def load(self):
self.__trainSet = load.Data(0.0, 0.64) # 按 0.64 的比例划分训练集
self.__valSet = load.Data(0.64, 0.8) # 按 0.16 的比例划分校验集
self.__testSet = load.Data(0.8) # 按 0.2 的比例划分测试集
self.__trainSize = self.__trainSet.getSize()
self.__valSize = self.__valSet.getSize()
self.__testSize = self.__testSet.getSize()
def load(self):
sort_list = load.Data.get_sort_list()
self.__train_set = load.Data(0.0, 0.9, 'train', sort_list)
self.__val_set = load.Data(0.9, 1.0, 'validation', sort_list)
# self.__test_set = load.Data(0.8, 1.0, 'test', sort_list)
self.__train_size = self.__train_set.get_size()
self.__val_size = self.__val_set.get_size()
def load(self):
self.__train_set = load.Data(0.0, 0.8, 'train', self.IMAGE_SHAPE)
self.__val_set = load.Data(0.8, 1.0, 'validation', self.IMAGE_SHAPE)
# self.__test_set = load.Data(0.8, 1.0, 'test')
self.__train_set.start_thread()
self.__val_set.start_thread()
self.__train_size = self.__train_set.get_size()
self.__val_size = self.__val_set.get_size()
def load(self):
# sort_list = load.Data.get_sort_list()
self.__train_set = load.Data(0.0, 0.8, 'train')
self.__val_set = load.Data(0.8, 1.0, 'validation')
# self.__test_set = load.Data(0.8, 1.0, 'test')
self.__train_set.start_thread()
self.__val_set.start_thread()
self.__train_size = self.__train_set.get_size()
self.__val_size = self.__val_set.get_size()
def __init__(self):
self.__oData = load.Data()
def load(self):
self.data = load.Data(self.TRAIN_DATA_START_RATIO,
self.TRAIN_DATA_END_RATIO)
'coefficient of l1 norm, default: 0.0')
# IBIS
tf.flags.DEFINE_string('paired_image_path',
'/ASD/Autism/IBIS2/IBIS_DL_Prediction/Data_preprocessed/pickle/paired_6_12_HR_QC',
# '/Users/yusenlin/Documents/github/pickledata_test/data_tmp',
'where pickcle data saved. format:[x,y,path]')
tf.flags.DEFINE_string('load_model', None,
'folder of saved model that you wish to continue training (e.g. 20170602-1936), default: None')
tf.flags.DEFINE_string('weight_dir', '/ASD/Autism/IBIS2/IBIS_DL_Prediction/Code/model_weights/unet_3d.pkl',
'the dir of weight file for feature extractor')
# IBIS
data_train = loader.Data(os.path.join(FLAGS.paired_image_path, 'train', 't1'), 'train')
data_val = loader.Data(os.path.join(FLAGS.paired_image_path, 'val', 't1'), 'val')
data_test = loader.Data(os.path.join(FLAGS.paired_image_path, 'test', 't1'), 'test')
# shuffle data
indices = np.array(range(data_train.len))
random.seed(10)
random.shuffle(indices)
data_train.set_path_list(indices)
# start fetching data
data_train.start_thread()
data_val.start_thread()
data_test.start_thread()
# calculate epoch
