model = keras.models.Sequential()

model.add(Conv2D(32, kernel_size=5, strides=2, activation='relu', input_shape=(268, 182, 3)))
model.add(Conv2D(64, kernel_size=3, strides=1, activation='relu'))

model.add(Dense(128, activation='relu'))
model.add(Dense(8, activation='softmax'))   # Final Layer using Softmax

model.compile(loss='categorical_crossentropy', optimizer='adam', metrics=['accuracy'])