小编LLT*_*eng的帖子

belos 是我的代码，用于确保文件夹中有图像，但 tf.keras.preprocessing.image_dataset_from_directory 返回未找到图像。我做错了什么？谢谢。

DATASET_PATH = pathlib.Path('C:\\Users\\xxx\\Documents\\images')
image_count = len(list(DATASET_PATH.glob('.\\*.jpg')))
print(image_count)

输出 = 2715

batch_size = 4
img_height = 32
img_width = 32

train_ds = tf.keras.preprocessing.image_dataset_from_directory(
    DATASET_PATH.name,
    validation_split=0.8,
    subset="training",
    seed=123,
    image_size=(img_height, img_width),
    batch_size=batch_size)

输出：

Found 0 files belonging to 0 classes.
Using 0 files for training.
Traceback (most recent call last):
  File ".\tensorDataPreProcessed.py", line 23, in <module>
    batch_size=batch_size)
  File "C:\Users\xxx\Anaconda3\envs\xxx\lib\site-packages\tensorflow\python\keras\preprocessing\image_dataset.py", line 200, in image_dataset_from_directory
    raise ValueError('No images found.')
ValueError: No images found.

我正在尝试加载从 pusher tfx 管道生成的 .pb 文件。我正在使用以下函数加载文件，但我从该函数中收到以下错误。请帮忙。

错误：

<ipython-input-40-af7ef7ac8a8b> in load_model()
      2     with tf.compat.v2.io.gfile.GFile('/home//saved_model.pb', "rb") as f:
      3         graph_def = tf.compat.v1.GraphDef()
----> 4         graph_def.ParseFromString(f.read())
      5 
      6     with tf.Graph().as_default() as graph:
DecodeError: Error parsing message

功能

def load_model():
    with tf.compat.v2.io.gfile.GFile('/home/saved_model.pb', "rb") as f:
        graph_def = tf.compat.v1.GraphDef()
        graph_def.ParseFromString(f.read())

    with tf.Graph().as_default() as graph:
        tf.import_graph_def(graph_def, name="")
    return graph

我有一个输出a = "[1,2,3]"，如何将它a = [1,2,3]从 Python 中的字符串转换为数组？

谢谢！