model.py

# create a model


def create_model():


   METRICS = [
   'accuracy',
   tf.keras.metrics.Precision(name='precision'),
   tf.keras.metrics.Recall(name='recall'),
   tf.keras.metrics.AUC(name='AUC'),
   ]


   model = Sequential([Conv2D(16, (3,3), input_shape=(IMG_SIZE[0], IMG_SIZE[1], 3), activation="relu"),
                              BatchNormalization(),
                              MaxPooling2D(2,2),
                              Dropout(0.3),


                              Flatten(),
                              Dense(64, activation="relu"),
                              Dense(4, activation="softmax"),
                              ])
   model.compile(optimizer="adamax", loss="categorical_crossentropy", metrics=METRICS)


   return model