Hands-free Temple Run

A temple run game controlled using face positions.

---

Prerequisites

Download and install Python 3.x (link)

Clone the repository

git clone https://github.com/priyanksharma7/temple-run.git

(Optional) Create and activate a virtual environment

python -m venv virtual_env
.\virtual_env\Scripts\activate

Install dependencies

pip install opencv-contrib-python imutils pyautogui flask

How to run

game.py : A python program that uses Haar Cascade Classifier for face detection and Opencv KCF tracker to register face movements from the camera's live stream. When the face lands on one of the four boxes, appropriate action is simulated using the pyutogui library.

python game.py

Note: Press 'q' to exit.

app.py : A Flask web application that implements the game controls logic and displays the Temple Run game as well as instructions together on a webpage.

python app.py

Note: Press 'Ctrl+C' in the terminal to exit.

---

Acknowledgements

Taha Anwar, Training a Custom Object Detector with DLIB & Making Gesture Controlled Applications, https://learnopencv.com/training-a-custom-object-detector-with-dlib-making-gesture-controlled-applications/

Nakul Lakhotia, Video Streaming in Web Browsers with OpenCV & Flask, https://towardsdatascience.com/video-streaming-in-web-browsers-with-opencv-flask-93a38846fe00

Oluwaseun Ilori, Deploying Your First Opencv Flask Web Application On Heroku, https://medium.com/analytics-vidhya/deploying-your-opencv-flask-web-application-on-heroku-c23efcceb1e8