Giter Site home page Giter Site logo

yaoq / batch-feature-erasing-network Goto Github PK

View Code? Open in Web Editor NEW

This project forked from daizuozhuo/batch-dropblock-network

2.0 2.0 1.0 25 KB

Official source code of Batch Feature Erasing for Person Re-identification and Beyond

License: MIT License

Python 100.00%

batch-feature-erasing-network's Introduction

Batch Feature Erasing for Person Re-identification and Beyond

Official source code of paper https://arxiv.org/abs/1811.07130

Setup running environment

This project requires python3, cython, torch, torchvision, scikit-learn, tensorboardX, fire. The baseline source code is borrowed from https://github.com/L1aoXingyu/reid_baseline.

Prepare dataset

Create a directory to store reid datasets under this repo via
```bash
cd reid
mkdir data
```
For market1501 dataset, 
1. Download Market1501 dataset to `data/` from http://www.liangzheng.org/Project/project_reid.html
2. Extract dataset and rename to `market1501`. The data structure would like:
```
market1501/
    bounding_box_test/
    bounding_box_train/
    query/
```
For CUHK03 dataset,
1. Download CUHK03-NP dataset from https://github.com/zhunzhong07/person-re-ranking/tree/master/CUHK03-NP 
2. Extract dataset and rename folers inside it to cuhk-detect and cuhk-label.
For DukeMTMC-reID dataset,
Dowload from https://github.com/layumi/DukeMTMC-reID_evaluation

Results

Dataset CUHK03-Label CUHK03-Detect DukeMTMC re-ID Market1501
Rank-1 75.0 72.1 88.7 94.4
mAP 70.9 67.9 75.8 85.0
model aliyun aliyun aliyun aliyun

You can download the pre-trained models from the above table and evaluate on person re-ID datasets. For example, to evaluate CUHK03-Label dataset, you can download the model to './pytorch-ckpt/cuhk_label_bfe' directory and run the following command:

python3 main_reid.py train --save_dir='./pytorch-ckpt/cuhk_label_bfe' --model_name=bfe --train_batch=32 --test_batch=32 --dataset=cuhk-label  --pretrained_model='./pytorch-ckpt/cuhk_label_bfe/750.pth.tar' --evaluate

batch-feature-erasing-network's People

Contributors

daizuozhuo avatar

Stargazers

 avatar  avatar

Watchers

 avatar  avatar

Forkers

swg209

Recommend Projects

  • React photo React

    A declarative, efficient, and flexible JavaScript library for building user interfaces.

  • Vue.js photo Vue.js

    ๐Ÿ–– Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.

  • Typescript photo Typescript

    TypeScript is a superset of JavaScript that compiles to clean JavaScript output.

  • TensorFlow photo TensorFlow

    An Open Source Machine Learning Framework for Everyone

  • Django photo Django

    The Web framework for perfectionists with deadlines.

  • D3 photo D3

    Bring data to life with SVG, Canvas and HTML. ๐Ÿ“Š๐Ÿ“ˆ๐ŸŽ‰

Recommend Topics

  • javascript

    JavaScript (JS) is a lightweight interpreted programming language with first-class functions.

  • web

    Some thing interesting about web. New door for the world.

  • server

    A server is a program made to process requests and deliver data to clients.

  • Machine learning

    Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.

  • Game

    Some thing interesting about game, make everyone happy.

Recommend Org

  • Facebook photo Facebook

    We are working to build community through open source technology. NB: members must have two-factor auth.

  • Microsoft photo Microsoft

    Open source projects and samples from Microsoft.

  • Google photo Google

    Google โค๏ธ Open Source for everyone.

  • D3 photo D3

    Data-Driven Documents codes.