An integrated pipeline for developing and evaluating trustworthy computer vision models.
Project description
xdep
Screenshots
| Accuracy & Loss Graphs | Explainability (LIME) |
|---|---|
Overview
xdep is an integrated pipeline designed to simplify the development and evaluation of trustworthy computer vision models.
It provides an end-to-end framework for training, interpreting, and visualizing deep learning models with a focus on transparency and reliability.
Features
- Easy setup and modular pipeline to build trustworthy computer vision models
- Integrated support for popular explainability techniques (e.g., LIME)
- Automated generation of evaluation reports and visualizations (CSV, figures)
- Lightweight and easy to extend for custom workflows
- Command-line interface (CLI) for quick experimentation and testing
Installation
You can install the latest stable version from TestPyPI (for testing) or PyPI (for production):
pip install xdep
Dependencies
xdep requires the following Python packages (automatically installed with pip):
lime >= 0.2.0.1matplotlibpillowrichscikit-learnseaborntensorflow
Quick Start
Using as a Python Package
Here’s a minimal example of how to use xdep in your Python code:
from xdep import main
# Call the main pipeline function or your preferred API
main.main()
Using the CLI
After installation, you can run the xdep command directly in your terminal:
xdep
This will show available commands and options.
Directory & Output Handling
xdep saves generated CSV files and figures to a results directory in the current working directory by default.
- If the
resultsdirectory does not exist, it will be created automatically. - You can configure output directories and filenames via the API or CLI arguments.
Development & Contribution
Contributions are welcome! Feel free to:
- Report issues or bugs
- Request features or improvements
- Submit pull requests with enhancements or fixes
Setup for Development
Clone the repo and install in editable mode:
git clone https://github.com/SAGAR-TAMANG/X-DEP
cd X-DEP
pip install -e .
License
This project is licensed under the MIT License. See the LICENSE file for details.
Contact
For questions, suggestions, or collaboration, reach out to:
Sagar Tamang Email: sagar.bdr0000@gmail.com GitHub: https://github.com/SAGAR-TAMANG
Acknowledgements
- Thanks to the developers of LIME and other open-source libraries integrated with this package.
- Inspired by the need for trustworthy and interpretable AI models in computer vision.
Happy modeling! 🚀
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