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IBLA - Imbalance Learning Archive

🔔🔔🔔 This project is shutdown owing to a very bad coding architecture, the new version of this project will be release soon.

Setup

Environment

Create a virtual environment and upgrade the version of pip

python3 -m venv .env
source .env/bin/activate
python -m pip install -U pip

Install the required packages

cd /path/to/cloned/repo/directory
pip install -r requirements.txt

Install Pytorch packages, the version of the Nvidia driver is 535 and the CUDA version is 12.1 on a Ubuntu-based system

pip3 install torch torchvision torchaudio

Dataset

Contribute to this project

Folder Structure

  • dataset
    • [ds].py where ds is any dataset name
    • getds.py used as a mapping from args to a dataset
  • loss
    • [loss].py where loss is any loss name
  • metrics
    • [metric].py where metric is any metric name
  • model
    • [model_name]
      • *.py
  • utils
  • main.py
  • mapping.py
  • requirements.txt
  • trainer.py

Dataset Contribution

  • Data sources and related annotations must be put into dataset/source folder, which is an ignored folder. A custom dataset class inheriting torch.utils.data.Dataset of Pytorch and read all data from dataset/source.
  • ⚠️⚠️: Do not change the content of any file inside dataset/, just create a new .py file to contribute your custom dataset.

Model/Loss Contribution

  • Create a new folder/new file .py to store your model architecture/loss function and its sub-components
  • ⚠️⚠️: Do not change the content of any file inside model/ and loss/

Workflow

  • For collaborators, create a new branch with the name as follows: <task>-<name> (i.e. model_deeplabv3) and then pull a request to merge to branch main.
  • For outer collaborators, fork this repo, and then pull a request also.
  • For review the pull request, you can tag the owner of this repo, the owner will merge and complete the final task to emerge your contribution thoroughly.

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