Searching for images on Wikimedia Commons mainly depends on titles, categories and descriptions. This makes it hard to find images when the metadata is missing, incomplete or doesn’t match the exact words used in the search.
For example, a query like:
- “people cooking street food in Indian night markets”
- "foggy mountains in the Western Ghats at sunrise”
- “photos of 19th-century Indian temples during monsoon”
do not return good results today.
Proposed Idea Introduce a new way to search images using natural language.
Instead of relying only on keywords, users can type full descriptions and the system will try to understand the meaning and show visually relevant images.
Benefits
- Makes image search more intuitive and user-friendly
- Helps discover images even when they are not well tagged
- Supports more descriptive and creative searches
- Improves overall accessibility of Wikimedia Commons
Possible Approach
- Start as an experimental feature/tool
- Test on a smaller set of images first
- Compare results with current search
- Gather feedback from users and contributors
Open Questions
- How should this be introduced to users (separate search option or part of existing search)?
- What is the best way to evaluate if results are actually better?
- How can this work well across different languages?
Next Steps
- Build a small prototype
- Test with sample queries
- Share results with the community
- Iterate based on feedback
Some refs:
