                        (current_char), 2.0));
+          int pos;
+          for (auto it = summed_propabilities.begin();
+               it != summed_propabilities.end(); ++it) {
+            if(sum == 0) break;
+            it->second/=sum;
+            pos = 0;
+            while (accumulated_timestep.size() > pos 
+                   && accumulated_timestep[pos].second > it->second) {
+              pos++;
+            }
+            accumulated_timestep.insert(accumulated_timestep.begin() + pos,
+                                        std::pair<const char*,float>(it->first,
+                                        it->second));
+          }
+          if (best_glyphs.size() > 0) {
+            current_char = best_glyphs.front().first;
+            best_glyphs.pop_front();
+          }
+          glyph_pairs.clear();
+          word_res->timesteps.push_back(accumulated_timestep);
+          sum = 0;
+        }
+      }
+      timestepEnd = xcoords[word_end];  
     }
     for (int i = word_start; i < word_end; ++i) {
       BLOB_CHOICE_LIST* choices = new BLOB_CHOICE_LIST;
@@ -304,7 +365,8 @@ void RecodeBeamSearch::DebugBeamPos(const UNICHARSET& unicharset,
 void RecodeBeamSearch::ExtractPathAsUnicharIds(
     const GenericVector<const RecodeNode*>& best_nodes,
     GenericVector<int>* unichar_ids, GenericVector<float>* certs,
-    GenericVector<float>* ratings, GenericVector<int>* xcoords) {
+    GenericVector<float>* ratings, GenericVector<int>* xcoords,
+    std::deque<std::pair<int,int>>* best_glyphs) {
   unichar_ids->truncate(0);
   certs->truncate(0);
   ratings->truncate(0);
@@ -333,6 +395,9 @@ void RecodeBeamSearch::ExtractPathAsUnicharIds(
       }
       unichar_ids->push_back(unichar_id);
       xcoords->push_back(t);
+      if(best_glyphs != nullptr) {
+        best_glyphs->push_back(std::pair<int,int>(unichar_id,t));
+      }
       do {
         double cert = best_nodes[t++]->certainty;
         // Special-case NO-PERM space to forget the certainty of the previous

src/lstm/recodebeam.h

@@ -28,6 +28,7 @@
 #include "networkio.h"
 #include "ratngs.h"
 #include "unicharcompress.h"
+#include <deque>
 #include <set>
 #include <vector>
 
@@ -185,7 +186,7 @@ class RecodeBeamSearch {
   // If charset is not null, it enables detailed debugging of the beam search.
   void Decode(const NetworkIO& output, double dict_ratio, double cert_offset,
               double worst_dict_cert, const UNICHARSET* charset,
-              bool glyph_confidence = false);
+              int glyph_confidence = 0);
   void Decode(const GENERIC_2D_ARRAY<float>& output, double dict_ratio,
               double cert_offset, double worst_dict_cert,
               const UNICHARSET* charset);
@@ -204,12 +205,16 @@ class RecodeBeamSearch {
   // Returns the best path as a set of WERD_RES.
   void ExtractBestPathAsWords(const TBOX& line_box, float scale_factor,
                               bool debug, const UNICHARSET* unicharset,
-                              PointerVector<WERD_RES>* words, bool glyph_confidence);
+                              PointerVector<WERD_RES>* words,
+                              int glyph_confidence = 0);
 
   // Generates debug output of the content of the beams after a Decode.
   void DebugBeams(const UNICHARSET& unicharset) const;
-
+  
+  // Stores the alternative characters of every timestep together with their 
+  // probability.
   std::vector< std::vector<std::pair<const char*, float>>> timesteps;
+
   // Clipping value for certainty inside Tesseract. Reflects the minimum value
   // of certainty that will be returned by ExtractBestPathAsUnicharIds.
   // Supposedly on a uniform scale that can be compared across languages and
@@ -276,7 +281,8 @@ class RecodeBeamSearch {
   static void ExtractPathAsUnicharIds(
       const GenericVector<const RecodeNode*>& best_nodes,
       GenericVector<int>* unichar_ids, GenericVector<float>* certs,
-      GenericVector<float>* ratings, GenericVector<int>* xcoords);
+      GenericVector<float>* ratings, GenericVector<int>* xcoords,
+      std::deque<std::pair<int,int>>* best_glyphs = nullptr);
 
   // Sets up a word with the ratings matrix and fake blobs with boxes in the
   // right places.