A high-performance, scalable image processing system designed to leverage distributed computing to handle massive image processing workloads efficiently
⚠️ IMPORTANT: This project is currently in early development phase. Repository structure and core functionality is not yet implemented.
This engine will provide a flexible node-based processing pipeline that allows complex image transformations to be composed visually and executed at scale. Perfect for content delivery networks, e-commerce platforms, and media processing services that need to handle millions of images daily.
- Distributed processing with horizontal scaling
- Node-based visual workflow editor
- OpenCV integration for high-performance image operations
- Spring Batch for reliable job execution
- REST API for programmatic access
- Basic filters (blur, sharpen, edge detection, etc.)
- GPU acceleration for compute-intensive operations
- Machine learning-based image analysis (object detection, face recognition)
- Advanced content-aware resizing and cropping
- Webhook notifications for job completion
- Pre-built templates for common transformations
- Batch optimization for similar operations
- Comprehensive image metadata preservation
- OAuth2 authentication and fine-grained permissions
- Integration with different cloud storage providers
- Java 17
- Spring Boot 3.x
- Apache Kafka
- OpenCV
- PostgreSQL
- Redis
- React (for web interface)
This project is in the initial planning and development phase. Contributors interested in collaborating on the architecture and core implementation are welcome to open issues for discussion.
MIT license