小编asd*_*234的帖子

我正在尝试使用他们的教程将我自己的自定义图像数据集塑造成 Tensorflow 上预训练 MobileNet 模型的正确输入形状。我的代码：

batch_size = 256
epochs = 15
IMG_HEIGHT = 160
IMG_WIDTH = 160
BATCH_SIZE = 256
SHUFFLE_BUFFER_SIZE = 1000
traindir = pathlib.Path('/train')
valdir = pathlib.Path('/validation')
list_ds = tf.data.Dataset.list_files(str(traindir/'*/*'))
val_list_ds = tf.data.Dataset.list_files(str(valdir/'*/*'))
CLASS_NAMES = np.array([item.name for item in valdir.glob('*') if item.name != "LICENSE.txt"])
def get_label(file_path):
  # convert the path to a list of path components
  parts = tf.strings.split(file_path, os.path.sep)
  # The second to last is the class-directory
  return parts[-2] == CLASS_NAMES

def decode_img(img):
  # convert the …