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Limited max height to 48 even in variable height input, enabled neural nets via ocr engine mode

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This commit is contained in:
Ray Smith 2016-11-08 14:01:04 -08:00
parent c1c1e426b3
commit f24ef67df4
8 changed files with 61 additions and 21 deletions
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5
ChangeLog
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@ -1,3 +1,8 @@
2016-11-11 - V4.00.00
* Added new neural network system based on LSTMs, with major accuracy gains.
* Improvements to PDF rendering.
* Fixes to trainingdata rendering.
2016-02-17 - V3.04.01
* Added OSD renderer for psm 0. Works for single page and multi-page images.
* Improve tesstrain.sh script.

36
api/tesseractmain.cpp
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@ -90,7 +90,7 @@ void PrintVersionInfo() {
void PrintUsage(const char* program) {
printf(
"Usage:\n"
" %s --help | --help-psm | --version\n"
" %s --help | --help-psm | --help-oem | --version\n"
" %s --list-langs [--tessdata-dir PATH]\n"
" %s --print-parameters [options...] [configfile...]\n"
" %s imagename|stdin outputbase|stdout [options...] [configfile...]\n",
@ -120,6 +120,18 @@ void PrintHelpForPSM() {
printf("%s", msg);
}
void PrintHelpForOEM() {
const char* msg =
"OCR Engine modes:\n"
" 0 Original Tesseract only.\n"
" 1 Cube only.\n"
" 2 Tesseract + cube.\n"
" 3 Default, based on what is available.\n"
" 4 Neural nets (LSTM) only.\n";
printf("%s", msg);
}
void PrintHelpMessage(const char* program) {
PrintUsage(program);
@ -132,15 +144,18 @@ void PrintHelpMessage(const char* program) {
" -c VAR=VALUE Set value for config variables.\n"
" Multiple -c arguments are allowed.\n"
" -psm NUM Specify page segmentation mode.\n"
" -oem NUM Specify OCR Engine mode.\n"
"NOTE: These options must occur before any configfile.\n";
printf("\n%s\n", ocr_options);
PrintHelpForPSM();
PrintHelpForOEM();
const char* single_options =
"Single options:\n"
" -h, --help Show this help message.\n"
" --help-psm Show page segmentation modes.\n"
" --help-oem Show OCR Engine modes.\n"
" -v, --version Show version information.\n"
" --list-langs List available languages for tesseract engine.\n"
" --print-parameters Print tesseract parameters to stdout.\n";
@ -214,7 +229,8 @@ void ParseArgs(const int argc, char** argv, const char** lang,
const char** datapath, bool* list_langs, bool* print_parameters,
GenericVector<STRING>* vars_vec,
GenericVector<STRING>* vars_values, int* arg_i,
tesseract::PageSegMode* pagesegmode) {
tesseract::PageSegMode* pagesegmode,
tesseract::OcrEngineMode* enginemode) {
if (argc == 1) {
PrintHelpMessage(argv[0]);
exit(0);
@ -229,6 +245,10 @@ void ParseArgs(const int argc, char** argv, const char** lang,
PrintHelpForPSM();
exit(0);
}
if ((strcmp(argv[1], "--help-oem") == 0)) {
PrintHelpForOEM();
exit(0);
}
if ((strcmp(argv[1], "-v") == 0) || (strcmp(argv[1], "--version") == 0)) {
PrintVersionInfo();
exit(0);
@ -258,6 +278,9 @@ void ParseArgs(const int argc, char** argv, const char** lang,
} else if (strcmp(argv[i], "-psm") == 0 && i + 1 < argc) {
*pagesegmode = static_cast<tesseract::PageSegMode>(atoi(argv[i + 1]));
++i;
} else if (strcmp(argv[i], "-oem") == 0 && i + 1 < argc) {
*enginemode = static_cast<tesseract::OcrEngineMode>(atoi(argv[i + 1]));
++i;
} else if (strcmp(argv[i], "--print-parameters") == 0) {
noocr = true;
*print_parameters = true;
@ -355,6 +378,7 @@ int main(int argc, char** argv) {
bool print_parameters = false;
int arg_i = 1;
tesseract::PageSegMode pagesegmode = tesseract::PSM_AUTO;
tesseract::OcrEngineMode enginemode = tesseract::OEM_DEFAULT;
/* main() calls functions like ParseArgs which call exit().
* This results in memory leaks if vars_vec and vars_values are
* declared as auto variables (destructor is not called then). */
@ -367,7 +391,8 @@ int main(int argc, char** argv) {
#endif /* HAVE_TIFFIO_H && _WIN32 */
ParseArgs(argc, argv, &lang, &image, &outputbase, &datapath, &list_langs,
&print_parameters, &vars_vec, &vars_values, &arg_i, &pagesegmode);
&print_parameters, &vars_vec, &vars_values, &arg_i, &pagesegmode,
&enginemode);
bool banner = false;
if (outputbase != NULL && strcmp(outputbase, "-") &&
@ -380,9 +405,8 @@ int main(int argc, char** argv) {
api.SetOutputName(outputbase);
int init_failed =
api.Init(datapath, lang, tesseract::OEM_DEFAULT, &(argv[arg_i]),
argc - arg_i, &vars_vec, &vars_values, false);
int init_failed = api.Init(datapath, lang, enginemode, &(argv[arg_i]),
argc - arg_i, &vars_vec, &vars_values, false);
if (init_failed) {
fprintf(stderr, "Could not initialize tesseract.\n");
exit(1);

6
ccmain/tessedit.cpp
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@ -218,7 +218,11 @@ bool Tesseract::init_tesseract_lang_data(
if (tessdata_manager_debug_level)
tprintf("Loaded Cube with combiner\n");
} else if (tessedit_ocr_engine_mode == OEM_LSTM_ONLY) {
if (tessdata_manager.SeekToStart(TESSDATA_LSTM)) {
if (tessdata_manager.swap()) {
tprintf("Error: LSTM requested on big-endian hardware!!\n");
tprintf("Big-endian not yet supported! Loading tesseract.\n");
tessedit_ocr_engine_mode.set_value(OEM_TESSERACT_ONLY);
} else if (tessdata_manager.SeekToStart(TESSDATA_LSTM)) {
lstm_recognizer_ = new LSTMRecognizer;
TFile fp;
fp.Open(tessdata_manager.GetDataFilePtr(), -1);

10
ccstruct/imagedata.cpp
View File

@ -217,7 +217,7 @@ Pix* ImageData::GetPix() const {
// The return value is the scaled Pix, which must be pixDestroyed after use,
// and scale_factor (if not NULL) is set to the scale factor that was applied
// to the image to achieve the target_height.
Pix* ImageData::PreScale(int target_height, float* scale_factor,
Pix* ImageData::PreScale(int target_height, int max_height, float* scale_factor,
int* scaled_width, int* scaled_height,
GenericVector<TBOX>* boxes) const {
int input_width = 0;
@ -226,8 +226,12 @@ Pix* ImageData::PreScale(int target_height, float* scale_factor,
ASSERT_HOST(src_pix != NULL);
input_width = pixGetWidth(src_pix);
input_height = pixGetHeight(src_pix);
if (target_height == 0)
target_height = input_height;
if (target_height == 0) {
if (input_height > max_height)
target_height = max_height;
else
target_height = input_height;
}
float im_factor = static_cast<float>(target_height) / input_height;
if (scaled_width != NULL)
*scaled_width = IntCastRounded(im_factor * input_width);

5
ccstruct/imagedata.h
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@ -165,8 +165,9 @@ class ImageData {
// The return value is the scaled Pix, which must be pixDestroyed after use,
// and scale_factor (if not NULL) is set to the scale factor that was applied
// to the image to achieve the target_height.
Pix* PreScale(int target_height, float* scale_factor, int* scaled_width,
int* scaled_height, GenericVector<TBOX>* boxes) const;
Pix* PreScale(int target_height, int max_height, float* scale_factor,
int* scaled_width, int* scaled_height,
GenericVector<TBOX>* boxes) const;
int MemoryUsed() const;

7
lstm/input.cpp
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@ -25,6 +25,9 @@
namespace tesseract {
// Max height for variable height inputs before scaling anyway.
const int kMaxInputHeight = 48;
Input::Input(const STRING& name, int ni, int no)
: Network(NT_INPUT, name, ni, no), cached_x_scale_(1) {}
Input::Input(const STRING& name, const StaticShape& shape)
@ -92,8 +95,8 @@ Pix* Input::PrepareLSTMInputs(const ImageData& image_data,
// Note that NumInputs() is defined as input image height.
int target_height = network->NumInputs();
int width, height;
Pix* pix =
image_data.PreScale(target_height, image_scale, &width, &height, nullptr);
Pix* pix = image_data.PreScale(target_height, kMaxInputHeight, image_scale,
&width, &height, nullptr);
if (pix == nullptr) {
tprintf("Bad pix from ImageData!\n");
return nullptr;

10
lstm/lstmtrainer.cpp
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@ -34,8 +34,6 @@
#include "callcpp.h"
using std::string;
namespace tesseract {
// Min actual error rate increase to constitute divergence.
@ -203,7 +201,7 @@ bool LSTMTrainer::InitNetwork(const STRING& network_spec, int append_index,
// Initializes a trainer from a serialized TFNetworkModel proto.
// Returns the global step of TensorFlow graph or 0 if failed.
int LSTMTrainer::InitTensorFlowNetwork(const string& tf_proto) {
int LSTMTrainer::InitTensorFlowNetwork(const std::string& tf_proto) {
#ifdef INCLUDE_TENSORFLOW
delete network_;
TFNetwork* tf_net = new TFNetwork("TensorFlow");
@ -1199,14 +1197,14 @@ double LSTMTrainer::ComputeCharError(const GenericVector<int>& truth_str,
// Computes a very simple bag of words word recall error rate.
// NOTE that this is destructive on both input strings.
double LSTMTrainer::ComputeWordError(STRING* truth_str, STRING* ocr_str) {
typedef TessHashMap<string, int, std::hash<string> > StrMap;
typedef TessHashMap<std::string, int, std::hash<std::string> > StrMap;
GenericVector<STRING> truth_words, ocr_words;
truth_str->split(' ', &truth_words);
if (truth_words.empty()) return 0.0;
ocr_str->split(' ', &ocr_words);
StrMap word_counts;
for (int i = 0; i < truth_words.size(); ++i) {
string truth_word(truth_words[i].string());
std::string truth_word(truth_words[i].string());
StrMap::iterator it = word_counts.find(truth_word);
if (it == word_counts.end())
word_counts.insert(make_pair(truth_word, 1));
@ -1214,7 +1212,7 @@ double LSTMTrainer::ComputeWordError(STRING* truth_str, STRING* ocr_str) {
++it->second;
}
for (int i = 0; i < ocr_words.size(); ++i) {
string ocr_word(ocr_words[i].string());
std::string ocr_word(ocr_words[i].string());
StrMap::iterator it = word_counts.find(ocr_word);
if (it == word_counts.end())
word_counts.insert(make_pair(ocr_word, -1));

3
training/pango_font_info.cpp
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@ -127,7 +127,8 @@ string PangoFontInfo::DescriptionName() const {
/* static */
void PangoFontInfo::SoftInitFontConfig() {
if (fonts_dir_.empty()) {
HardInitFontConfig(FLAGS_fonts_dir.c_str(), FLAGS_fontconfig_tmpdir.c_str());
HardInitFontConfig(FLAGS_fonts_dir.c_str(),
FLAGS_fontconfig_tmpdir.c_str());
}
}