Shreyas2409 / Face-Recognition Public

Notifications You must be signed in to change notification settings
Fork 0
Star 0

Achieved accurate face recognition capabilities through a model employing SVM, Random Forest, and PDA, demonstrating effectiveness in accomplishing project goals.

0 stars 0 forks Branches Tags Activity

Name		Name	Last commit message	Last commit date
Latest commit History 15 Commits
LICENSE		LICENSE
README.md		README.md
ml_final.py		ml_final.py

Repository files navigation

Face-Recognition

Developed an advanced face recognition system by converting images to grayscale and extracting features using Haar Cascade, which were saved in pickle format. Principal Discriminant Analysis (PDA) was employed for dimensionality reduction. Multiple classifiers, including Support Vector Machine (SVM), Random Forest, and Logistic Regression, were trained on the processed data. The SVM classifier achieved the highest accuracy, demonstrating the system's effectiveness in accurately recognizing faces.