if os.path.exists(test_imagefeat_dict_name):
datasets.test_image_id_imagefeat_dict = load_obj(
test_imagefeat_dict_name)
datasets.load_test_data()
# Set this variable to True if you want to save the image features
save = False
if save:
save_obj(datasets.test_image_id_imagefeat_dict,
test_imagefeat_dict_name)
if is_training == 'YES':
if os.path.exists(train_imagefeat_dict_name):
datasets.train_image_id_imagefeat_dict = load_obj(
train_imagefeat_dict_name)
# Validation part of pipeline is commented out to speedup training process
# if os.path.exists(dev_imagefeat_dict_name):
# datasets.dev_image_id_imagefeat_dict = load_obj(dev_imagefeat_dict_name)
datasets.load_data(train_file)
# datasets.load_dev_data(validation_file)
model = load_model(question_generator)
if save:
save_obj(datasets.dev_image_id_imagefeat_dict,
dev_imagefeat_dict_name)
save_obj(datasets.train_image_id_imagefeat_dict,
train_imagefeat_dict_name)
