newnet.py 文件源码

def fcn_32s(input_dim, nb_classes=2):
    inputs = Input(shape=(input_dim,input_dim,3))
    vgg16 = VGG16(weights=None, include_top=False, input_tensor=inputs)
    pretrain_model_path = "../weights/vgg16_weights_tf_dim_ordering_tf_kernels_notop.h5"
    if not os.path.exists(pretrain_model_path):
        raise RuntimeError("No pretrained model loaded.")
    vgg16.load_weights(pretrain_model_path)
    x = Conv2D(filters=nb_classes,
               kernel_size=(1, 1))(vgg16.output)
    x = Conv2DTranspose(filters=nb_classes,
                        kernel_size=(64, 64),
                        strides=(32, 32),
                        padding='same',
                        activation='sigmoid',
                        kernel_initializer=initializers.Constant(bilinear_upsample_weights(32, nb_classes)))(x)
    model = Model(inputs=inputs, outputs=x)
    for layer in model.layers[:15]:
        layer.trainable = False
    return model