https://github.com/rahulvigneswaran/Class-Balanced-Distillation-for-Long-Tailed-Visual-Recognition.pytorch

Un-offical PyTorch Implementation of "Class-Balanced Distillation for Long-Tailed Visual Recognition" paper.
https://github.com/rahulvigneswaran/Class-Balanced-Distillation-for-Long-Tailed-Visual-Recognition.pytorch

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Un-offical PyTorch Implementation of "Class-Balanced Distillation for Long-Tailed Visual Recognition" paper.

• Host: GitHub
• URL: https://github.com/rahulvigneswaran/Class-Balanced-Distillation-for-Long-Tailed-Visual-Recognition.pytorch
• Owner: rahulvigneswaran
• Created: 2021-06-08T19:44:33.000Z (over 3 years ago)
• Default Branch: main
• Last Pushed: 2021-10-31T17:38:22.000Z (about 3 years ago)
• Last Synced: 2024-08-02T15:36:37.942Z (3 months ago)
• Language: Python
• Size: 779 KB
• Stars: 16
• Watchers: 2
• Forks: 4
• Open Issues: 0
• Metadata Files:
  • Readme: Readme.md

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README

        
# Pytorch Implementation of [Class-Balanced Distillation for Long-Tailed Visual Recognition](https://arxiv.org/abs/2104.05279) by [Ahmet Iscen](https://cmp.felk.cvut.cz/~iscenahm/), André Araujo, Boqing Gong, Cordelia Schmid

---

### Note:

    - Implemented only for ImageNetLT

    - `normal_teachers` is the `Standard model` from the paper

    - `aug_teachers` is the `Data Augmentation model` from the paper

## Things to do before you run :

- Change the `data_root` for your dataset in `main.py`.

- If you are using wandb logging ([Weights & Biases](https://docs.wandb.ai/quickstart)), make sure to change the `wandb.init` in `main.py` accordingly.

## How to use?

- Easy to use : Check this script - `multi_runs.sh`

- Train the normal teachers :

```

python main.py --experiment=0.1 --seed=1 --gpu="0,1" --train --log_offline

```

- Train the augmentation teachers :

```

python main.py --experiment=0.2 --seed=1 --gpu="0,1" --train --log_offline

```

- Train the Class Balanced Distilled Student :

```

python main.py --experiment=0.3 --alpha=0.4 --beta=100 --seed=$seeds --gpu="0,1" --train --log_offline --normal_teacher="10,20" --aug_teacher="20,30"

```

### Arguments :

(General)

- `--seed`: Seed of your current run

- `--gpu`: GPUs to be used

- `--experiment`: Experiment number (Check `libs/utils/experiment_maker.py` for more details)

- `--wandb_logger`: Does wandb Logging

- `--log_offline`: Does offline Logging

- `--resume`: Resumes the training if the run crashes

(Specific to Distillation and Student's training)

- `--alpha`: Weightage between Classifier loss and distillation loss

- `--beta`: weightage for the Cosine Similarity between teachers and student

- `--normal_teachers`: What all seed of norma teachers do you want to use? If you want to use only augmentation teachers, just don't use this argument. It is `None` by default.

- `--aug_teachers`:  What all seed of augmented teachers do you want to use? If you want to use only normal teachers, just don't use this argument. It is `None` by default.

## Raise an issue :

If something is not clear or you found a bug, raise an issue!!