问题
I have the output Tensor of a forward pass for a Facebook implementation of the ResNet model with a cat image. That is a 1000-dimensional Tensor with the classification probabilities. Using torch.topk I can obtain the top-5 probabilities and their indexes in the output tensor. Now I want to see the human-readable labels for those most-probable indexes.
I searched online for the list of labels (which apparently are also called sysnets) and only found this: http://image-net.org/challenges/LSVRC/2015/browse-synsets
I put those labels in a file using line numbers as the label index and when I run the network with two different cat images, I get "screwdriver" as the top guess for both. If I sort the label file alphabetically, I get "cinema" for both.
This appears to be a problem with converting index to label, right? So...the question is: How can I properly map index in network output tensor to Imagenet label?
回答1:
Found this tutorial on training ConvNets on ImageNet by Dato and at the end it contains the correct mapping. Reporting it here for the record:
{
0: 'tench, Tinca tinca',
1: 'goldfish, Carassius auratus',
2: 'great white shark, white shark, man-eater, man-eating shark, Carcharodon carcharias',
3: 'tiger shark, Galeocerdo cuvieri',
4: 'hammerhead, hammerhead shark',
5: 'electric ray, crampfish, numbfish, torpedo',
6: 'stingray',
7: 'cock',
8: 'hen',
9: 'ostrich, Struthio camelus',
10: 'brambling, Fringilla montifringilla',
... [truncated for space]
990: 'buckeye, horse chestnut, conker',
991: 'coral fungus',
992: 'agaric',
993: 'gyromitra',
994: 'stinkhorn, carrion fungus',
995: 'earthstar',
996: 'hen-of-the-woods, hen of the woods, Polyporus frondosus, Grifola frondosa',
997: 'bolete',
998: 'ear, spike, capitulum',
999: 'toilet tissue, toilet paper, bathroom tissue'
}
Full mapping here: https://gist.github.com/maraoz/388eddec39d60c6d52d4
来源：https://stackoverflow.com/questions/35528905/get-imagenet-label-for-a-specific-index-in-the-1000-dimensional-output-tensor-in