AI Quickstarts

Face similarity search

Identify the celebrities who look most similar to you using Supabase Vecs.

This guide will walk you through a "Face Similarity Search" example using Colab and Supabase Vecs. You will be able to identify the celebrities who look most similar to you (or any other person). You will:

  1. Launch a Postgres database that uses pgvector to store embeddings
  2. Launch a notebook that connects to your database
  3. Load the "ashraq/tmdb-people-image" celebrity dataset
  4. Use the face_recognition model to create an embedding for every celebrity photo.
  5. Search for similar faces inside the dataset.

Project setup#

Let's create a new Postgres database. This is as simple as starting a new Project in Supabase:

  1. Create a new project in the Supabase dashboard.
  2. Enter your project details. Remember to store your password somewhere safe.

Your database will be available in less than a minute.

Finding your credentials:

You can find your project credentials inside the project settings, including:

Launching a notebook#

Launch our semantic_text_deduplication notebook in Colab:

At the top of the notebook, you'll see a button Copy to Drive. Click this button to copy the notebook to your Google Drive.

Connecting to your database#

Inside the Notebook, find the cell which specifies the DB_CONNECTION. It will contain some code like this:

import vecs
DB_CONNECTION = "postgresql://<user>:<password>@<host>:<port>/<db_name>"
# create vector store client
vx = vecs.create_client(DB_CONNECTION)

Replace the DB_CONNECTION with your own connection string for your database, which you set up in first step of this guide.

Stepping through the notebook#

Now all that's left is to step through the notebook. You can do this by clicking the "execute" button (ctrl+enter) at the top left of each code cell. The notebook guides you through the process of creating a collection, adding data to it, and querying it.

You can view the inserted items in the Table Editor, by selecting the vecs schema from the schema dropdown.

Colab documents

Next steps#

You can now start building your own applications with Vecs. Check our examples for ideas.