Add Face Verification

[pavitraag]

The Goal of the project is to do Face recognition task using Siamese Neural Network that is trained over a triplet loss function , This is useful in situations where you have limited dataset for training the model.

This codebase implements a face recognition system using a Siamese Neural Network architecture. It helps you understand how this approach works and tackles the challenge of large datasets by employing one-shot learning techniques.

Model Functionality:

Feature Extraction: Generates a 128-dimensional vector embedding for any input image, capturing its key features. Similarity Measurement: Compares the 128-dimensional vectors of two images to determine their similarity and classify them as belonging to the same person or not. Triplet Loss for Training:

The model leverages a triplet loss function during training. This function uses triplets of images: anchor (reference), positive (same person), and negative (different person). It aims to:

Minimize the distance between the anchor and positive embeddings. Maximize the distance between the anchor and negative embeddings. This approach helps the model learn robust representations for effective face discrimination.

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[pavitraag]

hey @akshitagupta15june can u please assign me this under gssoc24