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I'm using the pretrained imagenet model provided along the caffe (CNN) library ('bvlc_reference_caffenet.caffemodel'). I can output a 1000 dim vector of object scores for any images using this model.
However I don't know what the actual object categories are. Did someone find a file, where the corresponding object categories are listed?
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pre-trained model (. caffemodel) — binary file that stores weights, biases and gradients for each layer of the network (here for more details) model definition (. prototxt) file that contains structure of the network being used.
A CAFFEMODEL file is a machine learning model created by Caffe. It contains an image classification or image segmentation model that has been trained using Caffe. CAFFEMODEL files are created from . PROTOTXT files.
Caffe is a free, open-source framework for CNN and DL.
Caffe models are end-to-end machine learning engines. The net is a set of layers connected in a computation graph – a directed acyclic graph (DAG) to be exact. Caffe does all the bookkeeping for any DAG of layers to ensure correctness of the forward and backward passes.
You should look for the file 'synset_words.txt' it has 1000 line each line provides a description of a different class.
For more information on how to get this file (and some others you might need) you can read this.
If you want all the labels to be ready-for-use in Matlab, you can read the txt file into a cell array (a cell per class):
C = textread('/path/to/synset_words.txt','%s','delimiter','\n');
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