将 BatchDataset 与 Keras VGG16 连接 preprocess_input

Question

我正在使用 tf.keras.preprocessing.image_dataset_from_directory 得到一个 BatchDataset，其中数据集有 10 个类。

我正在尝试将此 BatchDataset 与 Keras VGG16 (docs) 网络集成。来自文档：

Note: each Keras Application expects a specific kind of input preprocessing. For VGG16, call tf.keras.applications.vgg16.preprocess_input on your inputs before passing them to the model.

但是，我正在努力让这个 preprocess_input 与 BatchDataset 一起工作。 你能帮我弄清楚如何连接这两个点吗？

请看下面的代码：

train_ds = tf.keras.preprocessing.image_dataset_from_directory(train_data_dir, image_size=(224, 224))
train_ds = tf.keras.applications.vgg16.preprocess_input(train_ds)

这将抛出 TypeError: 'BatchDataset' object is not subscriptable:

Traceback (most recent call last):
  ...
  File "/path/to/venv/lib/python3.10/site-packages/keras/applications/vgg16.py", line 232, in preprocess_input
    return imagenet_utils.preprocess_input(
  File "/path/to/venv/lib/python3.10/site-packages/keras/applications/imagenet_utils.py", line 117, in preprocess_input
    return _preprocess_symbolic_input(
  File "/path/to/venv/lib/python3.10/site-packages/keras/applications/imagenet_utils.py", line 278, in _preprocess_symbolic_input
    x = x[..., ::-1]
TypeError: 'BatchDataset' object is not subscriptable

来自 TypeError: 'DatasetV1Adapter' object is not subscriptable (from BatchDataset not subscriptable when trying to format Python dictionary as table) 建议使用：

train_ds = tf.keras.applications.vgg16.preprocess_input(
    list(train_ds.as_numpy_iterator())
)

然而，这也失败了：

Traceback (most recent call last):
  ...
  File "/path/to/venv/lib/python3.10/site-packages/keras/applications/vgg16.py", line 232, in preprocess_input
    return imagenet_utils.preprocess_input(
  File "/path/to/venv/lib/python3.10/site-packages/keras/applications/imagenet_utils.py", line 117, in preprocess_input
    return _preprocess_symbolic_input(
  File "/path/to/venv/lib/python3.10/site-packages/keras/applications/imagenet_utils.py", line 278, in _preprocess_symbolic_input
    x = x[..., ::-1]
TypeError: list indices must be integers or slices, not tuple

这都是使用 Python==3.10.3 和 tensorflow==2.8.0。

我怎样才能让它工作？提前谢谢你。

Answer 1

好的，我明白了。我需要传递 tf.Tensor，而不是 tf.data.Dataset。可以通过遍历 Dataset.

得到 Tensor

这可以通过几种方式完成：

train_ds = tf.keras.preprocessing.image_dataset_from_directory(...)

# Option 1
batch_images = next(iter(train_ds))[0]
preprocessed_images = tf.keras.applications.vgg16.preprocess_input(batch_images)

# Option 2:
for batch_images, batch_labels in train_ds:
    preprocessed_images = tf.keras.applications.vgg16.preprocess_input(batch_images)

如果将选项2转换成生成器，可以直接传入下游model.fit。干杯！

将 BatchDataset 与 Keras VGG16 连接 preprocess_input

Connecting BatchDataset with Keras VGG16 preprocess_input

python

deep-learning

keras

tensorflow

vgg-net