def make_model_small(inshape, num_classes, weights_file=None):
model = Sequential()
model.add(KL.InputLayer(input_shape=inshape[1:]))
model.add(KL.Conv2D(32, (3, 3), padding='same'))
model.add(KL.Activation('relu'))
model.add(KL.Flatten())
# model.add(Dropout(0.5))
model.add(KL.Dense(num_classes))
model.add(KL.Activation('softmax'))
if weights_file is not None and os.path.exists(weights_file):
model.load_weights(weights_file)
return model
评论列表
文章目录