yinboc / Prototypical Network Pytorch
Licence: mit
A re-implementation of "Prototypical Networks for Few-shot Learning"
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python
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Prototypical Network
A re-implementation of Prototypical Network.
With ConvNet-4 backbone on miniImageNet.
For deep backbones (ResNet), see Meta-Baseline.
Results
1-shot: 49.1% (49.4% in the paper)
5-shot: 66.9% (68.2% in the paper)
Environment
- python 3
- pytorch 0.4.0
Instructions
-
Download the images: https://drive.google.com/open?id=0B3Irx3uQNoBMQ1FlNXJsZUdYWEE
-
Make a folder
materials/imagesand put those images into it.
--gpu to specify device for program.
1-shot Train
python train.py
1-shot Test
python test.py
5-shot Train
python train.py --shot 5 --train-way 20 --save-path ./save/proto-5
5-shot Test
python test.py --load ./save/proto-5/max-acc.pth --shot 5
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