STRIKE A POSE!

Predictive Body Pose Classification via Sequential Neural Network Analysis in a Motion-Controlled Videogame

Intro

"STRIKE A POSE!" is an interactive, motion-controlled videogame.

It's a fun workout challenge using body pose classification, in which to follow along with various exercises:
From squats to standing, hiding, making an X, or striking a unique pose of your own, you'll work up a sweat! 🏋️

You have the flexibility to adjust the number of rounds and the time between poses for an extra challenge.

Data collection, model training, and the game script are modularized, making it easy to customize to meet your unique workout needs. 💪

Demo

Turn the audio on! 🎧
Check out the demonstration video in better quality here.

STRIKE_A_POSE_demo.mp4

Installation

To get started with "STRIKE A POSE!", follow these steps:

1. Clone this Git repository to your local machine:

   git clone https://github.com/alx-sch/STRIKE_A_POSE_Body_Pose_Classification_Game.git
   

2. Optional: Create and activate a virtual environment for better isolation of dependencies:

   python3 -m venv envname # Create a virtual environment (macOS/LINUX)
   source envname/bin/activate # Activate the virtual environment
   
   deactivate # Deactivate the virtual environment when not needed anymore
   

3. Install the game-specific requirements.

   pip install -r requirements.txt
   

How to Play

To enjoy "STRIKE A POSE!", follow these steps:

1. Open a terminal and navigate to the project directory.

2. Start the game by specifying the number of rounds and the time between poses. For example:

   python play.py 10 5  # Start with 10 rounds and 5 seconds between poses
   

3. A window with a video feed will appear. Adjust your position and camera angle to fit the green square.

4. Controls:

• Press the 'Space' key to start the countdown.
• You can press 'R' to restart the script execution or 'Q' to quit the game

Make it Yours!

Adjust the game to your needs! 💪
Please refer to the documentation in collect_data.py, train_model.ipynb, and play.py for details.

• Collect training data of poses of your choice with collect_data.py.
• Train a new model to detect these new poses and evaluate the model's performance using train_model.ipynb. You are encouraged to explore and experiment with different model architectures.
• Adjust the model used, poses, and respective sound files (see Audio Credits) in play.py to start your new Pose Game!

Audio Credits

• Background music is sampled by KevWest: Funky Disco Beat.
• Sound effects are downloaded from Pixabay (CC0 License).
• Commands and in-game speech are generated using the Python library gTTS (Google Text-to-Speech).

Acknowledgments

I would like to thank Daniel Bärenbräuer for his outstanding project "Live Sign Language Translator", which served as a valuable source of inspiration for "STRIKE A POSE!".