evaluate_model.py 文件源码

def define_model(weights_path):
    '''
    Define model structure with weights.
    '''
    from resnet50 import ResNet50
    from keras.models import Model
    from keras.layers import Dense, GlobalAveragePooling2D


    resnet50_model = ResNet50()
    fc1000 = resnet50_model.get_layer('fc1000').output
    final_softmax = Dense(output_dim=2, activation='softmax')(fc1000)
    resnet50_finetune_1skip = Model(input=resnet50_model.input, output=final_softmax)
    resnet50_finetune_1skip.load_weights(weights_path)

    resnet50_finetune_1skip.compile(loss="categorical_crossentropy",
                                optimizer='nadam',
                                metrics=['accuracy'])

    return resnet50_finetune_1skip