- python (3.9 +)
- OpenCV:
Installed with:
pip install opencv-python
- Matplotlib:
Installed with:
pip install matplotlib
- PyTorch:
Installed with:
pip3 install torch torchvision torchaudio --extra-index-url https://download.pytorch.org/whl/cu113
Or if you don't have access to an Nvidia GPU:pip3 install torch torchvision torchaudio
Record a video of CS:GO gameplay involving some kills from the player. Note that the video must be 1080p and run at 60fps.
Predict by running: python predict.py <video>
where <video>
contains the path to the video you want to make predictions on
While running, the program will display a window that shows the gameplay that is currently being analyzed along with the number of clips recorded so far. An additional window shows approximately what the parser is looking at. The program will run until either the video is finished, or the user presses ‘q’. Once finished, the clips will automatically be saved to a new folder.
The clips are automatically sent to the CNN for extraction. Once the features have been extracted, the program automatically predicts whether the clips involved the use of the aimbot and the output can be seen in the terminal.
- Record gameplay of CS:GO at 1080p 60fps
- Parse gameplay using
autoclip.py
- aimbot clips should be saved to
hacks_data_nn
- regular clips should be saved to
no_hacks_data_nn
- aimbot clips should be saved to
- Extract clip features using
save_cnn_output.py
- aimbot clips should be saved to
hacks_data_tensor
- regular clips should be saved to
no_hacks_data_tensor
- aimbot clips should be saved to
- Train RNN using
train_rnn.py
- Model will be saved to
models/model.pt
Any file with that name will be overwritten
To run the auto clipper by itself, run the following command: python ./auto_clip.py <input file> <output directory> <use time>
<input file>
is the file you want to parse<output directory>
is where you want the clips to be output to<use time>
(Optional, defaults to0
) adds a timestamp to the clips. Set to1
to turn the timestamps on, and0
to turn them off
To run the CNN by itself, run the following command: python save_cnn_output.py <clip directory> <output directory>
<clip directory>
is the directory where the clips are located<output directory>
is where you want to save the extracted features
To run the extracted features through the RNN, run the following command: python test_rnn.py <.pt path> <clip path>
<.pt path>
is the path to the .pt file output from the CNN<clip path>
(Optional, displays timestamps when specified) is the path to clips corresponding to the .pt file are saved
To train the RNN, run the following command: python train_rnn.py
To validate the RNN, run the following command: python validate_rnn.py
https://github.com/SrikarValluri/aimbot-detection
- Cheat detection for multiple games and different cheats
- Website for easy access and use