Deepface-image-detection-with-elastic-search

This repository contains the Jupyter Notebook Connect_elasticsearch.ipynb, which provides an example of how to connect to an Elasticsearch instance, perform basic queries, and handle the results. This code is designed for users who want to learn how to interact with Elasticsearch using Python.

Table of Contents

1. Installation
2. Usage
3. Elasticsearch Connection
4. Performing Queries
5. Handling Results

Installation

1. Clone the repository
2. Launch Jupyter Notebook

Usage

1. Open the Connect_elasticsearch.ipynb file in Jupyter Notebook.
2. Follow the instructions and comments provided in the notebook to understand each step of the process.
3. Execute each code cell in sequence by pressing Shift + Enter.
4. Modify the code as needed to adapt it to your own Elasticsearch instance or use case.

Elasticsearch Connection

The notebook provides code for connecting to an Elasticsearch instance by specifying the host, port, and authentication details (if required). Make sure to update these details to match your own Elasticsearch instance.

Performing Queries

The notebook includes examples of how to perform basic queries on your Elasticsearch instance, such as:

1. Indexing documents
2. Retrieving documents by ID
3. Updating documents
4. Deleting documents
5. Searching for documents using various query types

Handling Results

The notebook demonstrates how to handle the results returned from Elasticsearch, such as extracting relevant information from the search results or handling errors.