Lunar is a neural network aimbot that uses real-time object detection accelerated with CUDA on Nvidia GPUs.

Lunar can be modified to work with a variety of FPS games; however, it is currently configured for Fortnite. Besides being general purpose, the main advantage of using 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.

1. Install a version of Python 3.8 or later.

2. Navigate to the root directory. Use the package manager pip to install the necessary dependencies.

pip install -r requirements.txt

python lunar.py

To update sensitivity settings:

python lunar.py setup

To collect image data for annotating and training:

python lunar.py collect_data

If you have image data with or without annotations, please send that in a zip file to [email protected].

• As of now, the aimbot is set to only work when targeting/scoping in (holding down the right mouse button). Therefore, it is not recommended to use at a close range.
• There is a known issue that occurs with PyTorch and GTX 1650/1660 GPUs on Windows

• Use TensorRT for faster inference
• Train a model on a custom dataset
• Explore combining real-time object detection with k-means pixel clustering
• Implement better player tracking
• Make an easy-to-use GUI

Pull requests are welcome. If you have any suggestions, questions, or find any issues, please open an issue and provide some detail. If you find this project interesting or helpful, please star the repository.