Popular Person Identification with Streamlit

This project identifies popular persons from uploaded images using SVM and Naive Bayes classifiers, with PCA and LDA for feature reduction.

Features

• Upload an image (JPG/PNG) for classification.
• Uses PCA and LDA for feature extraction.
• Predicts identity using SVM and Naive Bayes models.
• Displays the predicted person's name.

Setup

1. Install required libraries:

   pip install streamlit joblib numpy pillow pandas scikit-learn

2. Ensure the following models are in the directory:
   • svm_model.pkl, NB_model.pkl, pca_model.pkl, lda_model.pkl
3. Add target_data.csv with a column person_name for class labels.
4. Run the app:

   streamlit run app.py

File Structure