mirror of
https://github.com/tesseract-ocr/tesseract.git
synced 2024-12-13 07:59:04 +08:00
Revert "Integrated Timesteps per symbol into ChoiceIterator"
This reverts commit 4d3455e1de
.
This commit is contained in:
parent
4d3455e1de
commit
7160888653
@ -229,17 +229,11 @@ char* TessBaseAPI::GetHOCRText(ETEXT_DESC* monitor, int page_number) {
|
||||
}
|
||||
|
||||
// Now, process the word...
|
||||
std::vector<std::vector<std::pair<const char*, float>>>* rawTimestepMap =
|
||||
nullptr;
|
||||
std::vector<std::vector<std::pair<const char*, float>>>* choiceMap =
|
||||
nullptr;
|
||||
std::vector<std::vector<std::vector<std::pair<const char*, float>>>>*
|
||||
symbolMap = nullptr;
|
||||
if (tesseract_->lstm_choice_mode) {
|
||||
|
||||
choiceMap = res_it->GetBestLSTMSymbolChoices();
|
||||
symbolMap = res_it->GetSegmentedLSTMTimesteps();
|
||||
rawTimestepMap = res_it->GetRawLSTMTimesteps();
|
||||
}
|
||||
hocr_str << "\n <span class='ocrx_word'"
|
||||
<< " id='"
|
||||
@ -305,8 +299,8 @@ char* TessBaseAPI::GetHOCRText(ETEXT_DESC* monitor, int page_number) {
|
||||
if (italic) hocr_str << "</em>";
|
||||
if (bold) hocr_str << "</strong>";
|
||||
// If the lstm choice mode is required it is added here
|
||||
if (tesseract_->lstm_choice_mode == 1 && rawTimestepMap != nullptr) {
|
||||
for (auto timestep : *rawTimestepMap) {
|
||||
if (tesseract_->lstm_choice_mode == 1 && choiceMap != nullptr) {
|
||||
for (auto timestep : *choiceMap) {
|
||||
hocr_str << "\n <span class='ocrx_cinfo'"
|
||||
<< " id='"
|
||||
<< "timestep_" << page_id << "_" << wcnt << "_" << tcnt << "'"
|
||||
@ -342,33 +336,6 @@ char* TessBaseAPI::GetHOCRText(ETEXT_DESC* monitor, int page_number) {
|
||||
tcnt++;
|
||||
}
|
||||
}
|
||||
} else if (tesseract_->lstm_choice_mode == 3 && symbolMap != nullptr) {
|
||||
for (auto timesteps : *symbolMap) {
|
||||
hocr_str << "\n <span class='ocr_symbol'"
|
||||
<< " id='"
|
||||
<< "symbol_" << page_id << "_" << wcnt << "_" << scnt
|
||||
<< "'>";
|
||||
for (auto timestep : timesteps) {
|
||||
hocr_str << "\n <span class='ocrx_cinfo'"
|
||||
<< " id='"
|
||||
<< "timestep_" << page_id << "_" << wcnt << "_" << tcnt
|
||||
<< "'"
|
||||
<< ">";
|
||||
for (std::pair<const char*, float> conf : timestep) {
|
||||
hocr_str << "<span class='ocr_glyph'"
|
||||
<< " id='"
|
||||
<< "choice_" << page_id << "_" << wcnt << "_" << gcnt
|
||||
<< "'"
|
||||
<< " title='x_confs " << int(conf.second * 100) << "'>"
|
||||
<< conf.first << "</span>";
|
||||
gcnt++;
|
||||
}
|
||||
hocr_str << "</span>";
|
||||
tcnt++;
|
||||
}
|
||||
hocr_str << "</span>";
|
||||
scnt++;
|
||||
}
|
||||
}
|
||||
hocr_str << "</span>";
|
||||
tcnt = 1;
|
||||
|
@ -357,17 +357,7 @@ bool LTRResultIterator::SymbolIsDropcap() const {
|
||||
ChoiceIterator::ChoiceIterator(const LTRResultIterator& result_it) {
|
||||
ASSERT_HOST(result_it.it_->word() != nullptr);
|
||||
word_res_ = result_it.it_->word();
|
||||
oemLSTM_ = word_res_->tesseract->AnyLSTMLang();
|
||||
oemLegacy_ = word_res_->tesseract->AnyTessLang();
|
||||
BLOB_CHOICE_LIST* choices = nullptr;
|
||||
tstep_index_ = &result_it.blob_index_;
|
||||
if (oemLSTM_ && !oemLegacy_ && !word_res_->accumulated_timesteps.empty()) {
|
||||
if (word_res_->leadingSpace)
|
||||
LSTM_choices_ = &word_res_->accumulated_timesteps[(*tstep_index_) + 1];
|
||||
else
|
||||
LSTM_choices_ = &word_res_->accumulated_timesteps[*tstep_index_];
|
||||
filterSpaces();
|
||||
}
|
||||
if (word_res_->ratings != nullptr)
|
||||
choices = word_res_->GetBlobChoices(result_it.blob_index_);
|
||||
if (choices != nullptr && !choices->empty()) {
|
||||
@ -376,42 +366,23 @@ ChoiceIterator::ChoiceIterator(const LTRResultIterator& result_it) {
|
||||
} else {
|
||||
choice_it_ = nullptr;
|
||||
}
|
||||
if (LSTM_choices_ != nullptr && !LSTM_choices_->empty()) {
|
||||
LSTM_mode_ = true;
|
||||
LSTM_choice_it_ = LSTM_choices_->begin();
|
||||
}
|
||||
}
|
||||
ChoiceIterator::~ChoiceIterator() { delete choice_it_; }
|
||||
|
||||
// Moves to the next choice for the symbol and returns false if there
|
||||
// are none left.
|
||||
bool ChoiceIterator::Next() {
|
||||
if (LSTM_mode_) {
|
||||
if (LSTM_choice_it_ != LSTM_choices_->end() &&
|
||||
next(LSTM_choice_it_) == LSTM_choices_->end()) {
|
||||
return false;
|
||||
} else {
|
||||
++LSTM_choice_it_;
|
||||
return true;
|
||||
}
|
||||
} else {
|
||||
if (choice_it_ == nullptr) return false;
|
||||
choice_it_->forward();
|
||||
return !choice_it_->cycled_list();
|
||||
}
|
||||
if (choice_it_ == nullptr) return false;
|
||||
choice_it_->forward();
|
||||
return !choice_it_->cycled_list();
|
||||
}
|
||||
|
||||
// Returns the null terminated UTF-8 encoded text string for the current
|
||||
// choice. Do NOT use delete [] to free after use.
|
||||
const char* ChoiceIterator::GetUTF8Text() const {
|
||||
if (LSTM_mode_) {
|
||||
std::pair<const char*, float> choice = *LSTM_choice_it_;
|
||||
return choice.first;
|
||||
} else {
|
||||
if (choice_it_ == nullptr) return nullptr;
|
||||
UNICHAR_ID id = choice_it_->data()->unichar_id();
|
||||
return word_res_->uch_set->id_to_unichar_ext(id);
|
||||
}
|
||||
if (choice_it_ == nullptr) return nullptr;
|
||||
UNICHAR_ID id = choice_it_->data()->unichar_id();
|
||||
return word_res_->uch_set->id_to_unichar_ext(id);
|
||||
}
|
||||
|
||||
// Returns the confidence of the current choice depending on the used language
|
||||
@ -421,47 +392,10 @@ const char* ChoiceIterator::GetUTF8Text() const {
|
||||
// interpreted as a percent probability. (0.0f-100.0f) In this case probabilities
|
||||
// won't add up to 100. Each one stands on its own.
|
||||
float ChoiceIterator::Confidence() const {
|
||||
if (LSTM_mode_) {
|
||||
std::pair<const char*, float> choice = *LSTM_choice_it_;
|
||||
return choice.second;
|
||||
} else {
|
||||
if (choice_it_ == nullptr) return 0.0f;
|
||||
float confidence = 100 + 5 * choice_it_->data()->certainty();
|
||||
if (confidence < 0.0f) confidence = 0.0f;
|
||||
if (confidence > 100.0f) confidence = 100.0f;
|
||||
return confidence;
|
||||
}
|
||||
}
|
||||
|
||||
// Returns the set of timesteps which belong to the current symbol
|
||||
std::vector<std::vector<std::pair<const char*, float>>>*
|
||||
ChoiceIterator::Timesteps() const {
|
||||
if (word_res_->symbol_steps.empty() || !LSTM_mode_) return nullptr;
|
||||
if (word_res_->leadingSpace) {
|
||||
return &word_res_->symbol_steps[*(tstep_index_) + 1];
|
||||
} else {
|
||||
return &word_res_->symbol_steps[*tstep_index_];
|
||||
}
|
||||
}
|
||||
|
||||
void ChoiceIterator::filterSpaces() {
|
||||
if (LSTM_choices_->empty()) return;
|
||||
std::vector<std::pair<const char*, float>>::iterator it;
|
||||
bool found_space = false;
|
||||
float sum = 0;
|
||||
for (it = LSTM_choices_->begin(); it != LSTM_choices_->end();) {
|
||||
if (!strcmp(it->first, " ")) {
|
||||
it = LSTM_choices_->erase(it);
|
||||
found_space = true;
|
||||
} else {
|
||||
sum += it->second;
|
||||
++it;
|
||||
}
|
||||
}
|
||||
if (found_space) {
|
||||
for (it = LSTM_choices_->begin(); it != LSTM_choices_->end(); ++it) {
|
||||
it->second /= sum;
|
||||
}
|
||||
}
|
||||
if (choice_it_ == nullptr) return 0.0f;
|
||||
float confidence = 100 + 5 * choice_it_->data()->certainty();
|
||||
if (confidence < 0.0f) confidence = 0.0f;
|
||||
if (confidence > 100.0f) confidence = 100.0f;
|
||||
return confidence;
|
||||
}
|
||||
} // namespace tesseract.
|
||||
|
@ -216,28 +216,11 @@ class ChoiceIterator {
|
||||
// probabilities won't add up to 100. Each one stands on its own.
|
||||
float Confidence() const;
|
||||
|
||||
// Returns a vector containing all timesteps, which belong to the currently
|
||||
// selected symbol. A timestep is a vector containing pairs of symbols and
|
||||
// floating point numbers. The number states the probability for the
|
||||
// corresponding symbol.
|
||||
std::vector<std::vector<std::pair<const char*, float>>>* Timesteps() const;
|
||||
|
||||
private:
|
||||
//clears the remaining spaces out of the results and adapt the probabilities
|
||||
void filterSpaces();
|
||||
// Pointer to the WERD_RES object owned by the API.
|
||||
WERD_RES* word_res_;
|
||||
// Iterator over the blob choices.
|
||||
BLOB_CHOICE_IT* choice_it_;
|
||||
std::vector<std::pair<const char*, float>>* LSTM_choices_ = nullptr;
|
||||
std::vector<std::pair<const char*, float>>::iterator LSTM_choice_it_;
|
||||
|
||||
const int* tstep_index_;
|
||||
bool LSTM_mode_ = false;
|
||||
//true when there is lstm engine related trained data
|
||||
bool oemLSTM_;
|
||||
// true when there is legacy engine related trained data
|
||||
bool oemLegacy_;
|
||||
};
|
||||
|
||||
} // namespace tesseract.
|
||||
|
@ -604,28 +604,11 @@ char* ResultIterator::GetUTF8Text(PageIteratorLevel level) const {
|
||||
strncpy(result, text.string(), length);
|
||||
return result;
|
||||
}
|
||||
std::vector<std::vector<std::pair<const char*, float>>>*
|
||||
ResultIterator::GetRawLSTMTimesteps() const {
|
||||
if (it_->word() != nullptr) {
|
||||
return &it_->word()->raw_timesteps;
|
||||
} else {
|
||||
return nullptr;
|
||||
}
|
||||
}
|
||||
|
||||
std::vector<std::vector<std::pair<const char*, float>>>*
|
||||
ResultIterator::GetBestLSTMSymbolChoices() const {
|
||||
if (it_->word() != nullptr) {
|
||||
return &it_->word()->accumulated_timesteps;
|
||||
} else {
|
||||
return nullptr;
|
||||
}
|
||||
}
|
||||
|
||||
std::vector<std::vector<std::vector<std::pair<const char*, float>>>>*
|
||||
ResultIterator::GetSegmentedLSTMTimesteps() const {
|
||||
if (it_->word() != nullptr) {
|
||||
return &it_->word()->symbol_steps;
|
||||
return &it_->word()->timesteps;
|
||||
} else {
|
||||
return nullptr;
|
||||
}
|
||||
|
@ -100,12 +100,8 @@ class TESS_API ResultIterator : public LTRResultIterator {
|
||||
/**
|
||||
* Returns the LSTM choices for every LSTM timestep for the current word.
|
||||
*/
|
||||
virtual std::vector<std::vector<std::pair<const char*, float>>>*
|
||||
GetRawLSTMTimesteps() const;
|
||||
virtual std::vector<std::vector<std::pair<const char*, float>>>*
|
||||
GetBestLSTMSymbolChoices() const;
|
||||
virtual std::vector<std::vector<std::vector<std::pair<const char*, float>>>>*
|
||||
GetSegmentedLSTMTimesteps() const;
|
||||
|
||||
/**
|
||||
* Return whether the current paragraph's dominant reading direction
|
||||
|
@ -526,9 +526,7 @@ Tesseract::Tesseract()
|
||||
"Valid input values are 0, 1, 2 and 3. 0 is the default value. "
|
||||
"With 1 the alternative symbol choices per timestep are included. "
|
||||
"With 2 the alternative symbol choices are accumulated per "
|
||||
"character. "
|
||||
"With 3 the alternative symbol choices per timestep are included "
|
||||
"and separated by the suggested segmentation of Tesseract",
|
||||
"character. ",
|
||||
this->params()),
|
||||
|
||||
backup_config_file_(nullptr),
|
||||
|
@ -1091,9 +1091,7 @@ class Tesseract : public Wordrec {
|
||||
"Valid input values are 0, 1, 2 and 3. 0 is the default value. "
|
||||
"With 1 the alternative symbol choices per timestep are included. "
|
||||
"With 2 the alternative symbol choices are accumulated per "
|
||||
"character. "
|
||||
"With 3 the alternative symbol choices per timestep are included "
|
||||
"and separated by the suggested segmentation of Tesseract");
|
||||
"character. ");
|
||||
|
||||
//// ambigsrecog.cpp /////////////////////////////////////////////////////////
|
||||
FILE* init_recog_training(const STRING& fname);
|
||||
|
@ -220,12 +220,7 @@ class WERD_RES : public ELIST_LINK {
|
||||
// blob i and blob i+1.
|
||||
GenericVector<int> blob_gaps;
|
||||
// Stores the lstm choices of every timestep
|
||||
std::vector<std::vector<std::pair<const char*, float>>> raw_timesteps;
|
||||
std::vector<std::vector<std::pair<const char*, float>>> accumulated_timesteps;
|
||||
std::vector<std::vector<std::vector<std::pair<const char*, float>>>>
|
||||
symbol_steps;
|
||||
//Stores if the timestep vector starts with a space
|
||||
bool leadingSpace = false;
|
||||
std::vector<std::vector<std::pair<const char*, float>>> timesteps;
|
||||
// Ratings matrix contains classifier choices for each classified combination
|
||||
// of blobs. The dimension is the same as the number of blobs in chopped_word
|
||||
// and the leading diagonal corresponds to classifier results of the blobs
|
||||
|
@ -151,6 +151,25 @@ void destroy_nodes(LIST list, void_dest destructor) {
|
||||
}
|
||||
}
|
||||
|
||||
/**********************************************************************
|
||||
* i n s e r t
|
||||
*
|
||||
* Create a list element and rearrange the pointers so that the first
|
||||
* element in the list is the second argument.
|
||||
**********************************************************************/
|
||||
void insert(LIST list, void *node) {
|
||||
LIST element;
|
||||
|
||||
if (list != NIL_LIST) {
|
||||
element = push(NIL_LIST, node);
|
||||
set_rest(element, list_rest(list));
|
||||
set_rest(list, element);
|
||||
node = first_node(list);
|
||||
list->node = first_node(list_rest(list));
|
||||
list->next->node = (LIST)node;
|
||||
}
|
||||
}
|
||||
|
||||
/**********************************************************************
|
||||
* l a s t
|
||||
*
|
||||
@ -209,6 +228,19 @@ LIST push_last(LIST list, void *item) {
|
||||
return (push(NIL_LIST, item));
|
||||
}
|
||||
|
||||
/**********************************************************************
|
||||
* r e v e r s e
|
||||
*
|
||||
* Create a new list with the elements reversed. The old list is not
|
||||
* destroyed.
|
||||
**********************************************************************/
|
||||
LIST reverse(LIST list) {
|
||||
LIST newlist = NIL_LIST;
|
||||
|
||||
iterate(list) copy_first(list, newlist);
|
||||
return (newlist);
|
||||
}
|
||||
|
||||
/**********************************************************************
|
||||
* s e a r c h
|
||||
*
|
||||
|
@ -38,6 +38,10 @@
|
||||
* -----------------
|
||||
* iterate - Macro to create a for loop to visit each cell.
|
||||
*
|
||||
* COPYING:
|
||||
* -----------------
|
||||
* reverse - (Deprecated) Creates a backwards copy of the input list.
|
||||
*
|
||||
* LIST CELL COUNTS:
|
||||
* -----------------
|
||||
* count - Returns the number of list cells in the list.
|
||||
@ -46,6 +50,8 @@
|
||||
* TRANSFORMS: (Note: These functions all modify the input list.)
|
||||
* ----------
|
||||
* delete_d - Removes the requested elements from the list.
|
||||
* insert - (Deprecated) Add a new element into this spot in a list.
|
||||
(not NIL_LIST)
|
||||
* push_last - Add a new element onto the end of a list.
|
||||
*
|
||||
* SETS:
|
||||
@ -124,6 +130,8 @@ LIST destroy(LIST list);
|
||||
|
||||
void destroy_nodes(LIST list, void_dest destructor);
|
||||
|
||||
void insert(LIST list, void *node);
|
||||
|
||||
LIST last(LIST var_list);
|
||||
|
||||
LIST pop(LIST list);
|
||||
@ -132,6 +140,8 @@ LIST push(LIST list, void* element);
|
||||
|
||||
LIST push_last(LIST list, void* item);
|
||||
|
||||
LIST reverse(LIST list);
|
||||
|
||||
LIST search(LIST list, void* key, int_compare is_equal);
|
||||
|
||||
#endif
|
||||
|
@ -187,7 +187,6 @@ void RecodeBeamSearch::ExtractBestPathAsWords(const TBOX& line_box,
|
||||
GenericVector<const RecodeNode*> best_nodes;
|
||||
GenericVector<const RecodeNode*> second_nodes;
|
||||
std::deque<std::tuple<int, int>> best_choices;
|
||||
std::deque<std::tuple<int, int>> best_choices_acc;
|
||||
ExtractBestPaths(&best_nodes, &second_nodes);
|
||||
if (debug) {
|
||||
DebugPath(unicharset, best_nodes);
|
||||
@ -197,18 +196,15 @@ void RecodeBeamSearch::ExtractBestPathAsWords(const TBOX& line_box,
|
||||
DebugUnicharPath(unicharset, second_nodes, unichar_ids, certs, ratings,
|
||||
xcoords);
|
||||
}
|
||||
int timestepEndRaw = 0;
|
||||
int timestepEnd = 0;
|
||||
int timestepEnd_acc = 0;
|
||||
int timestepEnd= 0;
|
||||
//if lstm choice mode is required in granularity level 2 it stores the x
|
||||
//Coordinates of every chosen character to match the alternative choices to it
|
||||
if (lstm_choice_mode) {
|
||||
if (lstm_choice_mode == 2) {
|
||||
ExtractPathAsUnicharIds(best_nodes, &unichar_ids, &certs, &ratings,
|
||||
&xcoords, &best_choices, &best_choices_acc);
|
||||
&xcoords, &best_choices);
|
||||
if (best_choices.size() > 0) {
|
||||
timestepEnd = std::get<1>(best_choices.front());
|
||||
timestepEnd_acc = std::get<1>(best_choices_acc.front());
|
||||
best_choices_acc.pop_front();
|
||||
best_choices.pop_front();
|
||||
}
|
||||
} else {
|
||||
ExtractPathAsUnicharIds(best_nodes, &unichar_ids, &certs, &ratings,
|
||||
@ -244,22 +240,23 @@ 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 (lstm_choice_mode) {
|
||||
for (size_t i = timestepEndRaw; i < xcoords[word_end]; i++) {
|
||||
word_res->raw_timesteps.push_back(timesteps[i]);
|
||||
if (lstm_choice_mode == 1) {
|
||||
for (size_t i = timestepEnd; i < xcoords[word_end]; i++) {
|
||||
word_res->timesteps.push_back(timesteps[i]);
|
||||
}
|
||||
timestepEndRaw = xcoords[word_end];
|
||||
timestepEnd = xcoords[word_end];
|
||||
} else if (lstm_choice_mode == 2){
|
||||
// Accumulated Timesteps (choice mode 2 processing)
|
||||
float sum = 0;
|
||||
std::vector<std::pair<const char*, float>> choice_pairs;
|
||||
for (size_t i = timestepEnd_acc; i < xcoords[word_end]; i++) {
|
||||
for (size_t i = timestepEnd; i < xcoords[word_end]; i++) {
|
||||
for (std::pair<const char*, float> choice : timesteps[i]) {
|
||||
if (std::strcmp(choice.first, "")) {
|
||||
sum += choice.second;
|
||||
choice_pairs.push_back(choice);
|
||||
}
|
||||
}
|
||||
if ((best_choices_acc.size() > 0 && i == std::get<1>(best_choices_acc.front()) - 1)
|
||||
if ((best_choices.size() > 0 && i == std::get<1>(best_choices.front()) - 1)
|
||||
|| i == xcoords[word_end]-1) {
|
||||
std::map<const char*, float> summed_propabilities;
|
||||
for (auto & choice_pair : choice_pairs) {
|
||||
@ -278,32 +275,14 @@ void RecodeBeamSearch::ExtractBestPathAsWords(const TBOX& line_box,
|
||||
std::pair<const char*,float>(summed_propability.first,
|
||||
summed_propability.second));
|
||||
}
|
||||
if (best_choices_acc.size() > 0) {
|
||||
best_choices_acc.pop_front();
|
||||
if (best_choices.size() > 0) {
|
||||
best_choices.pop_front();
|
||||
}
|
||||
choice_pairs.clear();
|
||||
word_res->accumulated_timesteps.push_back(accumulated_timestep);
|
||||
word_res->timesteps.push_back(accumulated_timestep);
|
||||
sum = 0;
|
||||
}
|
||||
}
|
||||
timestepEnd_acc = xcoords[word_end];
|
||||
//Symbol Step (choice mode 3 processing)
|
||||
std::vector<std::vector<std::pair<const char*, float>>> currentSymbol;
|
||||
for (size_t i = timestepEnd; i < xcoords[word_end]; i++) {
|
||||
if (i == std::get<1>(best_choices.front())) {
|
||||
if (currentSymbol.size() > 0) {
|
||||
word_res->symbol_steps.push_back(currentSymbol);
|
||||
currentSymbol.clear();
|
||||
}
|
||||
const char* leadCharacter =
|
||||
unicharset->id_to_unichar_ext(std::get<0>(best_choices.front()));
|
||||
if (!strcmp(leadCharacter, " "))
|
||||
word_res->leadingSpace = true;
|
||||
if(best_choices.size()>1) best_choices.pop_front();
|
||||
}
|
||||
currentSymbol.push_back(timesteps[i]);
|
||||
}
|
||||
word_res->symbol_steps.push_back(currentSymbol);
|
||||
timestepEnd = xcoords[word_end];
|
||||
}
|
||||
for (int i = word_start; i < word_end; ++i) {
|
||||
@ -379,8 +358,7 @@ void RecodeBeamSearch::ExtractPathAsUnicharIds(
|
||||
const GenericVector<const RecodeNode*>& best_nodes,
|
||||
GenericVector<int>* unichar_ids, GenericVector<float>* certs,
|
||||
GenericVector<float>* ratings, GenericVector<int>* xcoords,
|
||||
std::deque<std::tuple<int, int>>* best_choices,
|
||||
std::deque<std::tuple<int, int>>* best_choices_acc) {
|
||||
std::deque<std::tuple<int, int>>* best_choices) {
|
||||
unichar_ids->truncate(0);
|
||||
certs->truncate(0);
|
||||
ratings->truncate(0);
|
||||
@ -434,8 +412,6 @@ void RecodeBeamSearch::ExtractPathAsUnicharIds(
|
||||
if (best_choices != nullptr) {
|
||||
best_choices->push_back(
|
||||
std::tuple<int, int>(id, tposition));
|
||||
best_choices_acc->push_back(
|
||||
std::tuple<int, int>(id, tposition));
|
||||
}
|
||||
}
|
||||
xcoords->push_back(width);
|
||||
|
@ -282,8 +282,7 @@ class RecodeBeamSearch {
|
||||
const GenericVector<const RecodeNode*>& best_nodes,
|
||||
GenericVector<int>* unichar_ids, GenericVector<float>* certs,
|
||||
GenericVector<float>* ratings, GenericVector<int>* xcoords,
|
||||
std::deque<std::tuple<int, int>>* best_choices = nullptr,
|
||||
std::deque<std::tuple<int, int>>* best_choices_acc = nullptr);
|
||||
std::deque<std::tuple<int, int>>* best_choices = nullptr);
|
||||
|
||||
// Sets up a word with the ratings matrix and fake blobs with boxes in the
|
||||
// right places.
|
||||
|
Loading…
Reference in New Issue
Block a user