GithubHelp home page GithubHelp logo

lionelsamrat10 / sports-celebrity-image-classification Goto Github PK

View Code? Open in Web Editor NEW
4.0 1.0 5.0 174.44 MB

This is a machine learning (Image Classifier) web app, that lets the user upload an image of a sports celebrity (Lionel Messi, Maria Sharapova, Roger Federer, Serena Williams, Virat Kohli) and predicts whose image is uploaded.

Jupyter Notebook 98.20% Python 0.88% CSS 0.08% HTML 0.55% JavaScript 0.30%
image-classification opencv machine-learning flask python image-processing wavelet-transform gridsearchcv hyperparameter-tuning svm-classifier logistic-regression

sports-celebrity-image-classification's Introduction

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 โญ 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 !!!

sports-celebrity-image-classification's People

Contributors

lionelsamrat10 avatar

Stargazers

 avatar  avatar  avatar  avatar

Watchers

 avatar

Recommend Projects

  • React photo React

    A declarative, efficient, and flexible JavaScript library for building user interfaces.

  • Vue.js photo Vue.js

    ๐Ÿ–– Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.

  • Typescript photo Typescript

    TypeScript is a superset of JavaScript that compiles to clean JavaScript output.

  • TensorFlow photo TensorFlow

    An Open Source Machine Learning Framework for Everyone

  • Django photo Django

    The Web framework for perfectionists with deadlines.

  • D3 photo D3

    Bring data to life with SVG, Canvas and HTML. ๐Ÿ“Š๐Ÿ“ˆ๐ŸŽ‰

Recommend Topics

  • javascript

    JavaScript (JS) is a lightweight interpreted programming language with first-class functions.

  • web

    Some thing interesting about web. New door for the world.

  • server

    A server is a program made to process requests and deliver data to clients.

  • Machine learning

    Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.

  • Game

    Some thing interesting about game, make everyone happy.

Recommend Org

  • Facebook photo Facebook

    We are working to build community through open source technology. NB: members must have two-factor auth.

  • Microsoft photo Microsoft

    Open source projects and samples from Microsoft.

  • Google photo Google

    Google โค๏ธ Open Source for everyone.

  • D3 photo D3

    Data-Driven Documents codes.