delira - Deep Learning In RAdiology

Getting Started

• Getting started
  • Backends
  • Installation

Tutorials:

• Delira Introduction
  • Loading Data
  • Models
  • Abstract Networks for specific Backends
  • Training
  • Logging
  • More Examples
• Classification with Delira - A very short introduction
  • Logging and Visualization
  • Data Preparation
  • Training
  • See Also
• Generative Adversarial Nets with Delira - A very short introduction
  • HyperParameters
  • Logging and Visualization
  • Data Preparation
  • Training
  • See Also
• Segmentation in 2D using U-Nets with Delira - A very short introduction
  • Logging and Visualization
  • Data Praparation
  • Training
  • See Also
• Segmentation in 3D using U-Nets with Delira - A very short introduction
  • Logging and Visualization
  • Data Praparation
  • Training
  • See Also

API Documentation:

• API Documentation
  • Delira
    • Data Loading
      • Arbitrary Data
        • Dataset
        • Dataloader
        • Datamanager
        • Utils
      • Nii
      • Sampler
    • IO
    • Logging
      • MultiStreamHandler
      • TrixiHandler
    • Models
      • Classification
      • Generative Adversarial Networks
      • Segmentation
    • Training
      • Parameters
      • Network Trainer
      • Predictor
      • Experiment
      • Callbacks
      • Losses
      • Metrics
      • convert_batch_to_numpy_identity
      • float_to_pytorch_tensor
      • create_optims_default_pytorch
      • create_optims_gan_pytorch
      • convert_torch_tensor_to_npy
      • create_optims_default_tf
      • initialize_uninitialized
      • convert_tf_tensor_to_npy
    • Utilities
    • Backend Resolution
    • Class Hierarchy Diagrams
• GitHub

Indices and tables

• Index

• Module Index

• Search Page