项目作者: TreezzZ

项目描述 :
Source code for paper "Deep Hashing Network for Efficient Similarity Retrieval" on AAAI-2016
高级语言: Python
项目地址: git://github.com/TreezzZ/DHN_PyTorch.git
创建时间: 2020-01-04T08:24:14Z
项目社区:https://github.com/TreezzZ/DHN_PyTorch

开源协议:GNU General Public License v3.0

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Deep Hashing Network for Efficient Similarity Retrieval

REQUIREMENTS

pip install -r requirements.txt

  1. pytorch >= 1.0
  2. loguru

DATASETS

  1. CIFAR-10 Password: aemd
  2. NUS-WIDE Password: msfv
  3. Imagenet100 Password: xpab

USAGE

  1. usage: run.py [-h] [--dataset DATASET] [--root ROOT]
  2. [--code-length CODE_LENGTH] [--arch ARCH]
  3. [--batch-size BATCH_SIZE] [--lr LR] [--max-iter MAX_ITER]
  4. [--num-workers NUM_WORKERS] [--topk TOPK] [--gpu GPU]
  5. [--lamda LAMDA] [--seed SEED]
  6. [--evaluate-interval EVALUATE_INTERVAL]
  7. DHN_PyTorch
  8. optional arguments:
  9. -h, --help show this help message and exit
  10. --dataset DATASET Dataset name.
  11. --root ROOT Path of dataset
  12. --code-length CODE_LENGTH
  13. Binary hash code length.
  14. --arch ARCH CNN model name.(default: alexnet)
  15. --batch-size BATCH_SIZE
  16. Batch size.(default: 256)
  17. --lr LR Learning rate.(default: 1e-5)
  18. --max-iter MAX_ITER Number of iterations.(default: 500)
  19. --num-workers NUM_WORKERS
  20. Number of loading data threads.(default: 6)
  21. --topk TOPK Calculate map of top k.(default: all)
  22. --gpu GPU Using gpu.(default: False)
  23. --lamda LAMDA Hyper-parameter.(default: 1)
  24. --seed SEED Random seed.(default: 3367)
  25. --evaluate-interval EVALUATE_INTERVAL
  26. Evaluation interval.(default: 10)

EXPERIMENTS

CNN model: Alexnet.

cifar10: 1000 query images, 5000 training images, MAP@ALL.

nus-wide: Top 21 classes, 2100 query images, 10500 training images, MAP@5000.

imagenet100: Top 100 classes, 5000 query images, 10000 training images, MAP@1000.

bits 16 32 48 128
cifar10@ALL 0.7275 0.7353 0.7302 0.7386
nus-wide-tc21@5000 0.8194 0.8326 0.8396 0.8443
imagenet100@1000 0.2659 0.3703 0.4122 0.4743