Demo tutorial

End-to-end pipeline: preprocessing → habitat segmentation → feature extraction → machine learning → model comparison.

Prerequisites: Installation .

Prepare data

Note

D:\habit-cpu is an example path — use your portable or project root.

1. Download and extract to the project root (same level as python.exe or repo root):

   demo_data.rar (required)

   • Download demo_data.rar

   • Code: 9ws9

   config/ is already included in both the portable ZIP and source checkout.

   tests.zip (optional)

   • Download tests bundle

   • Code: vv2c

2. Verify habit --version .

Run (5 steps)

Demo includes preprocessed data — start at step 2 on first run.

cd /d D:\habit-cpu

habit preprocess --config config/preprocessing/config_preprocessing_demo.yaml
habit get-habitat --config config/habitat/config_habitat_two_step.yaml
habit extract --config config/feature_extraction/config_extract_features_demo.yaml
habit model --config config/machine_learning/config_machine_learning_radiomics.yaml --mode train
habit model --config config/machine_learning/config_machine_learning_clinical.yaml --mode train
habit compare --config config/model_comparison/config_model_comparison_demo.yaml

Outputs under demo_data/results/ . Your own data → How-to guides .