Lunar is a neural network aimbot that uses real-time object detection accelerated with CUDA on Nvidia GPUs.
Note: This project is very much under development, but right now, i'm putting it on the back burner due to other obligations that I have.
Lunar can be modified to work with a variety of FPS games; however, it is currently configured for Fortnite. Besides being easy-to-use, the main benefit of Lunar is that it is virtually undetectable by anti-cheat software (no memory is meddled with).
The basis of Lunar's player detection is the YOLOv5 architecture written in the PyTorch framework.
pip3 install -r requirements.txt
python lunar.py
- Train a custom model to detect players with a greater mAP than the YOLOv5s default person detection.
- Explore combining real-time object detection with pixel color tracking
- Implement smooth, natural player tracking (bezier curve)
If you have any suggestions or find any issues, please open an issue and provide some detail.