Pic To GB

Live Demo

Overview

Pic To GB is a sophisticated tool designed for converting images into Game Boy graphics format. This project caters to both aesthetic enthusiasts and homebrew game developers, offering a unique blend of retro styling and practical functionality.

Features

• Flexible Image Processing: Converts images to Game Boy graphics while maintaining original dimensions.
• Color Reduction: Implements a 4-color palette conversion, emulating the classic Game Boy aesthetic.
• Tile-Based Graphics: Transforms images into tile-based formats, authentic to Game Boy architecture.
• Adjustable Parameters: Fine-tune contrast and brightness for optimal rendering.
• Export Options: Download processed images or generate playable Game Boy ROMs.
• Tile Limitation: Option to restrict tile count, creating intentional glitch aesthetics or optimizing for hardware constraints.

Technical Specifications

• Processing: All operations are performed client-side, ensuring data privacy and rapid processing.
• ROM Generation: Creates simple, image-display ROMs compatible with both emulators and original hardware.
• Tile Limits: Supports standard Game Boy (196 tiles) and Game Boy Color (256 tiles) specifications.

Developer Notes

This project extends the original concept to support homebrew game development. Key modifications include:

• Removal of the 160x144 pixel restriction, allowing for larger, more detailed scenes.
• Implementation of customizable tile limits for multi-part scene development.
• Optimized for integration with tools like GB Studio and GBSDK.

Usage Guidelines

1. For optimal performance, process large images in sections.
2. When creating multi-part scenes, allocate tile budgets accordingly (e.g., 64 tiles per quarter for a four-part scene).
3. Export processed images for reassembly or direct use in development environments.

Running the Application

• Open the HTML file directly in a web browser.
• Alternatively, serve through a local development server (e.g., VSCode's Live Server or Python's http.server).

Note: Processing time may increase with larger images. Sectioning large images is recommended for efficiency.

Data Privacy

This application processes all data locally within the user's browser. No information is uploaded or transmitted to external servers.

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Contributions and feedback are welcome. For any inquiries or suggestions, please open an issue on the GitHub repository.