how to use keras model .hdf5 to predict image in siamese neural network with cnn ?

Question

im newbie in keras and neural network.

I have done the train process and got the model with the .h5 format

the neural network that I use is the siamese convolutional neural network.

when validating, the predicted image is a random image from my test folder.

i use this when test

```

test_alphabets = glob('{}/TEST/*'.format(dataset_dirname))

testset={}

for alph in test_alphabets:

    dirs = glob('{}/*'.format(alph))

    alphabet = {}

    for dirname in dirs:

        alphabet[dirname] = glob('{}/*'.format(dirname))

    testset[alph] = alphabet        

```

then, display the result with

```

display_validation_test(siamese_model1, testset)

```

How do I do the test process by inputting the image I want, then displaying the appropriate image using the .h5 model earlier?