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A pytorch implementation of the "Selective Convolutional Descriptor Aggregation" algorithm
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dependabot[bot] 9780079ab1
Bump numpy from 1.17.3 to 1.22.0 
Bumps [numpy](https://github.com/numpy/numpy) from 1.17.3 to 1.22.0.
- [Release notes](https://github.com/numpy/numpy/releases)
- [Changelog](https://github.com/numpy/numpy/blob/main/doc/HOWTO_RELEASE.rst)
- [Commits](https://github.com/numpy/numpy/compare/v1.17.3...v1.22.0)

---
updated-dependencies:
- dependency-name: numpy
  dependency-type: direct:production
...

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requirements.txt Bump numpy from 1.17.3 to 1.22.0 2022-06-22 02:09:49 +00:00

README.md

SCDA_pytorch

A pytorch implementation of the "Selective Convolutional Descriptor Aggregation" algorithm

NOTE

cpu-only version

no in [1]

train_data_L31a(i,:) = train_data_L31a(i,:) ./ norm(train_data_L31a(i,:));

largestConnectComponent

Details

install requirements

  pip install -r requirements.txt;

On CUB and split dataset in CUB_200.py.

random split CUB-200-2011 results:

top1 top5
CUB 0.546 0.794

[1] Wei X S , Luo J H , Wu J , et al. Selective Convolutional Descriptor Aggregation for Fine-Grained Image Retrieval[J]. IEEE Transactions on Image Processing, 2017, 26(6):2868-2881.