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@ -4,22 +4,22 @@ Benyi Hu, Ren-Jie Song, Xiu-Shen Wei*, Yazhou Yao, Xian-Sheng Hua, Yuehu Liu
## Introduction
PyRetri (pronounced as [ˈperɪˈtriː]) is a unified deep learning based image retrieval toolbox based on PyTorch, which is designed for researchers and engineers.
PyRetri (pronounced as [ˈperɪˈtriː]) is a unified deep learning based unsupervised image retrieval toolbox based on PyTorch, which is designed for researchers and engineers.
![image](teaser_image/overview.png)
### Major Features
PyRetri is a versatile deep learning based image retrieval toolbox designed with simplicity and flexibility in mind.
PyRetri is a versatile deep learning based unsupervised image retrieval toolbox designed with simplicity and flexibility in mind.
- **Modular Design**: We decompose the deep learning based image retrieval into several stages and users can easily construct an image retrieval pipeline by selecting and combining different modules.
- **Modular Design**: We decompose the deep learning based unsupervised image retrieval into several stages and users can easily construct an image retrieval pipeline by selecting and combining different modules.
- **Flexible Loading**: The toolbox is able to adapt to load several types of model parameters, including parameters with the same keys and shape, parameters with different keys, and parameters with the same keys but different shapes.
- **Support of Multiple Methods**: The toolbox directly supports several popluar methods designed for deep learning based image retrieval, which is also suitable for person re-identification.
- **Support of Multiple Methods**: The toolbox directly supports several popluar methods designed for deep learning based unsupervised image retrieval, which is also suitable for person re-identification.
- **Configuration Search Tool**: We provide the configuration search tool to help users to find the optimal retrieval configuration with various hyper-parameters.
### Supported Methods
The toolbox supports popluar and prominent methods of image retrieval and users can also design and add their own modules.
The toolbox supports popluar and prominent methods of unsupervised image retrieval and users can also design and add their own modules.
- **Pre-processing**
- DirectResize, PadResize, ShorterResize
@ -58,7 +58,7 @@ If you use this toolbox in your research, please cite this project.
```
@article{PyRetri,
title = {PyRetri: A PyTorch-based Library for Image Retrieval by Deep Convolutional Neural Networks},
title = {PyRetri: A PyTorch-based Library for Unsupervised Image Retrieval by Deep Convolutional Neural Networks},
author = {Hu, Benyi and Song, Ren-Jie and Wei, Xiu-Shen and Yao, Yazhou and Hua, Xian-Sheng and Liu, Yuehu},
year = {2020}
}