{"library":"nnunetv2","title":"nnU-Net v2","description":"nnU-Net is a self-adapting framework for biomedical image segmentation that automatically configures itself for new datasets. Version 2.7.0 reworks the dataset conversion and introduces new training modes. Active development, monthly releases.","language":"python","status":"active","last_verified":"Fri May 01","install":{"commands":["pip install nnunetv2","pip install nnunetv2[all]"],"cli":{"name":"nnUNet","version":""}},"imports":["from nnunetv2.experiment_planning.plan_and_configurator import nnUNetPlanner","from nnunetv2.training.nnUNetTrainer import nnUNetTrainer","from nnunetv2.inference.predict import nnUNetPredictor"],"auth":{"required":false,"env_vars":[]},"quickstart":{"code":"import os\nos.environ['nnUNet_raw'] = '/path/to/nnUNet_raw'\nos.environ['nnUNet_preprocessed'] = '/path/to/nnUNet_preprocessed'\nos.environ['nnUNet_results'] = '/path/to/nnUNet_results'\n# Convert dataset (Task002_Heart example)\nfrom nnunetv2.dataset_conversion import convert_MSD_dataset\nconvert_MSD_dataset.convert_msd_dataset('/path/to/Task02_Heart')\n# Plan & preprocess\nfrom nnunetv2.experiment_planning.plan_and_configurator import nnUNetPlanner\nplanner = nnUNetPlanner(dataset_name_or_id='002', plans_identifier='nnUNetPlans')\nplanner.plan_and_preprocess()\n# Train 2D U-Net\nfrom nnunetv2.run.run_training import run_training\nrun_training('002', '2d', 0, plans_identifier='nnUNetPlans')\n","lang":"python","description":"Prepares environment variables, converts a Medical Segmentation Decathlon dataset, plans preprocessing, and runs a 2D training fold.","tag":null,"tag_description":null,"last_tested":null,"results":[]},"compatibility":null}