The network for creativity
Join 1.25M professional creatives like you
Connect with clients, get discovered, and run your business 100% commission-free
Creatives on Contra have earned over $150M and we are just getting started
Back to feedPost
Real-Time Restaurant Table Monitoring System Using Computer Vision
Complete video of *Real-Time Restaurant Table Monitoring System*
The network for creativity
Join 1.25M professional creatives like you
Connect with clients, get discovered, and run your business 100% commission-free
Creatives on Contra have earned over $150M and we are just getting started
Related posts
This project focused on building and testing a practical AI security assessment lab for evaluating LLM defenses against prompt injection and jailbreak attacks.
I integrated Spikee by Reversec with a locally hosted cybersecurity model running through LM Studio, then added NVIDIA NeMo Guardrails to compare model behavior under three conditions: no guardrails, input filtering, and combined input/output protection.
The work included configuring the local model environment, building a custom FastAPI gateway, integrating NeMo Guardrails, troubleshooting model latency and timeout issues, creating a reusable Spikee target, and analyzing attack results using Spikee’s built-in reporting tools.
The project also explored different adversarial testing approaches, including prompt injection datasets, obfuscation, encoded attacks, Best-of-N testing, synthetic canary leakage tests, and structured benchmark comparisons.
The objective was to measure how much the guardrails reduced successful attacks while keeping the model, dataset, and testing conditions consistent.
Tools used: Spikee, NVIDIA NeMo Guardrails, LM Studio, Python, FastAPI, PowerShell, Parrot OS, local LLMs, JSONL datasets, and custom security testing scripts.
This project demonstrates a hands-on approach to LLM red teaming, AI safety testing, prompt-injection assessment, and guardrail validation for organizations deploying generative AI systems.
pretty cool tbh. testing the same attacks with different guardrail setups makes the results way more interesting.
Food Restaurant SaaS Dashboard
A SaaS dashboard concept designed for restaurant businesses to manage and understand their day-to-day operations.
The interface brings key business information into a structured workspace, with clear sections for performance, orders, sales and operational data.
The design approach focuses on hierarchy first — helping users find important information quickly without overwhelming them with unnecessary detail.
Design focus:
• SaaS Dashboard Design
• Restaurant Management UX
• Data Visualization
• Business Analytics
• UI/UX Design
• Product Design
Designed by WaxyWeb.
great
Food Delivery Mobile App UI/UX Design
A modern and engaging food delivery app designed to make discovering, ordering, and tracking favorite meals simple and enjoyable. The clean interface combines appetizing food visuals, intuitive navigation, personalized recommendations, detailed menu information, and a seamless checkout experience for a smooth ordering journey.
