https://github.com/bupt-ai-cz/PGDF

Sample Prior Guided Robust Model Learning to Suppress Noisy Labels
https://github.com/bupt-ai-cz/PGDF

computer-vision deep-learning image-classification noisy-labels

Last synced: about 2 months ago
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Sample Prior Guided Robust Model Learning to Suppress Noisy Labels

• Host: GitHub
• URL: https://github.com/bupt-ai-cz/PGDF
• Owner: bupt-ai-cz
• Created: 2021-12-03T08:06:38.000Z (about 3 years ago)
• Default Branch: main
• Last Pushed: 2022-03-18T08:43:24.000Z (almost 3 years ago)
• Last Synced: 2024-08-02T15:26:53.966Z (5 months ago)
• Topics: computer-vision, deep-learning, image-classification, noisy-labels
• Language: Python
• Homepage:
• Size: 33.2 KB
• Stars: 31
• Watchers: 3
• Forks: 4
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

        
# PGDF ![visitors](https://visitor-badge.glitch.me/badge?page_id=bupt-ai-cz.PGDF)

[![PWC](https://img.shields.io/endpoint.svg?url=https://paperswithcode.com/badge/sample-prior-guided-robust-model-learning-to/image-classification-on-mini-webvision-1-0)](https://paperswithcode.com/sota/image-classification-on-mini-webvision-1-0?p=sample-prior-guided-robust-model-learning-to)  [![PWC](https://img.shields.io/endpoint.svg?url=https://paperswithcode.com/badge/sample-prior-guided-robust-model-learning-to/image-classification-on-clothing1m)](https://paperswithcode.com/sota/image-classification-on-clothing1m?p=sample-prior-guided-robust-model-learning-to)  [![PWC](https://img.shields.io/endpoint.svg?url=https://paperswithcode.com/badge/sample-prior-guided-robust-model-learning-to/image-classification-on-cifar-10-with-noisy)](https://paperswithcode.com/sota/image-classification-on-cifar-10-with-noisy?p=sample-prior-guided-robust-model-learning-to)

This repo is the official implementation of our paper ["Sample Prior Guided Robust Model Learning to Suppress Noisy Labels

"](https://arxiv.org/abs/2112.01197).

## Citation

If you use this code for your research, please cite our paper ["Sample Prior Guided Robust Model Learning to Suppress Noisy Labels

"](https://arxiv.org/abs/2112.01197).

```

@misc{chen2022sample,

      title={Sample Prior Guided Robust Model Learning to Suppress Noisy Labels}, 

      author={Wenkai Chen and Chuang Zhu and Yi Chen and Mengting Li and Tiejun Huang},

      year={2022},

      eprint={2112.01197},

      archivePrefix={arXiv},

      primaryClass={cs.CV}

}

```

## Training

Take CIFAR-10 with 50% symmetric noise as an example:

First, please modify the `data_path` in ``presets.json`` to indicate the location of your dataset.

Then, run

```bash

python train_cifar_getPrior.py --preset c10.50sym

```

to get the prior knowledge. Related files will be saved in ``checkpoints/c10/50sym/saved/``.

Next, run

```bash

python train_cifar.py --preset c10.50sym

```

for the subsequent training process.

``c10`` means CIFAR-10, ``50sym`` means 50% symmetric noise.  

Similarly, if you want to take experiment on CIFAR-100 with 20% symmetric noise, you can use the command:

```bash

python train_cifar_getPrior.py --preset c100.20sym

```

```bash

python train_cifar.py --preset c100.20sym

```

## Contact

Wenkai Chen

- email: [email protected]

- wechat: cwkyiyi

Chuang Zhu

- email: [email protected]

- homepage: https://teacher.bupt.edu.cn/zhuchuang/zh_CN/index.htm

If you have any question about the code and data, please contact us directly.

## Additional Info

The (basic) semi-supervised learning part of our code is borrow from [the official DM-AugDesc implementation](https://github.com/KentoNishi/Augmentation-for-LNL/).

Since this paper has not yet been published, we only release part of the experimental code. We will release all the experimental codes after this paper is accepted by a conference.