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>
This commit is contained in:
Noah Metzger 2018-08-15 16:06:02 +02:00
parent 115fe7662c
commit 663be426f6
7 changed files with 111 additions and 17 deletions

View File

@ -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;

View File

@ -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()),

View File

@ -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);

View File

@ -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;

View File

@ -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,

View File

@ -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

View File

@ -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.