角星中的resnet50和densenet121系综

Question

我想做一个resnet50和desnsenet121的合奏，但是得到了一个错误：

图断开:不能获得张量张量(“input_8:0”，shape=(?，224,224，3)，dtype=float32)在"input_8“层的值。没有问题地访问了以下前几个层：[]

下面是我的集合代码：

from keras import applications
from keras.layers import Dense, Dropout, Flatten, Conv2D, MaxPool2D
from keras.models import Model, Input
#from keras.engine.topology import Input
from keras.layers import Average

def resnet50():
    base_model = applications.resnet50.ResNet50(weights='imagenet', include_top=False, input_shape=(224, 224, 3))
    last = base_model.output
    x = Flatten()(last)
    x = Dense(2000, activation='relu')(x)
    preds = Dense(200, activation='softmax')(x)
    model = Model(base_model.input, preds)
    return model

def densenet121():
    base_model = applications.densenet.DenseNet121(weights='imagenet', include_top=False, input_shape=(224,224, 3))
    last = base_model.output
    x = Flatten()(last)
    x = Dense(2000, activation='relu')(x)
    preds = Dense(200, activation='softmax')(x)
    model = Model(base_model.input, preds)
    return model

resnet50_model = resnet50()
densenet121_model = densenet121()
ensembled_models = [resnet50_model,densenet121_model]
def ensemble(models,model_input):
    outputs = [model.outputs[0] for model in models]
    y = Average()(outputs)
    model = Model(model_input,y,name='ensemble')
    return model

model_input = Input(shape=(224,224,3))
ensemble_model = ensemble(ensembled_models,model_input)

我认为原因是当我将reset50和densenet121组合在一起时，它们有自己的输入层，尽管我使输入形状是相同的。不同的输入层会导致冲突。这只是我的猜测，我不知道如何解决

Answer 1

您可以在创建基本模型时设置input_tensor=model_input。

def resnet50(model_input):
    base_model = applications.resnet50.ResNet50(weights='imagenet', include_top=False, input_tensor=model_input)
    # ...

def densenet121(model_input):
    base_model = applications.densenet.DenseNet121(weights='imagenet', include_top=False, input_tensor=model_input)
    # ...

model_input = Input(shape=(224, 224, 3))
resnet50_model = resnet50(model_input)
densenet121_model = densenet121(model_input)

然后，基本模型将使用提供的model_input张量，而不是创建它们自己的独立输入张量。