Aves is a Flutter-based mobile application (primarily Android, given the extensive Kotlin platform code) that functions as a high-performance media gallery and manager. It browses local storage, indexes media into a SQLite database, extracts and allows editing of extensive metadata (EXIF, XMP, IPTC, MP4), and provides a rich viewing experience including maps, video playback with subtitle support, and custom gesture-driven zoom/pan. The codebase is notable for its modular plugin architecture (magnifier, map, video, model, services), its defensive approach to parsing potentially corrupt media files on the native Android side, and its comprehensive internationalization and multi-calendar support. It is a mature, actively developed application with a strong focus on user experience and data integrity.
Photonix is a self-hosted, full-stack photo management application with AI-powered classification and search. The backend is a Django monolith exposing a GraphQL API, with background workers for importing, thumbnail generation, raw processing, and ML classification (color, objects, faces, location, style, events). The frontend is a React 19 single-page app built with TanStack Router, Apollo Client, Zustand state management, and a dark-themed shadcn/ui component library. The system supports multi-user libraries, invitations, map view, albums, and fine-grained search with facets. The architecture relies on a PostgreSQL database, Redis for task coordination and locks, and supervisor to manage numerous background processes. While the project shows solid engineering and a modern tech stack, it carries some technical debt from vendored ML models, TensorFlow 1.x compatibility, and hardcoded download URLs, and is explicitly not yet feature-complete.