nnunetv2

library2.8.0pypypiunverified

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.

ai-ml

pip install nnunetv2

github ↗package ↗

INSTALL

IMPORT

SIG · NNUNETV2

nnunetv2

ai-mlpythonv2.8.0

Install

97.4s avg

Import

—

Disk

5769MB

Pass rate

3/ 10

Env Coverage3 / 10

glibc

3.9–3.13

musl

3.9–3.13

Install & Compatibility

Where this runs

tested against v2.8.0 · pip install

no network on importno background threads

Install × environment matrix

Each cell = how many times install + import succeeded across repeated harness runs. Partial = flaky.
glibc = Debian/Ubuntu slim · musl = Alpine Linux

musl

glibc

py 3.10

✕ build_error

1/2 runs

py 3.11

✕ build_error

✓ 104.2s

py 3.12

✕ build_error

✓ 96.3s

py 3.13

✕ build_error

✓ 91.6s

py 3.9

✕ build_error

5769MB installed

● package 5769MB

Code

Verified usage

Verified import paths — ran on the pinned version, not inferred.

nnUNetPlanner

✓ from nnunetv2.experiment_planning.plan_and_configurator import nnUNetPlanner

✗ from nnunetv2.experiment_planning.plan_and_configurator import nnUNetPlanner

Prepares environment variables, converts a Medical Segmentation Decathlon dataset, plans preprocessing, and runs a 2D training fold.

import os os.environ['nnUNet_raw'] = '/path/to/nnUNet_raw' os.environ['nnUNet_preprocessed'] = '/path/to/nnUNet_preprocessed' os.environ['nnUNet_results'] = '/path/to/nnUNet_results' # Convert dataset (Task002_Heart example) from nnunetv2.dataset_conversion import convert_MSD_dataset convert_MSD_dataset.convert_msd_dataset('/path/to/Task02_Heart') # Plan & preprocess from nnunetv2.experiment_planning.plan_and_configurator import nnUNetPlanner planner = nnUNetPlanner(dataset_name_or_id='002', plans_identifier='nnUNetPlans') planner.plan_and_preprocess() # Train 2D U-Net from nnunetv2.run.run_training import run_training run_training('002', '2d', 0, plans_identifier='nnUNetPlans')

nnUNet --version

Debug

Known issues

breakingFrom v2.0, the environment variables nnUNet_raw_data_base and nnUNet_preprocessed are replaced by nnUNet_raw, nnUNet_preprocessed, and nnUNet_results. Old scripts will break.

fix

Set new env vars: nnUNet_raw, nnUNet_preprocessed, nnUNet_results. Update scripts that used the old names.

affects: >=2.0

breakingThe dataset JSON format changed. The 'labels' field now uses a dictionary for old label names to new ones, and the 'modality' field must be a dict.

fix

Update dataset.json to follow the new schema. See https://github.com/MIC-DKFZ/nnUNet/blob/master/documentation/dataset_format.md

affects: >=2.2

deprecatedThe use of 'nnUNet_compile' flag is deprecated. Use PyTorch's torch.compile directly.

fix

Replace nnUNet_compile=True with torch.compile(model) in your training script.

affects: >=2.7

gotchaTraining on Windows may fail due to the default CUDA memory allocation policy or path length limits. Linux is the only officially supported OS.

fix

Use Linux (Ubuntu) or WSL2. Ensure short paths (e.g., C:\nnunet).

affects: all

gotchannU-Net v2 no longer supports multi-GPU training via nnUNet_train. Use PyTorch DDP manually.

fix

Run training with torchrun: torchrun --nnodes=1 --nproc_per_node=4 --master_port=xxxx nnunetv2/run/run_training.py ...

affects: >=2.0

Upgrade

Version history

2.8.0latest on PyPI · released Jun 7, 2026

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Dependencies

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Resources

githubhttps://github.com/MIC-DKFZ/nnUNet ↗

packagehttps://pypi.org/project/nnunetv2/ ↗