End to end machine learning project for football player image classification

In this project I have collected photos of my all time favourite players and tried to do EDA. After performing EDA I trained multiple models and took the best one. Then I build a UI for user to drag and drop his/her own player image and the Flask server will come up with the prediction.

I took the dataset from here and also by manual downloading using the Fatkun batch image downloader.

Built With

• Python, HTML, CSS, JavaScript, jQuery
• Flask

Getting Started

git clone https://github.com/Micky373/end_to_end_football_players_image_classification.git

cd end_to_end_football_players_image_classification

pip install -r requirements.txt

cd server

python sever.py

After the flask server is succesfully loaded go to the client directory and open the html cd ../client

Then the UI will open

Here drag and drop a clear picture of one of the 5 players and click classify

In the test_images section I have provided 5 sample images you can check the classification using those too

All the EDA, model training and predicting is clearly shown is found in the notebooks folder.

Currently I have worked on simpler less number of images, my future plan is to come up with a robust model trained with vast data.

Author

• GitHub: @GitHub

• LinkedIn: LinkedIn

🤝 Contributing

Contributions, issues, and feature requests are welcome!

Feel free to check the issues page.

Show your support

Give a ⭐️ if you like this project!

Acknowledgments

• Special thanks to Dhaval Patel
• The UI implementation and code flow done with the help of this play list