print("Loading vgg19 weights...")
 
    vgg_model = VGG19(include_top=False, weights="imagenet")
 
    from_vgg = dict()  # 因为模型定义中的layer的名字与原始vgg名字不同，所以需要调整
    from_vgg["conv1_1"] = "block1_conv1"
    from_vgg["conv1_2"] = "block1_conv2"
    from_vgg["conv2_1"] = "block2_conv1"
    from_vgg["conv2_2"] = "block2_conv2"
    from_vgg["conv3_1"] = "block3_conv1"
    from_vgg["conv3_2"] = "block3_conv2"
    from_vgg["conv3_3"] = "block3_conv3"
    from_vgg["conv3_4"] = "block3_conv4"
    from_vgg["conv4_1"] = "block4_conv1"
    from_vgg["conv4_2"] = "block4_conv2"
 
    for layer in model.layers:
      if layer.name in from_vgg:
        vgg_layer_name = from_vgg[layer.name]
        layer.set_weights(vgg_model.get_layer(vgg_layer_name).get_weights())
        print("Loaded VGG19 layer: " + vgg_layer_name)

densenet.load_weights("model/densenet_weight/densenet_bottom.h5")
# densenet.save_weights("densenet_bottom.h5")
 
# print(densenet.weights)# 获得模型所有权值
t=densenet.get_layer("densenet_conv1/bn")
print(t)
print(densenet.get_weights()[2])