Retro Pixel Maker banner

Retro Pixel Maker

Created by: Rushgo
1 devlog
4h 15m

The Retro Pixel Character Maker is a web-based project that converts user-uploaded photos into retro-style pixel art game characters. The application automatically detects and crops faces, applies pixelation techniques, and supports classic color …

The Retro Pixel Character Maker is a web-based project that converts user-uploaded photos into retro-style pixel art game characters. The application automatically detects and crops faces, applies pixelation techniques, and supports classic color palettes such as GameBoy and NES styles to give a nostalgic game-like appearance. Users can generate their character through an interactive interface and download the final pixel avatar as an image. The project is being developed by Rushil Goyal as a solo full-stack project, handling both frontend and backend development along with image processing and debugging. In the future, the project can be extended with features such as live preview while adjusting settings, sprite animation generation, support for multiple faces, improved UI design, and full online deployment with a public demo link.

This project uses AI

ChatGPT was used for debugging assistance and development guidance during the project.

Demo Repository

README

Loading README...
Rushgo
Rushgo worked on Retro Pixel Maker
3 months ago
4h 15m logged

I started this project with the goal of creating a fun web app that converts photos into retro pixel-art characters. I first built the basic Flask backend and frontend connection to handle image uploads and display results. After that, I implemented pixelation and added options to adjust pixel size and colors.

As development continued, I added retro palettes like GameBoy and NES styles and implemented a download feature so users could save their characters. One of the biggest challenges was debugging frontend–backend integration issues and fixing image processing errors.

Later, I integrated face detection using OpenCV to automatically crop faces, which significantly improved the quality of the generated avatars. This project helped me understand full-stack development, image processing workflows, and real-world debugging.

Attachment
0