Project VII: Celebrity Face Recognition WebApp
In this data science and machine learning project, we classify sports personalities. We restrict classification to only 5 people. In this model firstly we collected images of the athletes from the internet and then cropped all the face detected in images using OpenCV. Then we Wavelets transformed the images to extract the key feature of the faces. Then we created a training set to train the data. We tried many algorithms but chose SVM as it was giving the best results. Then we created a flask application as a backend to handle the input and return output.
Web App - https://celebrity-face-recognition.herokuapp.com/
Visualization
Cropping all the images where face and eyes are being detected
Detecting key features from the face images using Wavelet Transformation.
Performance of Algorithms on Training Set
Performance of Algorithms on Training Set
Confusion Matric of testing X_test on the model
Five Celebrities
- Maria Sharapova
- Serena Williams
- Virat Kohli
- Roger Federer
- Lionel Messi
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 and pycharm as IDE
- Python flask for HTTP server
- HTML/CSS/Javascript for UI
Deployment
This Model is deployed on Heroku Server