UDFs in Pixeltable
Pixeltable comes with a library of built-in functions and integrations, but sooner or later, you'll want to introduce some customized logic into your workflow.
Expressions are the basic building blocks of Pixeltable.
Tutorials · Notebook · Updated
Colab runs it in your browser. If it calls a model provider, it asks for that provider's API key in a cell.
pip install pixeltable datasets torch transformers
huggingface.vit_for_image_classification()huggingface.clip()pxt.create_table()add_computed_column()from pixeltable.functions.huggingface import vit_for_image_classificationt.add_computed_column(classification=vit_for_image_classification(t.image, model_id='farleyknight-org-username/vit-base-mnist'))
One cell of the notebook, copied as it is. Open it in Colab for the rest.
Pixeltable comes with a library of built-in functions and integrations, but sooner or later, you'll want to introduce some customized logic into your workflow.
Create an embedding index, query it with similarity search and keep it current as data changes. Covers several indexes on one column, custom embedding UDFs and precomputed embeddings.
In Pixeltable, all media data (videos, images, audio) resides in external files, and Pixeltable stores references to those.
Welcome to Pixeltable! In this tutorial, we'll survey how to create tables, populate them with data, and enhance them with built-in and user-defined transformations and AI operations.