KonfAI KonfAI KonfAI
/

Getting started

  • Installation
  • Quickstart

Tutorials

  • Examples
    • KonfAI on real data
    • Segmentation Example
    • Registration example
    • Synthesis Example

Task-oriented guides

  • How-to guides
    • Adopt KonfAI from PyTorch, MONAI, or nnU-Net
    • Processing large images
    • Using custom models, transforms, augmentations, and losses
    • Docker

Core concepts

  • Core concepts
    • Configuration model
    • Datasets and groups
    • Patch streaming
    • Model graph and output naming
    • Declarative YAML model graphs
    • Execution flow
  • Configuration reference
    • Training configuration
    • Prediction configuration
    • Evaluation configuration

Apps and automation

  • Using KonfAI Apps
  • Agent workflows (MCP server)
  • Ecosystem

Reference

  • Reference
    • Built-in component catalogue
      • Models
      • Losses & metrics
      • Transforms
      • Augmentations
      • Schedulers
      • Storage backends & formats
    • CLI reference
    • Environment variables
    • App server HTTP API
    • Python API (apps)
    • API reference
      • Workflows API
      • Configuration API
      • Data API
      • Models API
      • Apps API
      • Extension points
      • Full module reference
        • konfai package

Project

  • Troubleshooting
  • Development and contributing
  1. KonfAI /
  2. Overview: module code

All modules for which code is available

  • konfai
    • konfai.data.augmentation
    • konfai.data.data_manager
    • konfai.data.patching
    • konfai.data.transform
    • konfai.evaluator
    • konfai.main
    • konfai.metric.measure
    • konfai.metric.schedulers
    • konfai.network.blocks
    • konfai.network.network
    • konfai.predictor
    • konfai.trainer
    • konfai.utils.ITK
    • konfai.utils.config
    • konfai.utils.dataset
    • konfai.utils.utils
  • konfai_apps.app

2026, Valentin Boussot

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