enigmaceo/example-cat-vs-dog-classification-svm

Cat vs Dog Classification with SVM

A simple and efficient cat vs dog image classifier using Support Vector Machines.

Features

• —Upload & Classify: Upload cat or dog images for instant classification
• —Real-time Results: Get predictions with confidence scores
• —Clean Architecture: Models loaded from separate Hugging Face repository

How to Use

1. 1.Click "Upload Image" to select a cat or dog photo
2. 2.View the prediction results with confidence scores
3. 3.The model uses HOG, color histogram, and LBP features

Model Information

This application loads the trained SVM model from the Model Repository.

• —Model: SVM with RBF kernel (87% accuracy)
• —Features: HOG + Color Histogram + LBP
• —Training: Balanced dataset of 2000 images

API Endpoints

• —GET /: Interactive dashboard
• —POST /api/predict: Image classification
• —GET /api/health: Service health check

Environment Variables

• —HF_MODEL_REPO: Model repository name (automatically set)

Technical Stack

• —Backend: FastAPI with Python
• —Frontend: HTML5 + Tailwind CSS
• —Machine Learning: scikit-learn SVM
• —Deployment: Docker on Hugging Face Spaces