Similarity search web service

Perform similarity search against an uploaded dataset of images.

Features

This project implements a web service that allows to:

• perform image similarity search against custom datasets
• directly link the resulting images to entries in a data repository
• work directly with data hosted on HeidICON, Heidelberg University's media data base

Installation

The recommended way of setting up an instance of similarity webservice is to use Docker.

Docker

git clone https://github.com/ssciwr/similarity-webservice.git
cd similarity-webservice
docker compose up

For customization of the deployment, you may want to look at and tweak

• docker-compose.yml for e.g. mounted volumes
• ./frontend/nginx.conf for SSL setup

The page will be served to localhost.

Development Installation

Required setup:

git clone https://github.com/ssciwr/similarity-webservice.git
cd similarity-webservice

Now, you need to start the backend:

python -m pip install ./backend
similarity_webservice

And separately, the frontend:

cd frontend
npm install
npm run dev

Usage

Usage as a web service

Accessing the web service through a web browser, you can upload a query image and look at the results. In order to create new collections you should do the following:

• Click on Collection Management
• Enter your API key (see below for generation)
• At the bottom of the page, enter a new name for the dataset and determine whether the data is located on HeidICON.
  • If the data is located on HeidICON, provide the name of the tag that is applied to the data on HeidICON.
  • Otherwise, click the Upload Data button and select a CSV file. It is expected to have a row per image and two columns: One for the image URL and one for the URL to link to when clicking on the image.
• Click the Finetune model button (this may take a while)

Usage via the REST API

This service can be used via a REST API. We refer to the API documentation

Creating an API key

This will typically be done by a systems administrator with command line access to the running instance.

docker exec -it <containername> bash
python -m similarity_webservice.auth --help
python -m similarity_webservice.auth create

The name of the running backend container can be determined using docker ps -a.

License

This work is licensed under the MIT license.