def create_metrics(self):
return SoftmaxMetrics(
self.args.blank_symbol,
self.args.char_map,
self.args.timesteps,
self.image_size,
uses_original_data=self.args.is_original_fsns,
)
curriculum = BabyStepCurriculum(
args.dataset_specification,
FileBasedDataset,
args.blank_label,
attributes_to_adjust=attributes_to_adjust,
trigger=(args.test_interval, 'iteration'),
min_delta=0.1,
)
train_dataset, validation_dataset = curriculum.load_dataset(0)
# the metrics object calculates the loss
metrics = SoftmaxMetrics(
args.blank_label,
args.char_map,
train_dataset.num_timesteps,
image_size,
area_loss_factor=args.area_factor,
aspect_ratio_loss_factor=args.aspect_factor,
area_scaling_factor=args.area_scale_factor,
uses_original_data=args.is_original_fsns,
)
# create the localization net
localization_net = FSNSSingleSTNLocalizationNet(
args.dropout_ratio,
train_dataset.num_timesteps,
zoom=args.zoom,
use_dropout=args.use_dropout,
)
# create the recognition net
recognition_net = FSNSRecognitionResnet(