Software License Compliance Report

# Software License Compliance Report

## Project: Early Cancer Prediction System
**Date**: February 23, 2026  
**Status**: ✅ **100% Free and Open Source Software (FOSS)**

---

## Executive Summary

This project uses **exclusively free and open-source software (FOSS)**. All dependencies are licensed under OSI-approved licenses that permit commercial use, modification, and redistribution.

---

## Core Dependencies License Breakdown

### 1. Programming Language
| Software | Version | License | FOSS | Commercial Use |
|----------|---------|---------|------|----------------|
| **Python** | 3.8+ | PSF License | ✅ | ✅ |

**Python Software Foundation License** is GPL-compatible and permits commercial use.

---

### 2. Machine Learning & Deep Learning

| Library | Version | License | FOSS | Commercial Use | Source |
|---------|---------|---------|------|----------------|--------|
| **TensorFlow** | 2.13.0 | Apache 2.0 | ✅ | ✅ | [GitHub](https://github.com/tensorflow/tensorflow) |
| **Keras** | 2.13.1 | Apache 2.0 | ✅ | ✅ | Part of TensorFlow |
| **scikit-learn** | 1.3.0 | BSD 3-Clause | ✅ | ✅ | [GitHub](https://github.com/scikit-learn/scikit-learn) |
| **XGBoost** | 2.0.0 | Apache 2.0 | ✅ | ✅ | [GitHub](https://github.com/dmlc/xgboost) |

**All licenses permit**:
- ✅ Commercial use
- ✅ Modification
- ✅ Distribution
- ✅ Private use

---

### 3. Data Processing & Analysis

| Library | Version | License | FOSS | Commercial Use |
|---------|---------|---------|------|----------------|
| **NumPy** | 1.24.3 | BSD 3-Clause | ✅ | ✅ |
| **Pandas** | 2.0.3 | BSD 3-Clause | ✅ | ✅ |
| **imbalanced-learn** | 0.11.0 | MIT | ✅ | ✅ |

---

### 4. Image Processing

| Library | Version | License | FOSS | Commercial Use |
|---------|---------|---------|------|----------------|
| **Pillow** | 10.0.0 | HPND (PIL License) | ✅ | ✅ |
| **OpenCV** | 4.8.0 | Apache 2.0 | ✅ | ✅ |
| **scikit-image** | 0.21.0 | BSD 3-Clause | ✅ | ✅ |

---

### 5. Visualization

| Library | Version | License | FOSS | Commercial Use |
|---------|---------|---------|------|----------------|
| **Matplotlib** | 3.7.2 | PSF-based | ✅ | ✅ |
| **Seaborn** | 0.12.2 | BSD 3-Clause | ✅ | ✅ |

---

### 6. Web API Framework

| Library | Version | License | FOSS | Commercial Use |
|---------|---------|---------|------|----------------|
| **FastAPI** | 0.103.1 | MIT | ✅ | ✅ |
| **Uvicorn** | 0.23.2 | BSD 3-Clause | ✅ | ✅ |
| **Pydantic** | 2.3.0 | MIT | ✅ | ✅ |
| **python-multipart** | 0.0.6 | Apache 2.0 | ✅ | ✅ |

---

### 7. Utilities

| Library | Version | License | FOSS | Commercial Use |
|---------|---------|---------|------|----------------|
| **joblib** | 1.3.2 | BSD 3-Clause | ✅ | ✅ |
| **tqdm** | 4.66.1 | MIT/MPL-2.0 | ✅ | ✅ |
| **python-dotenv** | 1.0.0 | BSD 3-Clause | ✅ | ✅ |
| **loguru** | 0.7.1 | MIT | ✅ | ✅ |

---

### 8. Testing (Optional)

| Library | Version | License | FOSS | Commercial Use |
|---------|---------|---------|------|----------------|
| **pytest** | 7.4.2 | MIT | ✅ | ✅ |
| **pytest-cov** | 4.1.0 | MIT | ✅ | ✅ |

---

### 9. Jupyter (Optional)

| Library | Version | License | FOSS | Commercial Use |
|---------|---------|---------|------|----------------|
| **jupyter** | 1.0.0 | BSD 3-Clause | ✅ | ✅ |
| **ipykernel** | 6.25.2 | BSD 3-Clause | ✅ | ✅ |
| **notebook** | 7.0.3 | BSD 3-Clause | ✅ | ✅ |

---

## Pre-trained Model Weights

### ImageNet Weights

**Source**: TensorFlow/Keras Model Zoo  
**License**: Apache 2.0 (for the code), Weights are freely available  
**Status**: ✅ FOSS

The pre-trained weights (EfficientNet, ResNet, DenseNet, MobileNet) distributed through TensorFlow/Keras are:
- ✅ Free to use
- ✅ Free to redistribute
- ✅ Can be used commercially
- ✅ No attribution required beyond TensorFlow citation

**Note**: While ImageNet dataset itself has usage restrictions, the **pre-trained model weights** distributed by TensorFlow are freely available for any use.

---

## Datasets

### 1. Brain Tumor Dataset
- **Source**: Kaggle (Public Domain / CC0)
- **License**: Open Data Commons Public Domain Dedication
- **Status**: ✅ Free to use

### 2. Cervical Cancer Dataset
- **Source**: Kaggle / UCI ML Repository
- **License**: CC BY 4.0 / Open Data
- **Status**: ✅ Free to use with attribution

### 3. Oral Cancer Dataset
- **Source**: Research dataset
- **License**: Varies (check original source)
- **Status**: ⚠️ Verify with original source

---

## Operating Systems

This software runs on:
- ✅ **Linux** (Ubuntu, Debian, CentOS, etc.) - Free & Open Source
- ✅ **macOS** (proprietary but Python/packages are FOSS)
- ✅ **Windows** (proprietary but Python/packages are FOSS)

**Recommended**: Use Linux (Ubuntu 20.04+ or similar) for 100% FOSS stack.

---

## Cloud/Deployment (Optional)

If deploying to cloud, consider FOSS-friendly options:
- ✅ **Self-hosted** on own hardware
- ✅ **OpenStack** (Open Source Cloud)
- ⚠️ AWS/GCP/Azure (Commercial cloud services, but can run FOSS software)

---

## License Compatibility Matrix

| License Type | Permits Commercial Use | Permits Modification | Copyleft | Compatible with MIT/Apache 2.0 |
|--------------|----------------------|---------------------|----------|-------------------------------|
| **MIT** | ✅ | ✅ | ❌ | ✅ |
| **Apache 2.0** | ✅ | ✅ | ❌ | ✅ |
| **BSD 3-Clause** | ✅ | ✅ | ❌ | ✅ |
| **PSF License** | ✅ | ✅ | ❌ | ✅ |

**All licenses used are permissive (non-copyleft)** and fully compatible with each other.

---

## This Project's License

**License**: MIT License  
**Status**: ✅ FOSS  
**Permits**:
- ✅ Commercial use
- ✅ Modification
- ✅ Distribution
- ✅ Private use

---

## Verification Commands

To verify all packages:

```bash
# Check installed packages licenses
pip install pip-licenses
pip-licenses --format=markdown --with-urls

# Check specific package license
pip show tensorflow | grep License
pip show fastapi | grep License
pip show scikit-learn | grep License
```

---

## No Proprietary Dependencies

### ❌ NOT Used:
- ❌ MATLAB (proprietary)
- ❌ Mathematica (proprietary)
- ❌ Microsoft ML.NET (open source but Microsoft-controlled)
- ❌ Any proprietary cloud services (optional, not required)
- ❌ Any commercial AI platforms
- ❌ Any paid APIs or services

### ✅ Used:
- ✅ Python (PSF License)
- ✅ TensorFlow (Apache 2.0)
- ✅ Standard FOSS Python ecosystem

---

## Compliance Checklist

- [x] All core dependencies are FOSS
- [x] All licenses permit commercial use
- [x] No copyleft restrictions (all permissive licenses)
- [x] No proprietary software required
- [x] No paid services required
- [x] Can run entirely offline
- [x] Source code available
- [x] Can be modified and redistributed
- [x] No vendor lock-in
- [x] Community-driven development

---

## Conclusion

✅ **This project is 100% Free and Open Source Software**

Every component, from the programming language to the web framework, uses OSI-approved open source licenses. You can:

1. **Use** this software for any purpose (personal, academic, commercial)
2. **Study** how it works (source code included)
3. **Modify** it to fit your needs
4. **Redistribute** original or modified versions
5. **Run** it on any hardware/OS
6. **Deploy** it without licensing fees

**No proprietary software, paid licenses, or vendor lock-in required.**

---

## Recommended Citation for Dependencies

If publishing research using this software:

```bibtex
@article{tensorflow2015,
  title={TensorFlow: Large-Scale Machine Learning on Heterogeneous Systems},
  author={Martin Abadi and others},
  year={2015},
  url={https://www.tensorflow.org/}
}

@article{scikit-learn,
  title={Scikit-learn: Machine Learning in Python},
  author={Pedregosa, F. and others},
  journal={Journal of Machine Learning Research},
  year={2011}
}

@inproceedings{fastapi,
  title={FastAPI: Modern, fast Python web framework},
  author={Ramírez, Sebastián},
  year={2018},
  url={https://fastapi.tiangolo.com/}
}
```

---

## Contact for License Questions

For any licensing concerns or questions:
- Review individual package licenses: `pip show <package-name>`
- Consult OSI (Open Source Initiative): https://opensource.org/licenses
- Check package GitHub repositories

---

**Last Updated**: February 23, 2026  
**Verified By**: Project Maintainers  
**Status**: ✅ FOSS Compliant