tesseract/training/lstmtester.cpp

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///////////////////////////////////////////////////////////////////////
// File: lstmtester.cpp
// Description: Top-level line evaluation class for LSTM-based networks.
// Author: Ray Smith
// Created: Wed Nov 23 11:18:06 PST 2016
//
// (C) Copyright 2016, Google Inc.
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
// http://www.apache.org/licenses/LICENSE-2.0
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.
///////////////////////////////////////////////////////////////////////
#include "lstmtester.h"
#include "genericvector.h"
namespace tesseract {
LSTMTester::LSTMTester(inT64 max_memory)
: test_data_(max_memory), total_pages_(0), async_running_(false) {}
// Loads a set of lstmf files that were created using the lstm.train config to
// tesseract into memory ready for testing. Returns false if nothing was
// loaded. The arg is a filename of a file that lists the filenames.
bool LSTMTester::LoadAllEvalData(const STRING& filenames_file) {
GenericVector<STRING> filenames;
if (!LoadFileLinesToStrings(filenames_file, &filenames)) {
tprintf("Failed to load list of eval filenames from %s\n",
filenames_file.string());
return false;
}
return LoadAllEvalData(filenames);
}
// Loads a set of lstmf files that were created using the lstm.train config to
// tesseract into memory ready for testing. Returns false if nothing was
// loaded.
bool LSTMTester::LoadAllEvalData(const GenericVector<STRING>& filenames) {
test_data_.Clear();
bool result = test_data_.LoadDocuments(filenames, CS_SEQUENTIAL, nullptr);
total_pages_ = test_data_.TotalPages();
return result;
}
// Runs an evaluation asynchronously on the stored data and returns a string
// describing the results of the previous test.
STRING LSTMTester::RunEvalAsync(int iteration, const double* training_errors,
const TessdataManager& model_mgr,
int training_stage) {
STRING result;
if (total_pages_ == 0) {
result.add_str_int("No test data at iteration", iteration);
return result;
}
if (!LockIfNotRunning()) {
result.add_str_int("Previous test incomplete, skipping test at iteration",
iteration);
return result;
}
// Save the args.
STRING prev_result = test_result_;
test_result_ = "";
if (training_errors != nullptr) {
test_iteration_ = iteration;
test_training_errors_ = training_errors;
test_model_mgr_ = model_mgr;
test_training_stage_ = training_stage;
SVSync::StartThread(&LSTMTester::ThreadFunc, this);
} else {
UnlockRunning();
}
return prev_result;
}
// Runs an evaluation synchronously on the stored data and returns a string
// describing the results.
STRING LSTMTester::RunEvalSync(int iteration, const double* training_errors,
const TessdataManager& model_mgr,
int training_stage, int verbosity) {
LSTMTrainer trainer;
trainer.InitCharSet(model_mgr);
TFile fp;
if (!model_mgr.GetComponent(TESSDATA_LSTM, &fp) ||
!trainer.DeSerialize(&model_mgr, &fp)) {
return "Deserialize failed";
}
int eval_iteration = 0;
double char_error = 0.0;
double word_error = 0.0;
int error_count = 0;
while (error_count < total_pages_) {
const ImageData* trainingdata = test_data_.GetPageBySerial(eval_iteration);
trainer.SetIteration(++eval_iteration);
NetworkIO fwd_outputs, targets;
Trainability result =
trainer.PrepareForBackward(trainingdata, &fwd_outputs, &targets);
if (result != UNENCODABLE) {
char_error += trainer.NewSingleError(tesseract::ET_CHAR_ERROR);
word_error += trainer.NewSingleError(tesseract::ET_WORD_RECERR);
++error_count;
if (verbosity > 1 || (verbosity > 0 && result != PERFECT)) {
tprintf("Truth:%s\n", trainingdata->transcription().string());
GenericVector<int> ocr_labels;
GenericVector<int> xcoords;
trainer.LabelsFromOutputs(fwd_outputs, &ocr_labels, &xcoords);
STRING ocr_text = trainer.DecodeLabels(ocr_labels);
tprintf("OCR :%s\n", ocr_text.string());
}
}
}
char_error *= 100.0 / total_pages_;
word_error *= 100.0 / total_pages_;
STRING result;
result.add_str_int("At iteration ", iteration);
result.add_str_int(", stage ", training_stage);
result.add_str_double(", Eval Char error rate=", char_error);
result.add_str_double(", Word error rate=", word_error);
return result;
}
// Static helper thread function for RunEvalAsync, with a specific signature
// required by SVSync::StartThread. Actually a member function pretending to
// be static, its arg is a this pointer that it will cast back to LSTMTester*
// to call RunEvalSync using the stored args that RunEvalAsync saves in *this.
// LockIfNotRunning must have returned true before calling ThreadFunc, and
// it will call UnlockRunning to release the lock after RunEvalSync completes.
/* static */
void* LSTMTester::ThreadFunc(void* lstmtester_void) {
2017-05-11 06:40:31 +08:00
LSTMTester* lstmtester = static_cast<LSTMTester*>(lstmtester_void);
lstmtester->test_result_ = lstmtester->RunEvalSync(
lstmtester->test_iteration_, lstmtester->test_training_errors_,
lstmtester->test_model_mgr_, lstmtester->test_training_stage_,
/*verbosity*/ 0);
lstmtester->UnlockRunning();
return lstmtester_void;
}
// Returns true if there is currently nothing running, and takes the lock
// if there is nothing running.
bool LSTMTester::LockIfNotRunning() {
SVAutoLock lock(&running_mutex_);
if (async_running_) return false;
async_running_ = true;
return true;
}
// Releases the running lock.
void LSTMTester::UnlockRunning() {
SVAutoLock lock(&running_mutex_);
async_running_ = false;
}
} // namespace tesseract