Welcome to Pixeltable! In this tutorial, we will survey how to create tables, populate them with data, and enhance them with built-in and user-defined transformations and AI operations.
This guide will get you from zero to a working AI application in under 5 minutes. Learn more by looking at this tutorial on Github.
Let’s build an image analysis application that combines object detection and OpenAI Vision.
Please refer to our installation section here.
Create Table Structure
This creates a persistent and versioned table that holds data.
Add Object Detection
Computed columns are populated whenever new data is added to their input columns.
Add OpenAI Vision Analysis
Pixeltable handles parallelization, rate limiting, and incremental processing automatically.
Use Your Application
The query engine uses lazy evaluation, only computing what’s needed.
What happened behind the scenes?
Pixeltable automatically:
All data and computed results are automatically stored and versioned. Your app state persists between sessions.
Define transformations once, they run automatically on new data. Perfect for AI orchestration.
Handle images, video, audio, and text seamlessly in one unified interface.
Built-in support for popular AI services like OpenAI, YOLOX, Hugging Face, Label Studio, Replicate, Anthropic…
Extend Pixeltable with your own functions using the @pxt.udf
decorator: