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Dimensionality Reduction and face classification using PCA on AT&T Face dataset.

This is a numpy based implementation of PCA for dimensionality reduction and image classification using K-Nearest-Neighbors.

  • To run the program in default mode run:
python3 main.py
  • To run in PCA mode(default mode):
python3 main.py --mode=pca
  • To run in image reconstruction mode:
python3 main.py --mode=image_recons --nPC=30(your choice)

It will also save few reconstructed image samples.

  • To run in image classification mode:
python3 main.py --mode=face_classification --nPC=30(your choice)

With k=40, I am getting face recognition of 92.1 % on AT&T Face dataset.

Please check other flags for more information.