import os
ROOT_DIR = os.path.abspath(os.path.curdir)
DATA_DIR = os.path.join(ROOT_DIR, 'data')
# execute preprocess for train
from rapid_tsa_python import exec_preprocess
train_label_path = os.path.join(DATA_DIR, 'train_label_cls.lab')
preprocess_def_path = os.path.join(DATA_DIR, 'preprocess_cls.json')
exec_preprocess(preprocess_def_path, label_path=train_label_path)
# execute train
from rapid_tsa_python import exec_train
train_preprocessed_label_path = os.path.join(DATA_DIR, 'train_label_cls_preprocessed.lab')
train_parameter_conf_path = os.path.join(DATA_DIR, 'train_param.conf')
model_dir = os.path.join(ROOT_DIR, 'model')
exec_train('cls', '1DCNN', train_preprocessed_label_path, model_dir,
param_conf_path=train_parameter_conf_path)
# execute preprocess for predict
predict_label_path = os.path.join(DATA_DIR, 'predict_label_cls.lab')
exec_preprocess(preprocess_def_path, label_path=predict_label_path)
# execute predict
from rapid_tsa_python import exec_predict
predict_preprocessed_label_path = os.path.join(DATA_DIR, 'predict_label_cls_preprocessed.lab')
result_dir = os.path.join(ROOT_DIR, 'result')
exec_predict(model_dir, label_path=predict_preprocessed_label_path, output_dir=result_dir)