Contestant Disposer
Sports celebrity image classification system using OpenCV and Machine Learning.
System Architecture Flow
Image Upload
User uploads a photo via Dropzone.js frontend.
Preprocessing
OpenCV detects face/eyes and applies Wavelet Transform.
Classification
SVM model predicts the celebrity identity from extracted features.
Result Display
API returns the result with confidence scores to the UI.
What we have used
OpenCV for face and eye detection to crop and preprocess images.
Wavelet Transform for feature extraction from images.
SVM (Support Vector Machine) classifier for identifying specific athletes.
Flask backend to process image uploads and return classification results.
Dropzone.js for a smooth drag-and-drop image upload experience.
Uses & Applications
Automatically identifies famous sports personalities (e.g., Messi, Federer, Serena Williams) from photos.
Can be integrated into sports news portals or fan engagement platforms.
Showcases image preprocessing and classification techniques in a web environment.
Future Roadmap
Expanding the dataset to include a wider range of athletes and public figures.
Implementing Deep Learning (CNNs) to handle lower-quality or partially obscured images.
Developing a mobile-responsive interface for on-the-go celebrity identification.