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Open Image Search

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What Open Image Search is

Open Image Search is a free, open-source prototype for finding visually similar digitized prints and their metadata. It is aimed at graphical collections and museums; its hosted demo searches more than 20,000 prints from the Graphische Sammlung of ETH Zürich. Collections can also clone the project and run retrieval locally using their own image data. The search process extracts image features with VGG16 and uses a k-nearest neighbors model to locate similar images. Collections can provide metadata in a CSV file, following the column names described in the project documentation. Its mobile-friendly web interface can send a search request using a phone camera. The backend reformats uploaded images in memory before sending them to the feature extraction model, then uses the results to retrieve metadata for top matches. The project lists Vue, Django, TensorFlow, scikit-learn, SQLite, and Nginx among its technologies. It is available as a hosted web application or for self-hosting under the MIT license. The project is described as a prototype in development, and its repository was archived on September 1, 2026, making it read-only.

Who it suits

Open Image Search suits graphical collections and museums working with digitized prints or paintings. It may also suit collections that want to run image retrieval locally with their own image data.

What it does well

  • Hosted demo searches over 20,000 prints
  • Can run locally with collection image data
  • Accepts metadata supplied in CSV files
  • Web interface supports phone-camera searches
  • MIT-licensed and available for self-hosting

What to know first

  • Project remains at prototype stage
  • Repository is archived and read-only

Limits

The project is described as a prototype in development, and its repository is archived and read-only.

Getting started

  1. Open the online application to search the Graphische Sammlung of ETH Zürich.
  2. For local use, clone the project from its GitHub website.
  3. Prepare your own image data and metadata in a CSV using documented column names.
  4. Run image retrieval locally with your collection’s data.

Verdict

Open Image Search offers a focused way to locate similar prints and associated metadata, either through its hosted demo or local setup. Its prototype status and archived, read-only repository are important constraints for collections considering it.

Questions

Is Open Image Search free?

Yes. It is listed as free and open source under the MIT license.

What can I search?

The hosted application searches more than 20,000 prints from the Graphische Sammlung of ETH Zürich. You can also run retrieval locally with your own image data.

Can I use it on a phone?

Yes. Its web interface is designed for mobile devices and can send a search request from a phone camera.

Can collections provide their own metadata?

Yes. Metadata can be supplied in a CSV file using column names described in the project documentation.

Is the project still being developed?

The project is described as a prototype in development. Its GitHub repository was archived on September 1, 2026, and is read-only.

Facts from Open Image Search's own pages

Backend
A Django REST Framework API reformats uploaded images in memory, sends them to the feature extraction model, and uses the results to retrieve metadata for top matches. · github.com, 8 Oct 2026
Development status
The README describes the application as in development and in a prototype phase. · github.com, 8 Oct 2026
Headquarters
Zurich, Switzerland · github.com, 28 Sept 2026
Hosted access
The README links to an online application where users can upload pictures to find visually similar prints from the Graphische Sammlung of ETH Zürich. · github.com, 8 Oct 2026
Hosted collection
The README says the hosted demo lets users search a database of more than 20,000 prints from the Graphische Sammlung of ETH Zürich. · github.com, 7 Oct 2026
Image handling
Uploaded images are reformatted in memory before a request is sent to the feature extraction model. · github.com, 7 Oct 2026
Intended users
The project is aimed at graphical collections and museums working with digitized prints and paintings. · github.com, 7 Oct 2026
License
The software is distributed under the MIT License, which permits use, copying, modification, distribution, and sale subject to its terms. · github.com, 8 Oct 2026
Local use
The project can be cloned and run locally with a user’s own image data, metadata, and installed software dependencies. · github.com, 8 Oct 2026
Metadata
Users can supply image metadata in a CSV file, with permitted column names described in the project documentation. · github.com, 7 Oct 2026
Mobile access
The web interface is designed to work on mobile devices and supports sending search requests directly from a phone camera. · github.com, 7 Oct 2026
Mobile interface
The Vue web interface is designed to work on mobile devices and can send search requests from a phone’s camera. · github.com, 8 Oct 2026
Project status
The repository describes the application as in development and says it is in a prototype phase. · github.com, 7 Oct 2026
Purpose
Open Image Search is a prototype reverse image search tool for finding digitized print metadata and supporting workflows at graphical collections and museums. · github.com, 8 Oct 2026
Repository status
GitHub says the repository was archived by its owner on September 1, 2026, and is read-only. · github.com, 8 Oct 2026
Search method
The application extracts image features with VGG16 and uses a k-nearest neighbours model to find similar images. · github.com, 8 Oct 2026
Support
The README directs inquiries to the ETH Library Lab contact form. · github.com, 8 Oct 2026
Technology
The README lists TensorFlow, scikit-learn, Vue, Django, SQLite, and Nginx among the project’s libraries and frameworks. · github.com, 8 Oct 2026

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