Tensorflow 2: how to connect two layers from saved models?

I have two saved models. I want to load and connect the output from model-1 to the input for model-2:

# Load model1
model1 = tf.keras.models.load_model('/path/to/model1.h5')

# Load model2
model2 = tf.keras.models.load_model('/path/to/model2.h5')

# get the input/output tensors
model1Output = model1.output
model2Input = model2.input

# reshape to fit
x = Reshape((imageHeight, imageWidth, 3))(model1Output)

# how do I set 'x' as the input to model2?

# this is the combined model I want to train
model = models.Model(inputs=model1.input, outputs=model2.output)

I know you can set the Input when you instantiate a Layer by passing the input as a parameter (x = Input(shape)). But how do you set the Input, in my case x, on an existing layer? I've looked at the documentation for the Layer class here, but I can't see this mentioned?

Edit:

Adding the summaries of both models...

Here is the top of model1:

__________________________________________________________________________________________________
conv2d_transpose_3 (Conv2DTrans (None, 304, 304, 16) 4624        activation_14[0][0]              
__________________________________________________________________________________________________
dropout_7 (Dropout)             (None, 304, 304, 32) 0           concatenate[3][0]                
__________________________________________________________________________________________________
conv2d_17 (Conv2D)              (None, 304, 304, 16) 4624        dropout_7[0][0]                  
__________________________________________________________________________________________________
batch_normalization_17 (BatchNo (None, 304, 304, 16) 64          conv2d_17[0][0]                  
__________________________________________________________________________________________________
activation_16 (Activation)      (None, 304, 304, 16) 0           batch_normalization_17[0][0]     
__________________________________________________________________________________________________
conv2d_18 (Conv2D)              (None, 304, 304, 10) 170         activation_16[0][0]              
==================================================================================================

And here is the input of model2:

__________________________________________________________________________________________________
Layer (type)                    Output Shape         Param #     Connected to                     
==================================================================================================
input_1 (InputLayer)            [(None, 299, 299, 3) 0                                            
__________________________________________________________________________________________________
block1_conv1 (Conv2D)           (None, 149, 149, 32) 864         input_1[0][0]                    
__________________________________________________________________________________________________
block1_conv1_bn (BatchNormaliza (None, 149, 149, 32) 128         block1_conv1[0][0]               
__________________________________________________________________________________________________
block1_conv1_act (Activation)   (None, 149, 149, 32) 0           block1_conv1_bn[0][0]            
__________________________________________________________________________________________________
block1_conv2 (Conv2D)           (None, 147, 147, 64) 18432       block1_conv1_act[0][0]           
__________________________________________________________________________________________________

I need the output of conv2d_18 in model1 to be fed as the input to block1_conv1 in model2.