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