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103 lines
4.6 KiB
C++
103 lines
4.6 KiB
C++
// (C) Copyright 2017, 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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#include <allheaders.h>
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#include <tesseract/baseapi.h>
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#include "lstm_test.h"
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namespace tesseract {
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TEST_F(LSTMTrainerTest, EncodesEng) {
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TestEncodeDecodeBoth("eng", "The quick brown 'fox' jumps over: the lazy dog!");
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}
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TEST_F(LSTMTrainerTest, EncodesKan) {
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TestEncodeDecodeBoth("kan", "ಫ್ರಬ್ರವರಿ ತತ್ವಾಂಶಗಳೆಂದರೆ ಮತ್ತು ಜೊತೆಗೆ ಕ್ರಮವನ್ನು");
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}
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TEST_F(LSTMTrainerTest, EncodesKor) {
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TestEncodeDecodeBoth("kor", "이는 것으로 다시 넣을 수는 있지만 선택의 의미는");
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}
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TEST_F(LSTMTrainerTest, MapCoder) {
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LSTMTrainer fra_trainer;
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fra_trainer.InitCharSet(TestDataNameToPath("fra/fra.traineddata"));
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LSTMTrainer deu_trainer;
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deu_trainer.InitCharSet(TestDataNameToPath("deu/deu.traineddata"));
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// A string that uses characters common to French and German.
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std::string kTestStr = "The quick brown 'fox' jumps over: the lazy dog!";
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std::vector<int> deu_labels;
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EXPECT_TRUE(deu_trainer.EncodeString(kTestStr.c_str(), &deu_labels));
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// The french trainer cannot decode them correctly.
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std::string badly_decoded = fra_trainer.DecodeLabels(deu_labels);
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std::string bad_str(&badly_decoded[0], badly_decoded.length());
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LOG(INFO) << "bad_str fra=" << bad_str << "\n";
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EXPECT_NE(kTestStr, bad_str);
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// Encode the string as fra.
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std::vector<int> fra_labels;
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EXPECT_TRUE(fra_trainer.EncodeString(kTestStr.c_str(), &fra_labels));
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// Use the mapper to compute what the labels are as deu.
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std::vector<int> mapping =
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fra_trainer.MapRecoder(deu_trainer.GetUnicharset(), deu_trainer.GetRecoder());
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std::vector<int> mapped_fra_labels(fra_labels.size(), -1);
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for (int i = 0; i < fra_labels.size(); ++i) {
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mapped_fra_labels[i] = mapping[fra_labels[i]];
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EXPECT_NE(-1, mapped_fra_labels[i]) << "i=" << i << ", ch=" << kTestStr[i];
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EXPECT_EQ(mapped_fra_labels[i], deu_labels[i])
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<< "i=" << i << ", ch=" << kTestStr[i] << " has deu label=" << deu_labels[i]
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<< ", but mapped to " << mapped_fra_labels[i];
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}
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// The german trainer can now decode them correctly.
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std::string decoded = deu_trainer.DecodeLabels(mapped_fra_labels);
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std::string ok_str(&decoded[0], decoded.length());
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LOG(INFO) << "ok_str deu=" << ok_str << "\n";
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EXPECT_EQ(kTestStr, ok_str);
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}
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// Tests that the actual fra model can be converted to the deu character set
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// and still read an eng image with 100% accuracy.
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TEST_F(LSTMTrainerTest, ConvertModel) {
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// Setup a trainer with a deu charset.
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LSTMTrainer deu_trainer;
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deu_trainer.InitCharSet(TestDataNameToPath("deu/deu.traineddata"));
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// Load the fra traineddata, strip out the model, and save to a tmp file.
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TessdataManager mgr;
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std::string fra_data = file::JoinPath(TESSDATA_DIR "_best", "fra.traineddata");
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CHECK(mgr.Init(fra_data.c_str()));
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LOG(INFO) << "Load " << fra_data << "\n";
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file::MakeTmpdir();
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std::string model_path = file::JoinPath(FLAGS_test_tmpdir, "fra.lstm");
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CHECK(mgr.ExtractToFile(model_path.c_str()));
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LOG(INFO) << "Extract " << model_path << "\n";
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// Load the fra model into the deu_trainer, and save the converted model.
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CHECK(deu_trainer.TryLoadingCheckpoint(model_path.c_str(), fra_data.c_str()));
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LOG(INFO) << "Checkpoint load for " << model_path << " and " << fra_data << "\n";
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std::string deu_data = file::JoinPath(FLAGS_test_tmpdir, "deu.traineddata");
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CHECK(deu_trainer.SaveTraineddata(deu_data.c_str()));
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LOG(INFO) << "Save " << deu_data << "\n";
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// Now run the saved model on phototest. (See BasicTesseractTest in
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// baseapi_test.cc).
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TessBaseAPI api;
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api.Init(FLAGS_test_tmpdir, "deu", tesseract::OEM_LSTM_ONLY);
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Pix *src_pix = pixRead(TestingNameToPath("phototest.tif").c_str());
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CHECK(src_pix);
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api.SetImage(src_pix);
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std::unique_ptr<char[]> result(api.GetUTF8Text());
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std::string truth_text;
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CHECK_OK(
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file::GetContents(TestingNameToPath("phototest.gold.txt"), &truth_text, file::Defaults()));
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EXPECT_STREQ(truth_text.c_str(), result.get());
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pixDestroy(&src_pix);
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}
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} // namespace tesseract
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