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AI-powered culinary companion that turns leftovers into gourmet meals. Features intelligent recipe generation, batch cooking planning, and scientific dish rescue. Built with Next.js 16, TypeScript, MongoDB & Llama 3 (Groq).
Carta Digital QR interactiva para restaurantes con pedidos automáticos directos a WhatsApp. Solución 0% comisiones, actualización de precios en tiempo real y sin descargas de apps. Ideal para restaurantes, bares y cafeterías.
"Omnifood-FoodDelivery" is housing an innovative food delivery website project named Omnifood. This repository contains the complete source code, and interactive features that power Omnifood's seamless online food ordering experience.
Procedural cooking engine that builds recipes from molecular flavor pairing, texture contrast and taste balance, with diet filtering. Tkinter GUI and CLI, pure Python stdlib, optional AI Chef via Ollama or Claude.
Campus food delivery PWA for VIT-AP University students — order from campus canteens with real-time order tracking, Firebase Auth, and an admin dashboard. Built with Next.js 16, TypeScript, and Firestore, installable offline on iOS & Android.
Comprehensive e-commerce web platform built with Next.js featuring dual portals for buyers and sellers. Connects mushroom growers directly with consumers, eliminating middlemen and maximizing farmer profits.
ConvNeXt-CLF-75 is a food image classifier fine-tuned from ConvNeXt_tiny on a curated subset of 75 food categories from the MM-Food-100K dataset. The model is designed to serve as a semantic guide for a downstream segmentation network in a calorie‑estimation pipeline. The classifier outputs class predictions (multi-label).