pytorch_deephash

Introduction

This is the Pytorch implementation of Deep Learning of Binary Hash Codes for Fast Image Retrieval, and can achieve more than 93% mAP in CIFAR10 dataset.

Environment

Pytorch 1.4.0

torchvision 0.5.0

tqdm

numpy

Training

python train.py

You will get trained models in model folder by default, and models' names are their test accuracy.

Evaluation

python evaluate.py --pretrained {your saved model name in model folder by default}

Tips

1. If using Windows, keep num_works zero

2. There are some other args, which you can get them by adding '-h' or reading the code.