face similarity pinecone

Face Similarity Matching Using PineCone

Project Overview

Face Similarity Matching Using PineCone is a sophisticated image verification system designed to recognize repeat customers efficiently. It leverages advanced machine learning techniques for accurate facial recognition, enhancing both security and customer experience.

Purpose

The project aims to automate the identification of repeat customers using facial recognition, thus offering a more personalized and secure interaction.

Key Features

1. Facial Recognition: Uses MTCNN for accurate face detection in customer images.
2. Vector Embedding: Converts facial images into numerical vectors using the DeepFace-FaceNet model.
3. Efficient Database Management: Employs Pinecone, a vector database, for storing and querying facial embeddings.
4. API Functionality: Provides a set of APIs for matching images, upserting, deleting, and updating vectors with API key authentication for secure access.

Technologies

1. MTCNN (Multi-Task Cascaded Convolutional Neural Networks)
2. DeepFace-FaceNet Model
3. Pinecone Vector Database
4. RESTful API services

Workflow

1. Initial Setup:

   • Face detection using MTCNN.
   • Transformation of faces into embeddings with DeepFace-FaceNet.
   • Pinecone database setup and embedding upsertion.

2. API Usage:

   • ValidateImage API: Queries the Pinecone database to find the closest match for a given facial vector.
   • AddImageToIndex API: Add new facial vectors in the database.
   • DeleteImageFromIndex API: To remove existing facial vectors from the database.
   • ReplaceImage API: Updating existing facial vectors in the database.

Prerequisites

1. Python 3.9+
2. Access to customer image data
3. Pinecone API key

Installation

Install the necessary Python packages:

pip install mtcnn deepface pinecone-client

Configuration

Configure the Pinecone API key and database settings. Set the top_k parameter based on the desired matching precision.

API Authentication

1. Implement API key authentication to validate and secure API usage.
2. Ensure proper management of API keys to prevent unauthorized access.

Testing API

Run command to test API using Postman:

uvicorn app_fastapi:app --host 127.0.0.1 --port 5000 --reload

Data Privacy

Adhere to data privacy laws and ensure secure handling of sensitive customer data, especially facial images.

Contact

For queries or contributions, contact: [email protected].

Happy Coding!