问题检索值 decode_predictions` 需要一批预测

Question

我有一个预训练模型，试图移除一个层并对新模型执行预测。但是检索错误。

model = applications.VGG16(include_top=False, input_shape=(224, 224, 3), weights='imagenet') 
layers = [l for l in model.layers]
x = layers[9].output
x = layers[11](x)
x = layers[12](x)
x = layers[13](x)
x = layers[14](x)
x = layers[15](x)
x = layers[16](x)
x = layers[17](x)
x = layers[18](x)

result_model = Model(inputs=layers[0].input, outputs=x)
img='/content/elephant.jpg'
img = image.load_img(img, target_size=(224, 224))
x = image.img_to_array(img)
x = np.expand_dims(x, axis=0)
x = preprocess_input(x)
preds = result_model.predict(x)
print('Predicted:', decode_predictions(preds, top=3)[0])

错误

  ValueError: `decode_predictions` expects a batch of predictions (i.e. a 2D array of shape (samples, 1000)). Found array with shape: (1, 14, 14, 512)

Answer 1

您的神经网络没有输出层。 decode_predictions 无法解码卷积层的输出，这是您在执行 include_top=False 时得到的。这样做：

model = applications.VGG16(include_top=True, input_shape=(224, 224, 3), 
                           weights='imagenet')