classifier builder

imageclf.py

def imageclf2(input_shape):
    from tensorflow import keras as ks
    #from tensorflow.keras import regularizers
    model = ks.models.Sequential()
    #building architecture
    #Adding layers
    model.add(ks.layers.Conv2D(16,(6,6),
                               strides=2,
                               activation="relu",
                               padding='same',
                               name="layer1",
                               input_shape=input_shape))
    model.add(ks.layers.MaxPooling2D(pool_size=2))
    model.add(ks.layers.Conv2D(32,(3,3),strides=1,padding="same",activation="relu",name="layer2"))
    model.add(ks.layers.MaxPooling2D(pool_size=2,strides=2))
    model.add(ks.layers.Conv2D(64,(3,3),strides=1,padding="same",activation="relu",name="layer3"))
    model.add(ks.layers.MaxPooling2D(pool_size=2,strides=2))
    model.add(ks.layers.Conv2D(64,(3,3),strides=1,padding="same",activation="relu",name="layer4"))
    model.add(ks.layers.MaxPooling2D(pool_size=2,strides=2))
    
    
    model.add(ks.layers.Flatten())
    model.add(ks.layers.Dense(128,activation="relu",
                              name="layer5"))
    
    model.add(ks.layers.Dense(10,activation="softmax",
                              name="output"))#10 classes 
    model.summary()
    
    return model