docs(README): add small note about AI use
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aria 2025-06-14 04:09:47 +10:00
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- Normal and compact builds are uploaded as separate artifacts
- UPX compression applied to compact builds for size optimization
## Repository Information
- **Main Repository**: https://git.aria.coffee/aria/fps-go-brr (Personal Forgejo instance)
- **Mirror**: https://github.com/BuyMyMojo/fps-go-brr (GitHub - accepts PRs and issues)
- **Dual Licensed**: MIT OR Apache-2.0 (SPDX-License-Identifier: MIT OR Apache-2.0)
- **Copyright**: 2025 Aria, Wicket
### Inspirations
This project draws inspiration from:
- Digital Foundry (YouTube) - Professional video game performance analysis
- Brazil Pixel (YouTube) - Technical video analysis and frame rate studies
- TRDrop (GitHub) - Raw video analysis program for framerate estimation
- Original Python implementation - Early proof-of-concept for frame persistence analysis
## Memories
- The forgejo workflow runner is executed as root so it does not need to use root

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The goal is to provide similar professional-grade video analysis capabilities for the open-source community.
## Note on AI use
The use of AI in this project is minor and just an experiment, all major design decisions and functionality are heavily worked on by humans!
I do hope for future AI tools with ethical models to be avaliable and verifiable in the future!
The testing phase for Claude's coding agent in this repo is finished and it shall not contribute more to the code at the current time.
## License
SPDX-License-Identifier: MIT OR Apache-2.0