def test_2_train_faces(self):
base_model_path = base_models_dir + '/inception_v1'
trainer = Trainer(base_model_path, test_dir + '/fixtures/scaffolds/faces', num_steps=10000)
trainer.prepare()
benchmark_info = trainer.train(test_dir + '/fixtures/tmp/faces_test')
validate_model(test_dir + '/fixtures/tmp/faces_test')
self.assertEqual(benchmark_info['test_accuracy'] >= 0.80, True)
def test_7_train_coffee_roasts(self):
scaffold_dir = test_dir + '/fixtures/scaffolds/coffee_roasts'
output_model_path = test_dir + '/fixtures/tmp/coffee_roasts_test'
base_model_path = base_models_dir + '/inception_v3'
trainer = Trainer(base_model_path, scaffold_dir, num_steps=100)
clear_scaffold_cache(scaffold_dir)
trainer.prepare()
benchmark_info = trainer.train(output_model_path)
self.assertEqual(benchmark_info['test_accuracy'] >= 0.75, True)
validate_model(output_model_path)
def test_5_train_scene_type_resnet_v2(self):
scaffold_dir = test_dir + '/fixtures/scaffolds/scene_type'
output_model_path = test_dir + '/fixtures/tmp/scene_type_test_resnetv2'
base_model_path = base_models_dir + '/inception_resnet_v2'
trainer = SlimTrainer(base_model_path, scaffold_dir, num_steps=20, batch_size=32)
clear_scaffold_cache(scaffold_dir)
trainer.prepare()
benchmark_info = trainer.train(output_model_path)
self.assertEqual(benchmark_info['final_loss'] <= 0.80, True)
validate_model(output_model_path)