How to fix the error when data augmenting TensorFlow training data?-CodePudding

I am trying to data augment my TensorFlow model's training data. My model runs without data augmentation. I want to augment training data to improve results. This is my attempt:

from tensorflow.keras.preprocessing.image import ImageDataGenerator
 
train_datagen = ImageDataGenerator(
    rescale=1./255,
    shear_range=0.2,
    zoom_range=0.2,
    horizontal_flip=True)
 
test_datagen = ImageDataGenerator(rescale=1./255)
 
train_generator = train_datagen.flow_from_directory(
    directory_testData,
    #validation_split=0.2,
    target_size=(150, 150),
    batch_size=32,
    class_mode='binary')
 
validation_generator = test_datagen.flow_from_directory(
    directory_testData,
    #validation_split=0.2,
    target_size=(150, 150),
    batch_size=32,
    class_mode='binary')
 
model = create_functionalModel()
 
model.fit(
    train_generator,
    steps_per_epoch=2000,
    epochs=50,
    validation_data=validation_generator,
    validation_steps=800)

I then ran it and am getting these errors:

---------------------------------------------------------------------------
InvalidArgumentError                      Traceback (most recent call last)
<ipython-input-25-1c89b4a3fc84> in <module>()
     30     epochs=50,
     31     validation_data=validation_generator,
---> 32     validation_steps=800)

 
1 frames
/usr/local/lib/python3.7/dist-packages/tensorflow/python/eager/execute.py in quick_execute(op_name, num_outputs, inputs, attrs, ctx, name)
     57     ctx.ensure_initialized()
     58     tensors = pywrap_tfe.TFE_Py_Execute(ctx._handle, device_name, op_name,
---> 59                                         inputs, attrs, num_outputs)
     60   except core._NotOkStatusException as e:
     61     if name is not None:

InvalidArgumentError:  Input to reshape is a tensor with 663552 values, but the requested shape requires a multiple of 30976
     [[node model_4/flatten_4/Reshape
 (defined at /usr/local/lib/python3.7/dist-packages/keras/layers/core/flatten.py:96)
]] [Op:__inference_train_function_4555]

It seems that this issue is related to the input shapes required by my model. Can you please help me understand how to resolve this issue? Thank you.

CodePudding user response：

Your model requires an input of shape (180, 180) But you are resizing your images to (150, 150).

Changing:

target_size=(150, 150),

To:

target_size=(180, 180),

Should fix it.