74 {
75 tesseract::CheckSharedLibraryVersion();
77 if (FLAGS_model_output.empty()) {
78 tprintf(
"Must provide a --model_output!\n");
79 return EXIT_FAILURE;
80 }
81 if (FLAGS_traineddata.empty()) {
82 tprintf(
"Must provide a --traineddata see training wiki\n");
83 return EXIT_FAILURE;
84 }
85
86
88 test_file += "_wtest";
89 FILE* f = fopen(test_file.
c_str(),
"wb");
90 if (f != nullptr) {
91 fclose(f);
92 if (remove(test_file.
c_str()) != 0) {
93 tprintf(
"Error, failed to remove %s: %s\n",
94 test_file.
c_str(), strerror(errno));
95 return EXIT_FAILURE;
96 }
97 } else {
98 tprintf(
"Error, model output cannot be written: %s\n", strerror(errno));
99 return EXIT_FAILURE;
100 }
101
102
103 STRING checkpoint_file = FLAGS_model_output.
c_str();
104 checkpoint_file += "_checkpoint";
105 STRING checkpoint_bak = checkpoint_file +
".bak";
107 nullptr, nullptr, nullptr, nullptr, FLAGS_model_output.c_str(),
108 checkpoint_file.
c_str(), FLAGS_debug_interval,
109 static_cast<int64_t>(FLAGS_max_image_MB) * 1048576);
110 trainer.InitCharSet(FLAGS_traineddata.c_str());
111
112
113
114 if (FLAGS_stop_training || FLAGS_debug_network) {
115 if (!trainer.TryLoadingCheckpoint(FLAGS_continue_from.c_str(), nullptr)) {
116 tprintf(
"Failed to read continue from: %s\n",
117 FLAGS_continue_from.c_str());
118 return EXIT_FAILURE;
119 }
120 if (FLAGS_debug_network) {
121 trainer.DebugNetwork();
122 } else {
123 if (FLAGS_convert_to_int) trainer.ConvertToInt();
124 if (!trainer.SaveTraineddata(FLAGS_model_output.c_str())) {
125 tprintf(
"Failed to write recognition model : %s\n",
126 FLAGS_model_output.c_str());
127 }
128 }
129 return EXIT_SUCCESS;
130 }
131
132
133 if (FLAGS_train_listfile.empty()) {
134 tprintf(
"Must supply a list of training filenames! --train_listfile\n");
135 return EXIT_FAILURE;
136 }
139 &filenames)) {
140 tprintf(
"Failed to load list of training filenames from %s\n",
141 FLAGS_train_listfile.c_str());
142 return EXIT_FAILURE;
143 }
144
145
146 if (trainer.TryLoadingCheckpoint(checkpoint_file.
string(),
nullptr) ||
147 trainer.TryLoadingCheckpoint(checkpoint_bak.
string(),
nullptr)) {
148 tprintf(
"Successfully restored trainer from %s\n",
149 checkpoint_file.
string());
150 } else {
151 if (!FLAGS_continue_from.empty()) {
152
153 if (!trainer.TryLoadingCheckpoint(FLAGS_continue_from.c_str(),
154 FLAGS_append_index >= 0
155 ? FLAGS_continue_from.c_str()
156 : FLAGS_old_traineddata.c_str())) {
157 tprintf(
"Failed to continue from: %s\n", FLAGS_continue_from.c_str());
158 return EXIT_FAILURE;
159 }
160 tprintf(
"Continuing from %s\n", FLAGS_continue_from.c_str());
161 trainer.InitIterations();
162 }
163 if (FLAGS_continue_from.empty() || FLAGS_append_index >= 0) {
164 if (FLAGS_append_index >= 0) {
165 tprintf(
"Appending a new network to an old one!!");
166 if (FLAGS_continue_from.empty()) {
167 tprintf(
"Must set --continue_from for appending!\n");
168 return EXIT_FAILURE;
169 }
170 }
171
172 if (!trainer.InitNetwork(FLAGS_net_spec.c_str(), FLAGS_append_index,
173 FLAGS_net_mode, FLAGS_weight_range,
174 FLAGS_learning_rate, FLAGS_momentum,
175 FLAGS_adam_beta)) {
176 tprintf(
"Failed to create network from spec: %s\n",
177 FLAGS_net_spec.c_str());
178 return EXIT_FAILURE;
179 }
180 trainer.set_perfect_delay(FLAGS_perfect_sample_delay);
181 }
182 }
183 if (!trainer.LoadAllTrainingData(filenames,
184 FLAGS_sequential_training
187 FLAGS_randomly_rotate)) {
188 tprintf(
"Load of images failed!!\n");
189 return EXIT_FAILURE;
190 }
191
193 1048576);
195 if (!FLAGS_eval_listfile.empty()) {
196 if (!tester.LoadAllEvalData(FLAGS_eval_listfile.c_str())) {
197 tprintf(
"Failed to load eval data from: %s\n",
198 FLAGS_eval_listfile.c_str());
199 return EXIT_FAILURE;
200 }
201 tester_callback =
203 }
204 do {
205
206 int iteration = trainer.training_iteration();
208 iteration < target_iteration &&
209 (iteration < FLAGS_max_iterations || FLAGS_max_iterations == 0);
210 iteration = trainer.training_iteration()) {
211 trainer.TrainOnLine(&trainer, false);
212 }
214 trainer.MaintainCheckpoints(tester_callback, &log_str);
216 } while (trainer.best_error_rate() > FLAGS_target_error_rate &&
217 (trainer.training_iteration() < FLAGS_max_iterations ||
218 FLAGS_max_iterations == 0));
219 delete tester_callback;
220 tprintf(
"Finished! Error rate = %g\n", trainer.best_error_rate());
221 return EXIT_SUCCESS;
222}
_ConstTessMemberResultCallback_5_0< false, R, T1, P1, P2, P3, P4, P5 >::base * NewPermanentTessCallback(const T1 *obj, R(T2::*member)(P1, P2, P3, P4, P5) const, typename Identity< P1 >::type p1, typename Identity< P2 >::type p2, typename Identity< P3 >::type p3, typename Identity< P4 >::type p4, typename Identity< P5 >::type p5)
DLLSYM void tprintf(const char *format,...)
void ParseArguments(int *argc, char ***argv)
const int kNumPagesPerBatch
bool LoadFileLinesToStrings(const char *filename, GenericVector< STRING > *lines)
const char * c_str() const
const char * string() const
STRING RunEvalAsync(int iteration, const double *training_errors, const TessdataManager &model_mgr, int training_stage)