Examples

KonfAI ships two low-level, YAML-driven examples under examples/. They are the best starting point when you want to understand the framework before building a reusable KonfAI App.

Both examples are backed by public demo data on Hugging Face:

  • VBoussot/konfai-demo/Synthesis

  • VBoussot/konfai-demo/Segmentation

Each example also includes a notebook intended for a fresh environment, including Google Colab.

Choosing an example

Start with Segmentation when you want the smallest conservative baseline:

  • one input group (CT)

  • one label-map target (SEG)

  • built-in UNet

  • training with CrossEntropyLoss

  • final evaluation with Dice

Start with Synthesis when you want to understand more of KonfAI’s configuration model:

  • custom local Python modules loaded through classpath

  • paired image-to-image training

  • masked evaluation

  • shared prediction and evaluation configs

  • a GAN variant with nested patching scopes

A good adoption pattern is:

  1. get Segmentation to run once

  2. adapt that layout to your own data

  3. move to Synthesis only when you need custom modules or more advanced workflow structure

Working from the repository

All example commands in this documentation assume you are running from the example directory itself, for example:

cd examples/Segmentation

or:

cd examples/Synthesis

That matters because the shipped YAML files refer to local modules and dataset paths relative to the current working directory.

See also