🎮 'Play model': Choose and select a trained model to be played.
🔄 'Train from existing model': Continue training from a previously trained model.
🆕 'Start a new model': Creates a new model to train.
🕹️ 'Agent actions': Seamlessly choose what your AI actions will be.
📊 'Load logs': Easily open your Tensorboard logs to view the trained model stats.
🎯 'Select parameters': Click and drag to select your window, finish, and score locations.
📸 'Preview': Takes a screenshot of your screen with the parameters.
⚙️ 'Advanced Settings': Change your model settings.
🖱️ 'Reset Click': Select a point on the Desktop for the agent to click once the environment resets.
👁️ 'Ai View': View what your agent is seeing with the current FPS and actions being taken.
🔢 'Use a counter as reward': Uses a counter instead of the score location as a reward system (INCREASES AI FPS).
mss
pyautogui
opencv-python
numpy
gymnasium
stable-baselines3
torch
subprocess.run
Pillow
easyocr
Change into the project directory using the command line:
cd your-repository
Create a Virtual Environment (Optional, but Recommended)
To avoid conflicts with other projects, it's a good practice to create a virtual environment. Run:
python -m venv venv
Activate the virtual environment:
On Windows: venv\Scripts\activate
On macOS/Linux: source venv/bin/activate
Install the Dependencies
pip install -r requirements.txt
If you encounter any issues with the installation, ensure that you have the correct versions of Python and pip.
Make sure you're in the project directory where requirements.txt is located when running the pip install -r requirements.txt command.
Introducing.Lunai.-.Reinforcement.Learning.without.any.Coding.mp4
