CNN.py

model = keras.models.Sequential([
    keras.layers.Conv2D(32, (3, 3), activation='relu', input_shape = [224, 224,3]),
    keras.layers.MaxPooling2D(),
    keras.layers.Conv2D(64, (2, 2), activation='relu'),
    keras.layers.MaxPooling2D(),
    keras.layers.Conv2D(64, (2, 2), activation='relu'),
    keras.layers.Flatten(),
    keras.layers.Dense(100, activation='relu'),
    keras.layers.Dense(2, activation ='softmax')
])

# print model summary 
print(model.summary())