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Contributing Guide

Thank you for your interest in contributing to ITKIT! This guide will help you get started with development and contributions.

Getting Started

Development Setup

  1. Fork and clone the repository:

bash git clone https://github.com/MGAMZ/ITKIT.git cd ITKIT

  1. Install development dependencies:

bash pip install -e ".[dev]"

This installs ITKIT in editable mode with all development tools including:

  • pytest (testing)
  • black, isort, autopep8 (code formatting)
  • mypy, pyright (type checking)
  • pylint (linting)

  • pre-commit (git hooks)

  • Set up pre-commit hooks:

bash pre-commit install

This ensures code is automatically formatted and checked before commits.

What to Contribute

Areas for Contribution

  1. Bug Fixes: Fix reported bugs or issues you encounter

  2. New Features:

  3. New preprocessing operations
  4. Additional neural network models
  5. Dataset conversion scripts

  6. Framework integrations

  7. Documentation:

  8. Improve existing docs
  9. Add examples
  10. Fix typos

  11. Translate documentation

  12. Tests:

  13. Increase test coverage
  14. Add edge case tests

  15. Add integration tests

  16. Performance:

  17. Optimize slow operations
  18. Improve memory usage
  19. Add parallelization

Adding New Models

To add a new neural network model:

  1. Create model file in itkit/models/
  2. Implement model class with PyTorch
  3. Add documentation in docs/models.md
  4. Include reference paper and citation
  5. Add usage examples
  6. Create unit tests

Example structure:

# itkit/models/my_new_model.py

import torch
import torch.nn as nn

class MyNewModel(nn.Module):
    """
    Brief description of the model.

    Reference: Author et al., "Paper Title", Conference/Journal Year.
    """

    def __init__(self, in_channels, num_classes, **kwargs):
        super().__init__()
        # Model architecture

    def forward(self, x):
        # Forward pass
        return output

Adding Dataset Conversion Scripts

To add a new dataset conversion script:

  1. Create folder: itkit/dataset/<dataset_name>/
  2. Add conversion script: convert_<format>.py
  3. Document in docs/datasets.md
  4. Include dataset reference and citation
  5. Add example usage

Script should:

  • Convert to ITKIT format (image/ and label/ folders)
  • Preserve metadata
  • Handle edge cases
  • Provide progress feedback

Adding Preprocessing Tools

To add a new preprocessing command:

  1. Create script in itkit/process/
  2. Add entry point in pyproject.toml
  3. Create documentation in docs/itk_*.md and update mkdocs.yml
  4. Add tests in tests/
  5. Support common flags (--mp, --help)

Getting Help

  • Issues: Use GitHub Issues for bug reports and feature requests
  • Email: Contact maintainer at 312065559@qq.com
  • Discussions: Use GitHub Discussions for questions