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