Sports Celebrity Image Classification

In this end to end data science and machine learning project, we classify sports personalities. We restrict classification to only 5 people,

1. Maria Sharapova
2. Serena Williams
3. Virat Kohli
4. Roger Federer
5. Lionel Messi Plesae ⭐ this repository if you found it useful.

Folder structure

• UI : This contains ui website code
• server: Contains the Python flask server related code
• model: Contains python notebook for model building
• google_image_scrapping: Contains the code to scrap google for images
• images_dataset: Dataset used for training our model

Technologies used in this project,

• Python
• Numpy and OpenCV for data cleaning
• Matplotlib & Seaborn for data visualization
• Sklearn for model building
• Jupyter notebook, visual studio code as IDE
• Python flask for http server
• HTML/CSS/Javascript for UI

Installation :

A good practice to start with a new project and use it, is to make a virtual enviornment for the particular project. Here is the steps for making virtual enviornment ::

1. pip install virtualenv
2. python -m virtualenv myenv

Install the dependencies of the App ::

Run commands on python terminal or anaconda terimial or any terminal you are using in your system.

• pip install -r requirements.txt

Test the app:

• Clone the repository: git clone https://github.com/lionelsamrat10/Sports-Celebrity-Image-Classification.git
• Go to the project directory
• Go to Server Directory: cd Server
• Run the app: python app.py
• The development server will be up and running on port 5000 at the URL: http://127.0.0.1:5000/
• Now go to the UI Folder and open app.html on the browser. Note that the flask app server must be up and running.
• Drag an image of your favourite celebrity from the five and hit the classify button. Our app will predict the celebrity name with his/ her image. It will also show us the percentage match of our image with all the five celebrities.

Hope you like this project !!!