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Reverse Image Search Plugin

A FiftyOne plugin that searches an image dataset for visually similar items using a query image supplied by URL or upload and a similarity index already present on the dataset.

Explore the practical guide ↓

Independent OpenViST project profile, based on linked sources.

Reverse Image Search Plugin — OpenViST project profile in AI Data & Analytics.
OpenViST project illustration. See the linked sources for product details.
Understand the project

Practical overview

When it fits

Use it when working in FiftyOne with an image dataset that already has a similarity index and you want a reference image to drive retrieval.

Who it is for

  • FiftyOne users exploring or curating image datasets
  • Computer-vision practitioners who want to retrieve dataset examples from a reference image

Documented uses

  • Search an indexed dataset using an image URL.
  • Search an indexed dataset by uploading a query image.
  • Inspect visually similar dataset images returned by the configured similarity index.
Before you choose

Requirements & limits

  • The dataset must have a similarity index before the search panel becomes active.
  • The README demonstrates index creation with FiftyOne Brain and gives CLIP ViT-B/32 Torch with cosine distance as an example.
  • Milvus is an alternative backend with separate package and Docker-server setup requirements.

Check current requirements in the official documentation. Source-based guidance does not mean OpenViST has run or independently tested this project.

Source-based practical guide

Configure a dataset for Milvus-backed reverse search

Prepare a dataset similarity index to use Milvus as its backend.

Before you start

  • FiftyOne and a dataset
  • Docker
  • The pymilvus Python package

Steps

  1. Install pymilvus with the command below.

    Documented command
    pip install pymilvus

  2. Download the documented Milvus standalone Docker Compose file with wget https://github.com/milvus-io/milvus/releases/download/v2.2.11/milvus-standalone-docker-compose.yml -O docker-compose.yml.

  3. Start the server with sudo docker compose up -d.

  4. Add backend="milvus" to the compute_similarity call used to create the dataset index.

Expected outcome

The similarity index is configured to use Milvus as its backend.

Guide limitations

  • A similarity index is still required for the plugin’s search panel.
Documentation 1 ↗
Evidence and transparency

Sources & review

Official repository ↗
Source record details
Source availability
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Sources checked
18 October 2026
Original website title
jacobmarks/reverse-image-search-plugin · Official homepage title · retained in its source language
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