[Python] I am getting error like "Input 1 of layer "model_5" is incompatible with the layer:...

I am trying to fuse features of two image inputs of shape (299, 299, 3), (224, 224, 3) and am getting shape errors.

Here is my code


from tensorFlow.keras.applications.inception_v3 import InceptionV3
from tensorflow.keras.applications.vgg16 import VGG16
import tensorflow as tf
from tensorflow.keras import layers, Input

inp_pre_trained_model = InceptionV3( include_top=False)
inp_pre_trained_model.trainable=False
inp_input=tf.keras.Input(shape=(299,299,3),name="input_layer_inception_V3")
inp_x=inp_pre_trained_model (inp_input)
inp_x=layers.GlobalAveragePooling2D(name="global_average_pooling_layer_inception_v3")(inp_x)
vgg_pre_trained_model = VGG16( include_top=False)
vgg_pre_trained_model.trainable=False
vgg_input=tf.keras.Input(shape=(224,224,3),name="input_layer_VGG_16")

vgg_x=vgg_pre_trained_model(vgg_input)
vgg_x=layers.GlobalAveragePooling2D(name="global_average_pooling_layer_vgg_16")(vgg_x)
x=tf.keras.layers.concatenate([inp_x,vgg_x],axis=-1)
x = tf.keras.layers.Flatten()(x)
outputs=tf.keras.layers.Dense(5,activation="softmax", name= "output_layer") (x)
model=tf.keras.Model(inputs=[inp_input,vgg_input],outputs=outputs)


model.summary()


My model summary


Model: "model_9"
__________________________________________________________________________________________________
Layer (type) Output Shape Param # Connected to
==================================================================================================
input_layer_inception_V3 (Inpu [(None, 224, 224, 3 0 []
tLayer) )]

input_layer_VGG_16 (InputLayer [(None, 299, 299, 3 0 []
) )]

inception_v3 (Functional) (None, None, None, 21802784 ['input_layer_inception_V3[0][0]'
2048) ]

vgg16 (Functional) (None, None, None, 14714688 ['input_layer_VGG_16[0][0]']
512)

global_average_pooling_incepti (None, 2048) 0 ['inception_v3[0][0]']
on (GlobalAveragePooling2D)

global_average_pooling_vgg (Gl (None, 512) 0 ['vgg16[0][0]']
obalAveragePooling2D)

concatenate_71 (Concatenate) (None, 2560) 0 ['global_average_pooling_inceptio
n[0][0]',
'global_average_pooling_vgg[0][0
]']

output_layer (Dense) (None, 5) 12805 ['concatenate_71[0][0]']

==================================================================================================
Total params: 36,530,277
Trainable params: 12,805
Non-trainable params: 36,517,472


compiler

model.compile(loss="sparse_categorical_crossentropy",optimizer=tf.keras.optimizers.Adam(learning_rate=0.001),metrics=["accuracy"])

train = tf.data.Dataset.zip((cache_train_data, ceced_train_data))
test = tf.data.Dataset.zip((cache_test_data, ceced_test_data))
train_dataset = train.prefetch(tf.data.AUTOTUNE)
test_dataset = test.prefetch(tf.data.AUTOTUNE)

train_dataset, test_dataset


--->(<PrefetchDataset element_spec=((TensorSpec(shape=(None, 224, 224, 3), dtype=tf.float32, name=None), TensorSpec(shape=(None, 5), dtype=tf.float32, name=None)), (TensorSpec(shape=(None, 224, 224, 3), dtype=tf.float32, name=None), TensorSpec(shape=(None, 5), dtype=tf.float32, name=None)))>,
<PrefetchDataset element_spec=((TensorSpec(shape=(None, 224, 224, 3), dtype=tf.float32, name=None), TensorSpec(shape=(None, 5), dtype=tf.float32, name=None)), (TensorSpec(shape=(None, 224, 224, 3), dtype=tf.float32, name=None), TensorSpec(shape=(None, 5), dtype=tf.float32, name=None)))>)

fit the model

model_history = model.fit(train_dataset,
steps_per_epoch=len(train_dataset),
epochs=3,
validation_data=test_dataset,
validation_steps=len(test_dataset))



error ValueError: in user code:

File "/usr/local/lib/python3.7/dist-packages/keras/engine/training.py", line 1051, in train_function *
return step_function(self, iterator)
File "/usr/local/lib/python3.7/dist-packages/keras/engine/training.py", line 1040, in step_function **
outputs = model.distribute_strategy.run(run_step, args=(data,))
File "/usr/local/lib/python3.7/dist-packages/keras/engine/training.py", line 1030, in run_step **
outputs = model.train_step(data)
File "/usr/local/lib/python3.7/dist-packages/keras/engine/training.py", line 889, in train_step
y_pred = self(x, training=True)
File "/usr/local/lib/python3.7/dist-packages/keras/utils/traceback_utils.py", line 67, in error_handler
raise e.with_traceback(filtered_tb) from None
File "/usr/local/lib/python3.7/dist-packages/keras/engine/input_spec.py", line 264, in assert_input_compatibility
raise ValueError(f'Input {input_index} of layer "{layer_name}" is '

ValueError: Input 1 of layer "model_9" is incompatible with the layer: expected shape=(None, 299, 299, 3), found shape=(None, 5)

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