Politician-Face-Classifier Web Application

GitHub link

Web Application

Web Scraping

  • Collected images from google through web-scraping using Selenium with ChromeDriver Code Link

Data Cleaning

  • Performed data cleaning through face detection using OpenCV pre-trained feature-based Haar cascade classifiers to discard images from the dataset without face and two eyes visible

Feature engineering

  • Performed feature engineering through extraction by wavelet transformation of images using PyWavelets and then vertically stacking raw and wavelet transformed images

Model Building

trained machine learning models such as Logistic Regression, SVM(Support vector machine), and Ensembling bagging Random Forest

Model performance

Achieved 85% test accuracy after hyper tuning the model With Logisic regression

User interface

  • Used HTML,CSS and JavaScript,

Productionization

  • Deployed model to production using Flask

Technologies

  • Python
  • Numpy and OpenCV for data cleaning
  • Matplotlib & Seaborn for data visualization
  • Sklearn for model building
  • Python flask for HTTP server
  • HTML/CSS/Javascript for UI

link