我在哪里可以找到经过训练的模型(如 googleNet 的输出)与真实类别标签之间的标签映射? [英] Where can I find the label map between trained model like googleNet's output to there real class label?

问题描述

大家，我是咖啡新手.目前，我尝试使用从模型动物园下载的经过训练的 GoogleNet 对一些图像进行分类.然而，网络的输出似乎是一个向量而不是真正的标签(如狗、猫).我在哪里可以找到经过训练的模型(如 googleNet 的输出)与其真实类别标签之间的标签映射?谢谢.

everyone, I am new to caffe. Currently, I try to use the trained GoogleNet which was downloaded from model zoo to classify some images. However, the network's output seem to be a vector rather than real label(like dog, cat). Where can I find the label-map between trained model like googleNet's output to their real class label? Thanks.

推荐答案

如果你从 git 得到 caffe 你应该在 data/ilsvrc12 文件夹中找到一个 shell 脚本 get_ilsvrc_aux.sh.
此脚本应下载用于 ilsvrc(用于大规模图像识别挑战的 imagenet 子集)训练的几个文件.

If you got caffe from git you should find in data/ilsvrc12 folder a shell script get_ilsvrc_aux.sh.
This script should download several files used for ilsvrc (sub set of imagenet used for the large scale image recognition challenge) training.

将要下载的最有趣的文件(对你来说)是 synset_words.txt，这个文件有 1000 行，网络识别的每个类一行.
行的格式为

The most interesting file (for you) that will be downloaded is synset_words.txt, this file has 1000 lines, one line per class identified by the net.
The format of the line is

nXXXXXXXX 类描述

nXXXXXXXX description of class

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