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Replace GenericVector<WordData> by std::vector<WordData>

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This fixes an LGTM alert:

    This parameter of type WordData is 112 bytes -
    consider passing a const pointer/reference instead.

It might also improve the performance.

Signed-off-by: Stefan Weil <sw@weil.de>
This commit is contained in:
Stefan Weil 2020-12-30 12:05:32 +01:00
parent fbc807ce99
commit 536a676250
3 changed files with 8 additions and 8 deletions
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8
src/ccmain/control.cpp
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@ -153,7 +153,7 @@ void Tesseract::SetupAllWordsPassN(int pass_n,
const TBOX* target_word_box, const TBOX* target_word_box,
const char* word_config, const char* word_config,
PAGE_RES* page_res, PAGE_RES* page_res,
GenericVector<WordData>* words) { std::vector<WordData>* words) {
// Prepare all the words. // Prepare all the words.
PAGE_RES_IT page_res_it(page_res); PAGE_RES_IT page_res_it(page_res);
for (page_res_it.restart_page(); page_res_it.word() != nullptr; for (page_res_it.restart_page(); page_res_it.word() != nullptr;
@ -210,7 +210,7 @@ void Tesseract::SetupWordPassN(int pass_n, WordData* word) {
// Runs word recognition on all the words. // Runs word recognition on all the words.
bool Tesseract::RecogAllWordsPassN(int pass_n, ETEXT_DESC* monitor, bool Tesseract::RecogAllWordsPassN(int pass_n, ETEXT_DESC* monitor,
PAGE_RES_IT* pr_it, PAGE_RES_IT* pr_it,
GenericVector<WordData>* words) { std::vector<WordData>* words) {
// TODO(rays) Before this loop can be parallelized (it would yield a massive // TODO(rays) Before this loop can be parallelized (it would yield a massive
// speed-up) all remaining member globals need to be converted to local/heap // speed-up) all remaining member globals need to be converted to local/heap
// (eg set_pass1 and set_pass2) and an intermediate adaption pass needs to be // (eg set_pass1 and set_pass2) and an intermediate adaption pass needs to be
@ -336,7 +336,7 @@ bool Tesseract::recog_all_words(PAGE_RES* page_res,
// Set up all words ready for recognition, so that if parallelism is on // Set up all words ready for recognition, so that if parallelism is on
// all the input and output classes are ready to run the classifier. // all the input and output classes are ready to run the classifier.
GenericVector<WordData> words; std::vector<WordData> words;
SetupAllWordsPassN(1, target_word_box, word_config, page_res, &words); SetupAllWordsPassN(1, target_word_box, word_config, page_res, &words);
#ifndef DISABLED_LEGACY_ENGINE #ifndef DISABLED_LEGACY_ENGINE
if (tessedit_parallelize) { if (tessedit_parallelize) {
@ -386,7 +386,7 @@ bool Tesseract::recog_all_words(PAGE_RES* page_res,
if (tessedit_tess_adaption_mode != 0x0 && !tessedit_test_adaption && if (tessedit_tess_adaption_mode != 0x0 && !tessedit_test_adaption &&
AnyTessLang()) { AnyTessLang()) {
page_res_it.restart_page(); page_res_it.restart_page();
GenericVector<WordData> words; std::vector<WordData> words;
SetupAllWordsPassN(2, target_word_box, word_config, page_res, &words); SetupAllWordsPassN(2, target_word_box, word_config, page_res, &words);
if (tessedit_parallelize) { if (tessedit_parallelize) {
PrerecAllWordsPar(words); PrerecAllWordsPar(words);

2
src/ccmain/par_control.cpp
View File

@ -35,7 +35,7 @@ struct BlobData {
BLOB_CHOICE_LIST** choices = nullptr; BLOB_CHOICE_LIST** choices = nullptr;
}; };
void Tesseract::PrerecAllWordsPar(const GenericVector<WordData>& words) { void Tesseract::PrerecAllWordsPar(const std::vector<WordData>& words) {
// Prepare all the blobs. // Prepare all the blobs.
GenericVector<BlobData> blobs; GenericVector<BlobData> blobs;
for (int w = 0; w < words.size(); ++w) { for (int w = 0; w < words.size(); ++w) {

6
src/ccmain/tesseractclass.h
View File

@ -334,7 +334,7 @@ class Tesseract : public Wordrec {
OSResults* osr, TO_BLOCK_LIST* to_blocks, Pix** photo_mask_pix, OSResults* osr, TO_BLOCK_LIST* to_blocks, Pix** photo_mask_pix,
Pix** music_mask_pix); Pix** music_mask_pix);
// par_control.cpp // par_control.cpp
void PrerecAllWordsPar(const GenericVector<WordData>& words); void PrerecAllWordsPar(const std::vector<WordData>& words);
//// linerec.cpp //// linerec.cpp
// Generates training data for training a line recognizer, eg LSTM. // Generates training data for training a line recognizer, eg LSTM.
@ -380,12 +380,12 @@ class Tesseract : public Wordrec {
// Sets up the words ready for whichever engine is to be run // Sets up the words ready for whichever engine is to be run
void SetupAllWordsPassN(int pass_n, const TBOX* target_word_box, void SetupAllWordsPassN(int pass_n, const TBOX* target_word_box,
const char* word_config, PAGE_RES* page_res, const char* word_config, PAGE_RES* page_res,
GenericVector<WordData>* words); std::vector<WordData>* words);
// Sets up the single word ready for whichever engine is to be run. // Sets up the single word ready for whichever engine is to be run.
void SetupWordPassN(int pass_n, WordData* word); void SetupWordPassN(int pass_n, WordData* word);
// Runs word recognition on all the words. // Runs word recognition on all the words.
bool RecogAllWordsPassN(int pass_n, ETEXT_DESC* monitor, PAGE_RES_IT* pr_it, bool RecogAllWordsPassN(int pass_n, ETEXT_DESC* monitor, PAGE_RES_IT* pr_it,
GenericVector<WordData>* words); std::vector<WordData>* words);
bool recog_all_words(PAGE_RES* page_res, ETEXT_DESC* monitor, bool recog_all_words(PAGE_RES* page_res, ETEXT_DESC* monitor,
const TBOX* target_word_box, const char* word_config, const TBOX* target_word_box, const char* word_config,
int dopasses); int dopasses);