An Image Management Proof Of Concept

If you have thousands of digital images on a laptop, desktop PC or in the cloud, organizing them is a big task. To make this process easier, I recently did some proof of concept work to create an image management utility using Python.

Why Python?

Python is a great choice due to its (1) ease of use,(2) compatibility with Windows, macOS, and Linux, and (3) it's extensive and versatile library support.

A Command Line Script Foundation

I began by creating Python command-line scripts to locate and update image metadata. These scripts formed the core of the utility, making image management more efficient. I also created scripts for:

• Device ID Generation for Tracking: This generates a globally unique device ID for tracking the workstation or device in use. This ID is stored along with image file paths and additional meta data items.
• Image Quantity and Size Analysis: This allows you to analyze the quantity and size of your images, providing valuable insights to help organize your image catalog(s). This script uses the popular Python pandas library.
• Creation of Multiple Catalogs for Different Years: You can create multiple catalogs for different years, making it easy to partition images by year.

Choosing JSON for Data Storage

For data storage, I chose JSON, a simple and human-readable text format. It allowed me to store image metadata in an organized way. JSON also offered the flexibility to migrate the data to databases like PostgreSQL.

tkinter

To streamline the process, I added a graphical user interface (GUI) using tkinter. tkinter's simplicity made it perfect for creating a user-friendly interface that includes a 'Picture Deck' option for easily viewing and navigating through a large image collection.

Image Cataloger is a working proof of concept that can assist in collecting and managing a large number of images. The source code is open and located here: https://github.com/kds-github/image_cataloger.

Thanks for stopping by.