def test(self):
test_loader = DataLoader(
os.path.join(self.config['global']['folders']['datasets'],
self.config['global']['files']['datasets']['test']))
self.model.evaluate_generator(
generator=test_loader.flow(batch=self.batch),
val_samples=test_loader.size)
def train(self):
train_loader = DataLoader(
os.path.join(self.config['global']['folders']['datasets'],
self.config['global']['files']['datasets']['train']))
validation_loader = DataLoader(os.path.join(
self.config['global']['folders']['datasets'],
self.config['global']['files']['datasets']['validation']),
random=False)
h = self.model.fit_generator(train_loader.flow(self.batch),
samples_per_epoch=self.samples,
nb_epoch=self.epochs,
validation_data=validation_loader.flow(
self.batch),
nb_val_samples=validation_loader.size)
self.dump(h.history)
