自定义caffe模型的净手术 [英] net surgery on a custom caffe model

问题描述

我正在尝试修改caffe模型的权重，该模型是名为Deep Lab的caffe分支的一部分。尽管有关于如何进行网络手术的教程，当我尝试使用自定义caffemodel进行相同操作时，python内核始终死于以下行：

I'm trying to modify the weights of a caffemodel which is part of a caffe-branch called Deep Lab. Although there is a tutorial on how to do net surgery, when I try to do the same with my custom caffemodel the python kernel dies always on the following line:

# Load the original network and extract the fully connected layers' parameters.
net = caffe.Net('../models/deeplab/train.prototxt', 
                '../models/deeplab/train.caffemodel', 
                caffe.TRAIN)

我认为是因为pycaffe不知道其自定义图层，例如 ImageSegData ， Silence 和 SegAccuracy ，因此我从prototxt文件中删除了这些图层，但仍然删除了python内核当我尝试加载网络模型时，它一直在消亡。有人知道如何将这些权重加载到python中吗？

I think its because pycaffe doesn't know their custom layers such as ImageSegData, Silence and SegAccuracy so I removed these layers from the prototxt file, but still the python kernel keeps on dying when I try to load the network model. Does anyone know how to load these weights into python?

推荐答案

我已经找到了。我不得不从字面上删除每个自定义层，尤其是修改数据层，以便它可以读取所有输入图像，从而计算输入尺寸。

I found it already. I had literally to remove every custom layer and especially adapt the data layer such that it could read all the input images and thereby calculate the input dimensions.

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