I want to create a dataset-variable as well as a labels-variable using the function tf.keras.preprocessing.image_dataset_from_directory (https://www.tensorflow.org/api_docs/python/tf/keras/preprocessing/image_dataset_from_directory).
The documentation states:
Returns:
A tf.data.Dataset object.
If label_mode is None, it yields
float32 tensors of shape (batch_size, image_size[0], image_size[1],
num_channels), encoding images (see below for rules regarding
num_channels).
Otherwise, it yields a tuple (images, labels), where
images has shape (batch_size, image_size[0], image_size[1],
num_channels), and labels follows the format described below.
My code is the following:
train_ds, labels = tf.keras.preprocessing.image_dataset_from_directory(
directory = data_dir,
labels='inferred',
label_mode = "int",
validation_split=0.2,
subset="training",
seed=123,
image_size=(img_height, img_width),
batch_size=batch_size)
I expect to get a tuple as return values, but instead I get the error message:
Found 2160 files belonging to 2160 classes.
Using 1728 files for training.
---------------------------------------------------------------------------
ValueError Traceback (most recent call last)
<ipython-input-168-ed9d42ed2ab9> in <module>
7 seed=123,
8 image_size=(img_height, img_width),
----> 9 batch_size=batch_size)
ValueError: too many values to unpack (expected 2)
When I save the output in one variable (just train_ds) and I inspect the variable, I get the following output:
<BatchDataset shapes: ((None, 120, 30, 3), (None,)), types: (tf.float32, tf.int32)>
How can I access the two tuples inside seperatly?
question from:
https://stackoverflow.com/questions/65835387/valueerror-too-many-values-to-unpack-expected-2-when-using-tf-keras-preproces 
