keras 2.1.5/TF 后端
我尝试使用 lambda 层进行图像预处理(通过函数)
型号:
from keras.applications.resnet50 import preprocess_input
base_model = keras.applications.resnet50.ResNet50(include_top=False, input_shape=(224, 224, 3))
model = Sequential()
model.add(Lambda(preprocess_input, name='Input_Image', input_shape=(224, 224, 3))
model.add(base_model)
model.add(GlobalAveragePooling2D())
model.add(Dense(len(classes), activation="softmax"))
我用“custom_objects”调用了 load_model
from keras.models import load_model
model = load_model(h5_weights, custom_objects={'preprocess_input': preprocess_input})
但随后出现错误
File "/usr/local/lib/python2.7/dist-packages/keras/layers/core.py", line 663, in call
return self.function(inputs, **arguments)
File "/usr/local/lib/python2.7/dist-packages/keras/applications/imagenet_utils.py", line 177, in preprocess_input
return _preprocess_symbolic_input(x, data_format=data_format,
NameError: global name '_preprocess_symbolic_input' is not defined
未定义的函数:
_preprocess_symbolic_input
在
中File "/usr/local/lib/python2.7/dist-packages/keras/applications/imagenet_utils.py"
有什么建议吗？
最佳答案
将 _preprocess_symbolic_input 也放入 custom_objects 中。
custom_objects = {
'preprocess_input': preprocess_input,
'_preprocess_symbolic_input': keras.applications.imagenet_utils._preprocess_symbolic_input
}
model = load_model(h5_weights, custom_objects=custom_objects)
关于keras - lambda 层中的 load_model 错误为 "function=preprocess_input"(Keras)，我们在Stack Overflow上找到一个类似的问题： https://stackoverflow.com/questions/49568797/