Fashion MNIST Image Storage in PostgreSQL Database

Description

This repository contains code for storing Fashion MNIST dataset images in a PostgreSQL database. The Fashion MNIST dataset is a collection of 28x28 grayscale images of fashion items, such as shirts, pants, shoes, etc. This dataset is commonly used for training and testing machine learning models.

Files

1. fashion_mnist_to_postgres.py: This Python script demonstrates how to load the Fashion MNIST dataset using Keras, preprocess the data, and store it in a PostgreSQL database.
2. fashion_mnist.db: This is the PostgreSQL database file where the images and their corresponding labels are stored.

Dependencies

• Python 3.x
• TensorFlow (for loading the Fashion MNIST dataset)
• psycopg2 (Python library for connecting to PostgreSQL database)
• pandas (Python library for data manipulation and analysis)

Usage

1. Make sure you have Python installed on your system.
2. Install the required dependencies using pip:

pip install tensorflow psycopg2 pandas

3. Ensure you have PostgreSQL installed and running on your system.
4. Update the database connection details (dbname, user, password, host, port) in the Python script (fashion_mnist_to_postgres.py) according to your PostgreSQL setup.
5. Run the Python script to execute the code:

python fashion_mnist_to_postgres.py

Note

• This code assumes that you have already set up a PostgreSQL database named fashion_mnist.db with appropriate permissions.
• The Fashion MNIST dataset will be split into training and testing sets. Images and their corresponding labels will be stored in the images table within the database.
• The images are stored as binary data (BYTEA type) in the database.
• After executing the script, you can verify the data stored in the database by running a SELECT query on the images table.