Tutorials

The notebooks below are available in the notebooks/ directory of the GitHub repository. Run them locally to learn how to use the Datamint Python API across different scenarios.

Getting Started

01_upload_data.ipynb: Upload images, DICOMs, and other resources to a Datamint project.
02_explore_data.ipynb: Query and explore resources already in a project.

Annotations

01_upload_annotations.ipynb: Import and manage image-level and frame-level classification annotations.
02_geometry_annotations.ipynb: Upload bounding boxes, lines, and other geometry annotations.

Datasets

01_project_scoped_splits.ipynb: Assign project-scoped train/val/test splits, inspect split records, and replay historical snapshots.
02_patient_wise_splits.ipynb: Split datasets by patient to avoid data leakage between train and test sets.
03_build_dataset.ipynb: Build and configure a PyTorch dataset from a Datamint project.
04_volume_dataset.ipynb: Work with 3D volume datasets (NIfTI, DICOM series).

Experiment Tracking

01_mlflow_manual_logging.ipynb: Log models and experiments manually to MLflow via Datamint.

Deployment

01_deploy_registered_model.ipynb: Deploy a model registered in MLflow as a managed Datamint endpoint.
02_deploy_external_model.ipynb: Adapt and deploy an externally-trained model in Datamint.
03_validate_model.ipynb: Validate a model before promoting it to production.
04_predict_images_volumes_and_videos.ipynb: Run a 2D model on images, 3D volumes, and video frames using automatic prediction bridges.

End-to-End Examples

Complete workflows from data upload to deployment.

Slice-based (2D)

01_fracatlas_classification.ipynb: End-to-end classification pipeline on the FracAtlas dataset.
02_busi_segmentation.ipynb: Train a 2D segmentation model on the BUSI dataset with UNetPPTrainer, including custom model integration.
03_bccd_detection.ipynb: Object detection pipeline on the BCCD blood cell dataset.

Full 3D

01_synapse_unetrpp.ipynb: Volumetric segmentation on the Synapse dataset using UNETR++.
02_synapse_nnunet.ipynb: Volumetric segmentation on the Synapse dataset using nnUNet.