Members-Only
Recent Talks & Demos are for members only
You must be an AI Tinkerers active member to view these talks and demos.
KarloAIMutthiMain: C++ Virtual Try-On
Explore a C++ virtual try‑on app using Model Context Protocol for vector searches via Couchbase or local‑first methods, followed by style transfer via external API.
“KarloAIMutthiMain,” the second-place project at the AITinkerers Hackathon, is a Virtual Try-On Streamlit application. Users input desired clothing, and the app performs a vector search across an image database to find matches.
A key enhancement is the Model Context Protocol (MCP), offering two paths for vector search:
- Couchbase Services: For scalable, robust searches.
- Local-First Approach: For rapid, low-latency searches.
After the vector search, results are sent to an external Replicate inference API. This API performs style transfer, applying the chosen clothing to an image and returning the transformed result to the Streamlit app.
C++ server performs VTO using Ollama, IDM-VTON, and Couchbase.