Introducing image-filename-ai: AI-Powered Image Organization for Developers

I was working on a client project last month that involved processing hundreds of product images for an e-commerce site. Each image had generic names like "IMG_2847.jpg" or "photo_final_v3.png" that told me nothing about their content. After spending hours manually renaming files and writing alt text descriptions, I realized there had to be a better way. That's when I built image-filename-ai - a Python CLI tool that uses Google's Gemini AI to automatically generate descriptive, SEO-friendly filenames and alt text for images.

Today I'm excited to announce that image-filename-ai is now available on PyPI, ready to help developers and content creators organize their image libraries intelligently.

The Problem with Generic Image Names

Every developer has encountered this scenario: you inherit a project with a media folder full of cryptically named images, or you're working with a designer who exports everything as "Untitled-1.png". These generic filenames create several problems:

Your project becomes harder to navigate and maintain. Finding specific images requires opening each file individually. SEO opportunities are lost because search engines can't understand what your images contain. Content management becomes a nightmare as your image library grows.

I needed a solution that could process images in bulk while preserving the careful folder structures that organize different sections of a website or application.

How image-filename-ai Works

The tool combines Google's powerful Gemini vision model with practical batch processing capabilities. When you point it at a directory of images, it analyzes each one and generates descriptive names based on the actual content it sees.

Here's what happens under the hood: the AI examines each image and creates a filename that describes the main subjects, actions, or objects it identifies. Instead of "DSC_0892.jpg", you get "golden-retriever-playing-in-autumn-leaves.jpg". The tool also generates comprehensive alt text descriptions that you can use for web accessibility.

Getting Started

Installation is straightforward since the package is now available on PyPI:

pip install image-filename-ai

Once installed, you can start processing images immediately. The simplest usage processes all images in a directory:

image-filename-ai --input-dir ./photos --output-dir ./processed

This command will analyze every image in your photos directory, generate new descriptive filenames, and save the renamed files to the processed directory while maintaining your original folder structure.

Key Features That Make It Practical

What sets this tool apart from simple AI image description services is its focus on real-world development workflows. The CLI includes several features that I found essential during my own projects:

The resume functionality means you can interrupt processing and continue where you left off without re-analyzing images you've already processed. This is crucial when working with large image libraries that might take hours to process.

Multiple logging modes accommodate different project structures. You can choose central logging for simple projects, per-folder logging for complex site structures, or flat logging for streamlined workflows.

Rate limiting and exponential backoff ensure reliable processing even when working with Google's API limits. The tool automatically handles temporary failures and respects API quotas.

Language support means you can generate filenames and alt text in multiple languages, which is particularly valuable for international projects or multilingual websites.

Beyond the Command Line

While the CLI covers most use cases, the project also includes a FastAPI-based web service for integration into larger applications. This makes it possible to add AI-powered image organization to existing content management systems or automated workflows.

The entire project follows modern Python packaging standards with comprehensive testing, linting, and automated deployment through GitHub Actions. This ensures reliability and makes it easy for other developers to contribute or extend the functionality.

Real-World Impact

Since deploying this tool on my own projects, I've processed thousands of images that would have taken days to organize manually. The generated filenames are not only descriptive but also SEO-friendly, following web naming conventions automatically.

The alt text generation has been particularly valuable for accessibility compliance. Instead of leaving alt attributes empty or writing generic descriptions, I now have detailed, accurate descriptions that improve the experience for users with screen readers.

Try It Today

If you're dealing with image organization challenges in your development work, image-filename-ai can save you significant time while improving your project's maintainability and SEO performance. The tool is open source and available on GitHub, where you can also find detailed documentation and configuration options.

Installation takes seconds, and you can start seeing results immediately. The AI-generated names are surprisingly accurate and follow consistent naming conventions that make your image libraries much more navigable.

Let me know in the comments if you give it a try, and subscribe for more practical development tools and guides.

Thanks, Matija