Add academic and research-only license

Author: Rushir Bhavsar

LICENSE

@@ -0,0 +1,43 @@
+MIT License (Academic and Research Use Only)
+
+Copyright (c) 2024-2025 Rushir Bhavsar
+
+Permission is hereby granted, free of charge, to any person obtaining a copy
+of this software and associated documentation files (the "Software"), to use
+the Software for academic, educational, and research purposes only, subject to
+the following conditions:
+
+ACADEMIC AND RESEARCH USE ONLY:
+This software and associated documentation may be used solely for:
+- Academic research and study
+- Educational purposes
+- Portfolio demonstration
+- Personal learning and development
+
+COMMERCIAL USE RESTRICTION:
+Commercial use, including but not limited to:
+- Use in production systems for business purposes
+- Integration into commercial products or services
+- Use by corporations or for-profit entities
+- Revenue-generating applications
+
+is NOT permitted without explicit written permission from the copyright holder.
+
+DATA USAGE:
+This project uses the Yelp Open Dataset, which is subject to its own license
+terms. Users must comply with Yelp's dataset license agreement available at:
+https://www.yelp.com/dataset/documentation/licensing
+
+ATTRIBUTION:
+The above copyright notice and this permission notice shall be included in all
+copies or substantial portions of the Software.
+
+THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
+SOFTWARE.
+
+For commercial use inquiries, please contact: [your.email@example.com]

README.md

@@ -7,11 +7,14 @@ A production-ready machine learning platform for business recommendations and se
 [![Docker Build](https://github.com/rushirb2001/yelp-ml-platform/actions/workflows/docker.yml/badge.svg)](https://github.com/rushirb2001/yelp-ml-platform/actions/workflows/docker.yml)
 [![Python 3.11](https://img.shields.io/badge/python-3.11-blue.svg)](https://www.python.org/downloads/release/python-3110/)
 
+---
 
 ## Overview
 
 This project demonstrates end-to-end ML engineering capabilities including data processing, model training, API development, containerization, and CI/CD automation. The platform processes millions of Yelp reviews to provide business recommendations and sentiment analysis through a REST API.
 
+---
+
 ## Key Features
 
 **Machine Learning Models**
@@ -35,6 +38,8 @@ This project demonstrates end-to-end ML engineering capabilities including data
 - Code quality checks with Black, isort, and Flake8
 - Docker image building and deployment automation
 
+---
+
 ## Project Structure
 ```
 yelp-ml-platform/
@@ -54,6 +59,8 @@ yelp-ml-platform/
 
 For detailed project structure, see [docs/ARCHITECTURE.md](docs/ARCHITECTURE.md)
 
+---
+
 ## Quick Start
 
 ### Prerequisites
@@ -89,6 +96,8 @@ conda activate yelp-ml-platform
 
 For detailed setup instructions, see [docs/SETUP.md](docs/SETUP.md)
 
+---
+
 ## Usage
 
 ### Running the API
@@ -139,6 +148,8 @@ For complete API documentation, see [docs/API.md](docs/API.md)
 
 For detailed model evaluation, see [docs/MODELS.md](docs/MODELS.md)
 
+---
+
 ## Development
 
 ### Running Tests
@@ -174,6 +185,8 @@ mlflow ui --port 5001
 # View experiments at http://localhost:5001
 ```
 
+---
+
 ## Deployment
 
 ### Docker Deployment
@@ -195,6 +208,8 @@ The project includes automated workflows for:
 
 All workflows are defined in `.github/workflows/`
 
+---
+
 ## Technical Stack
 
 **Core Technologies:**
@@ -217,22 +232,58 @@ All workflows are defined in `.github/workflows/`
 - Pandas 2.1.0
 - NumPy 1.26.0
 
+---
+
 ## Project Timeline
 
 This project was developed over 16 weeks (November 2024 - March 2025) following a structured development plan with distinct phases for data engineering, ML model development, API creation, testing, and deployment automation.
 
+---
+
 ## License
 
-MIT License - see LICENSE file for details
+This project is licensed under a **Custom Research and Educational License**. 
 
-## Contact
+**Key Points:**
+- View and study the code freely
+- Use for educational purposes
+- Reference in academic papers
+- Copying/forking requires written permission
+- Commercial use requires written permission
+  - Modification and redistribution require written permission
 
-Rushir Bhavsar
-- GitHub: [@rushirb2001](https://github.com/rushirb2001)
-- LinkedIn: [Your LinkedIn]
-- Email: rushirbhavsar@gmail.com
+**To request permission:** Contact rushirbhavsar@gmail.com
+
+See the [LICENSE](LICENSE) file for complete terms.
+
+---
 
 ## Acknowledgments
 
-- Yelp Dataset: https://www.yelp.com/dataset
-- Dataset used for academic and portfolio purposes
+- OpenCV community for the GrabCut implementation
+- **Nirma University** for hosting the MiNeD Hackathon
+- Diamond dataset providers
+- Academic advisors and mentors
+- Open-source contributors
+
+---
+
+## References
+
+1. Rother, C., Kolmogorov, V., & Blake, A. (2004). "GrabCut: Interactive foreground extraction using iterated graph cuts." *ACM Transactions on Graphics*, 23(3), 309-314.
+
+2. Pizer, S. M., et al. (1987). "Adaptive histogram equalization and its variations." *Computer Vision, Graphics, and Image Processing*, 39(3), 355-368.
+
+3. Bradski, G. (2000). "The OpenCV Library." *Dr. Dobb's Journal of Software Tools*.
+
+---
+
+## Support
+
+For questions, issues, or suggestions:
+
+- Email: rushirbhavsar@gmail.com
+- Issues: [GitHub Issues](https://github.com/yourusername/diamond-shape-segmentation/issues)
+- Discussions: [GitHub Discussions](https://github.com/yourusername/diamond-shape-segmentation/discussions)
+
+---