This is a submission for the "Hacktoberfest Weekend Challenge: Build for a Friend" (https://dev.to/challenges/hacktoberfest-weekend-2026-10-01)
What I Built
I built AI Product Quality Inspector, a simple computer-vision application designed to
help a friend who needs an easier way to check products for visible quality issues before they are sold or delivered.
Instead of manually checking every product, the user can upload an image of a product and get an AI-powered inspection result. The application is designed to make the checking process faster, simpler, and easier to understand.
The project includes product image inspection, quality results, inspection history, reporting, and an AI assistant.
Demo
Live Demo: https://appuct-quality-gh8dydxnvruc6uefck54dl.streamlit.app/
Try uploading a product image and running an inspection.
Code
GitHub Repository: https://github.com/sudha-rani-000/product-quality
The complete project source code is available on GitHub.
How I Built It
I built the application using Python and Streamlit, with a computer-vision workflow for analyzing uploaded product images.
The application provides a simple interface where users can upload an image, request an inspection, and receive an AI-generated quality assessment.
I also added supporting features such as inspection results, history, reporting, and an AI assistant to make the application more useful as a complete product-quality tool.
Why Does Open Innovation Matter?
This project made me think about how AI-powered inspection tools can become more accessible to small businesses and individual users.
My current implementation uses the Gemini API for image analysis, so I am not claiming that Gemini itself is open-source. The project is shared publicly so others can inspect the implementation, learn from it, and build on the idea.
I would like to continue exploring open-weight vision models and local inference so that a future version can reduce dependence on external APIs and provide users with more control over their data and AI system.
My Agent Session
I used AI-assisted development while building and improving this project.
Prize Categories
I am not entering a partner category for this submission.
What I Learned
Building this project helped me understand how computer vision, AI-assisted analysis, and a simple Streamlit interface can be combined into a practical application.
My goal was not just to create an AI demo, but to build something that could solve a real product-checking problem in a simple way.
Top comments (1)
Product quality