crown-of-napoleon/south-africa-apartheid-truth-and-reconciliation

Utilizing Machine Learning to examine racial segregation trends over time and across geographical areas in South Africa.

south-africa-apartheid-truth-and-reconciliation's Issues

7/31 Issues

Code Quality: Some of the Python scripts do not follow PEP 8, the Python style guide, which is widely used in the industry to ensure code readability and consistency.

Code Reusability: Some of the data processing scripts (like 'request-1950s.py', 'request-1960s.py', etc.) seem to have repetitive code, which could potentially be refactored for better reusability.

Code Comments: While some scripts have comments, others do not. Adding comments to all scripts would make the code easier to understand and maintain.

Comprehensive Testing: While there are some unit tests, it's not clear if they cover all parts of the codebase. Comprehensive testing is important in industry-level projects to ensure all functionality works as expected.

6/20 Issues

Documentation: While the README file is quite comprehensive, it would be helpful to have more detailed comments in the Python script (evaluate_model_f1.py). This would make it easier for others to understand the code and contribute to the project.

Data Collection: The issue.md file mentions that the image set should contain different races in public space and be based on different epochs. It might be beneficial to provide more details on how this data will be collected and how the diversity of the data set will be ensured.

Model Evaluation: The evaluate_model_f1.py script calculates the F1 score of a model. It might be helpful to include other metrics as well, such as precision, recall, and accuracy, to provide a more comprehensive evaluation of the model's performance.

Version Control: It would be beneficial to use branches for developing new features or making significant changes. This would help keep the main branch stable and make it easier to manage the project as it grows.

Code of Conduct and Contribution Guidelines: The README file includes a code of conduct and mentions that all contributions are welcome. However, it might be helpful to have a separate CONTRIBUTING file that provides more detailed guidelines on how to contribute to the project.

Licensing: The project is under the MIT License, which is a permissive license. If the project has specific needs regarding how it can be used, it might be worth considering a different license.

Continuous Integration/Continuous Deployment (CI/CD): Implementing CI/CD practices can help automate the testing and deployment of your project, ensuring that changes do not break functionality and that the latest version of the project is always available.

Unit Tests: Adding unit tests can help ensure the functionality of your code as you make changes. This can be particularly helpful in a collaborative project where multiple people may be modifying the code.

Project Management: Using the "Issues" and "Projects" features on GitHub can help manage tasks and track progress. This can be particularly useful in a collaborative project.