Awesome
Deep Learning Anti-Cheat For CSGO
Input the directory with your .dem files and the model outputs predictions for every shot during the game.
from DLAC import Model
model = Model("./path_to_demos/")
model.predict_to_terminal(threshold=0.95) # You can manually specify threshold, 0.95 by default
Installation
Windows should be as easy as:
pip install DLAC
Linux users will need to build the .so file. This requres GO.
git clone https://github.com/LaihoE/DLAC
cd DLAC
python3 setup.py install
cd DLAC
go build -o parser.so -buildmode=c-shared
You can choose between a bigger and a smaller model
from DLAC import Model
model = Model("./path_to_demos/", model_type='big')
model.predict_to_terminal(threshold=0.99) # 0.99 is recommended with the bigger model
The bigger model is slower with slightly better accuracy
Other ways to output predictions
model.predict_to_csv()
model.predict_to_list()
Example output from one shot
Name, Confidence of cheating, SteamId, File
PeskyCheater22, 0.9601634, 123456789, exampledemo.dem
Special thank you to
Demoinfocs-golang is the underlying parser used for parsing the demos, found at:
https://github.com/markus-wa/demoinfocs-golang.
87andrewh has written the majority of the specific parser used, found at: https://github.com/87andrewh/DeepAimDetector/blob/master/parser/to_csv.go