Android App used to get NBA player statistics data from image recognition.
This is an educational project.
gain hand-on expirience and knowledge in new technologies, methodologies and platforms. We aim to deploy this app to a running environment so users can download and use it on their android OS.
- Frontend: React Native
- Backend: Express.js and Flask
- Machine Learning: Ultralitics (Yolo v8)
- Database: Firebase
- Authentication: Google Auth
These instructions will get you a copy of the project up and running on your local machine for development and testing purposes.
- ✔️ Set Up Client, Express, Flask.
- ✔️ User Authentication.
- ✔️ Database Connection.
- 🔲 Improve UI design.
- 🔲 Improve model predictions.
- 🔲 Deploy Servers to working environment.
- 🔲 Etc.
Before you can run this project on your local machine, you'll need to have the following software installed:
- Node.js
- npm
- Python
- pip
- Flask
- Android Studio
Clone the repository to your local machine Install the project dependencies by running npm install in the project root directory Start the frontend by running npm start in the frontend directory Start the backend by running python app.py in the backend directory
Explain how to run the automated tests for this system
Break down into end to end tests Explain what these tests test and why
Copy code Give an example Deployment Add additional notes about how to deploy this on a live system
- React Native - Frontend framework
- Express.js - Backend framework
- Flask - Backend framework
- Firebase - Database
- Google Auth - Authentication
- Yolo V8 - CV Model
This project is licensed under the MIT License - see the LICENSE.md file for details.
etc.