[training] More unique ptrs.

src/training/classifier_tester.cpp

@@ -110,8 +110,7 @@ int main(int argc, char **argv) {
   tesseract::CheckSharedLibraryVersion();
   ParseArguments(&argc, &argv);
   STRING file_prefix;
-  auto trainer =
-      tesseract::LoadTrainingData(argc, argv, false, nullptr, &file_prefix);
+  auto [trainer,_] = tesseract::LoadTrainingData(argc, argv, false, false, &file_prefix);
   tesseract::TessBaseAPI* api;
   // Decode the classifier string.
   tesseract::ShapeClassifier* shape_classifier = InitializeClassifier(

src/training/common/commontraining.cpp

@@ -149,16 +149,14 @@ void ParseArguments(int* argc, char ***argv) {
 
 namespace tesseract {
 // Helper loads shape table from the given file.
-ShapeTable* LoadShapeTable(const STRING& file_prefix) {
-  ShapeTable* shape_table = nullptr;
+std::unique_ptr<ShapeTable> LoadShapeTable(const STRING& file_prefix) {
+  std::unique_ptr<ShapeTable> shape_table;
   STRING shape_table_file = file_prefix;
   shape_table_file += kShapeTableFileSuffix;
   TFile shape_fp;
   if (shape_fp.Open(shape_table_file.c_str(), nullptr)) {
-    shape_table = new ShapeTable;
+    shape_table = std::make_unique<ShapeTable>();
     if (!shape_table->DeSerialize(&shape_fp)) {
-      delete shape_table;
-      shape_table = nullptr;
       tprintf("Error: Failed to read shape table %s\n",
               shape_table_file.c_str());
     } else {
@@ -206,9 +204,10 @@ void WriteShapeTable(const STRING& file_prefix, const ShapeTable& shape_table) {
  * If shape_table is not nullptr, but failed to load, make a fake flat one,
  * as shape clustering was not run.
  */
-std::unique_ptr<MasterTrainer> LoadTrainingData(int argc, const char* const * argv,
+std::pair<std::unique_ptr<MasterTrainer>, std::unique_ptr<ShapeTable>>
+LoadTrainingData(int argc, const char* const * argv,
                                 bool replication,
-                                ShapeTable** shape_table,
+                                bool shape_analysis,
                                 STRING* file_prefix) {
   InitFeatureDefs(&feature_defs);
   InitIntegerFX();
@@ -221,12 +220,9 @@ std::unique_ptr<MasterTrainer> LoadTrainingData(int argc, const char* const * ar
   // a shape_table written by a previous shape clustering, then
   // shape_analysis will be true, meaning that the MasterTrainer will replace
   // some members of the unicharset with their fragments.
-  bool shape_analysis = false;
-  if (shape_table != nullptr) {
-    *shape_table = LoadShapeTable(*file_prefix);
-    if (*shape_table != nullptr) shape_analysis = true;
-  } else {
-    shape_analysis = true;
+  std::unique_ptr<ShapeTable> shape_table;
+  if (shape_analysis) {
+    shape_table = LoadShapeTable(*file_prefix);
   }
   auto trainer = std::make_unique<MasterTrainer>(NM_CHAR_ANISOTROPIC,
                                              shape_analysis,
@@ -289,18 +285,18 @@ std::unique_ptr<MasterTrainer> LoadTrainingData(int argc, const char* const * ar
     fprintf(stderr, "Failed to save unicharset to file %s\n", FLAGS_O.c_str());
     return {};
   }
-  if (shape_table != nullptr) {
+  if (shape_analysis) {
     // If we previously failed to load a shapetable, then shape clustering
     // wasn't run so make a flat one now.
-    if (*shape_table == nullptr) {
-      *shape_table = new ShapeTable;
-      trainer->SetupFlatShapeTable(*shape_table);
+    if (!shape_table) {
+      shape_table = std::make_unique<ShapeTable>();
+      trainer->SetupFlatShapeTable(shape_table.get());
       tprintf("Flat shape table summary: %s\n",
-              (*shape_table)->SummaryStr().c_str());
+              shape_table->SummaryStr().c_str());
     }
-    (*shape_table)->set_unicharset(trainer->unicharset());
+    shape_table->set_unicharset(trainer->unicharset());
   }
-  return trainer;
+  return { std::move(trainer), std::move(shape_table) };
 }
 
 }  // namespace tesseract.

src/training/common/commontraining.h

@@ -100,7 +100,7 @@ using MERGE_CLASS = MERGE_CLASS_NODE*;
 namespace tesseract {
 
 // Helper loads shape table from the given file.
-ShapeTable* LoadShapeTable(const STRING& file_prefix);
+std::unique_ptr<ShapeTable> LoadShapeTable(const STRING& file_prefix);
 // Helper to write the shape_table.
 TESS_COMMON_TRAINING_API
 void WriteShapeTable(const STRING& file_prefix, const ShapeTable& shape_table);
@@ -119,9 +119,10 @@ void WriteShapeTable(const STRING& file_prefix, const ShapeTable& shape_table);
 // If shape_table is not nullptr, but failed to load, make a fake flat one,
 // as shape clustering was not run.
 TESS_COMMON_TRAINING_API
-std::unique_ptr<MasterTrainer> LoadTrainingData(int argc, const char* const * argv,
+std::pair<std::unique_ptr<MasterTrainer>, std::unique_ptr<ShapeTable>>
+LoadTrainingData(int argc, const char* const * argv,
                                 bool replication,
-                                ShapeTable** shape_table,
+                                bool shape_analysis,
                                 STRING* file_prefix);
 
 }  // namespace tesseract.

src/training/mftraining.cpp

@@ -202,12 +202,11 @@ int main (int argc, char **argv) {
 
   ParseArguments(&argc, &argv);
 
-  ShapeTable* shape_table = nullptr;
   STRING file_prefix;
   // Load the training data.
-  auto trainer = tesseract::LoadTrainingData(argc, argv,
+  auto [trainer,shape_table] = tesseract::LoadTrainingData(argc, argv,
                                                        false,
-                                                       &shape_table,
+                                                       true,
                                                        &file_prefix);
   if (trainer == nullptr) return 1;  // Failed.
 
@@ -216,7 +215,7 @@ int main (int argc, char **argv) {
   // with the same list of unichars becomes a different class and the configs
   // represent the different combinations of fonts.
   IndexMapBiDi config_map;
-  SetupConfigMap(shape_table, &config_map);
+  SetupConfigMap(shape_table.get(), &config_map);
 
   WriteShapeTable(file_prefix, *shape_table);
   // If the shape_table is flat, then either we didn't run shape clustering, or
@@ -270,7 +269,6 @@ int main (int argc, char **argv) {
   }
   delete [] float_classes;
   FreeLabeledClassList(mf_classes);
-  delete shape_table;
   printf("Done!\n");
   if (!FLAGS_test_ch.empty()) {
     // If we are displaying debug window(s), wait for the user to look at them.

src/training/shapeclustering.cpp

@@ -49,9 +49,7 @@ int main(int argc, char **argv) {
   ParseArguments(&argc, &argv);
 
   STRING file_prefix;
-  auto trainer =
-      tesseract::LoadTrainingData(argc, argv, false, nullptr, &file_prefix);
-
+  auto [trainer,_] = tesseract::LoadTrainingData(argc, argv, false, false, &file_prefix);
   if (!trainer)
     return 1;
 

unittest/mastertrainer_test.cc

@@ -126,7 +126,7 @@ class MockClassifier : public ShapeClassifier {
     return results->size();
   }
   // Provides access to the ShapeTable that this classifier works with.
-  virtual const ShapeTable* GetShapeTable() const { return shape_table_; }
+  const ShapeTable* GetShapeTable() const override { return shape_table_; }
 
  private:
   // Borrowed pointer to the ShapeTable.
@@ -159,15 +159,6 @@ class MasterTrainerTest : public testing::Test {
     return file::JoinPath(FLAGS_test_tmpdir, name);
   }
 
-  MasterTrainerTest() {
-    shape_table_ = nullptr;
-    master_trainer_ = nullptr;
-  }
-  ~MasterTrainerTest() {
-    delete master_trainer_;
-    delete shape_table_;
-  }
-
   // Initializes the master_trainer_ and shape_table_.
   // if load_from_tmp, then reloads a master trainer that was saved by a
   // previous call in which it was false.
@@ -180,11 +171,9 @@ class MasterTrainerTest : public testing::Test {
     const char* argv[] = {tr_file_name.c_str()};
     int argc = 1;
     STRING file_prefix;
-    delete master_trainer_;
-    delete shape_table_;
-    shape_table_ = nullptr;
-    master_trainer_ =
-        LoadTrainingData(argc, argv, false, &shape_table_, &file_prefix);
+    auto [m,s] = LoadTrainingData(argc, argv, false, true, &file_prefix);
+    master_trainer_ = std::move(m);
+    shape_table_ = std::move(s);
     EXPECT_TRUE(master_trainer_ != nullptr);
     EXPECT_TRUE(shape_table_ != nullptr);
   }
@@ -237,8 +226,8 @@ class MasterTrainerTest : public testing::Test {
   }
 
   // Objects declared here can be used by all tests in the test case for Foo.
-  ShapeTable* shape_table_;
-  MasterTrainer* master_trainer_;
+  std::unique_ptr<ShapeTable> shape_table_;
+  std::unique_ptr<MasterTrainer> master_trainer_;
 #endif
 };
 
@@ -268,12 +257,11 @@ TEST_F(MasterTrainerTest, ErrorCounterTest) {
   // count junk.
   if (shape_table_->FindShape(0, -1) < 0) shape_table_->AddShape(0, 0);
   // Make a mock classifier.
-  tesseract::ShapeClassifier* shape_classifier =
-      new tesseract::MockClassifier(shape_table_);
+  auto shape_classifier = std::make_unique<MockClassifier>(shape_table_.get());
   // Get the accuracy report.
   STRING accuracy_report;
   master_trainer_->TestClassifierOnSamples(tesseract::CT_UNICHAR_TOP1_ERR, 0,
-                                           false, shape_classifier,
+                                           false, shape_classifier.get(),
                                            &accuracy_report);
   LOG(INFO) << accuracy_report.c_str();
   std::string result_string = accuracy_report.c_str();
@@ -298,7 +286,5 @@ TEST_F(MasterTrainerTest, ErrorCounterTest) {
             result_values[tesseract::CT_OK_MULTI_UNICHAR]);
   EXPECT_EQ(num_samples - kNumNonReject, result_values[tesseract::CT_REJECT]);
   EXPECT_EQ(kNumAnswers, result_values[tesseract::CT_NUM_RESULTS]);
-
-  delete shape_classifier;
 #endif
 }