edt
Multi-Label Anisotropic Euclidean Distance Transform 3D
Decision gist · record as of 2026-08-14
Yes. edt is actively maintained, production-stable, has no known vulnerabilities, and offers genuine performance advantages for multi-label and anisotropic distance transforms in scientific workflows. The LGPL-3.0-or-later license requires compliance review if used in proprietary software. Medium install friction is acceptable given prebuilt wheels for common platforms; source builds require a C++ compiler.AI-flagged interpretation of the facts on this page — verify before relying
Before you install
- Requires numpy; source installation requires a C++ compiler and development headers (e.g., python3-dev on Linux).
- Medium install friction due to compiled C++ components; prebuilt wheels available for Python 3.10–3.13 on macOS (x86_64 and ARM64), Linux (x86_64 and aarch64), and Windows; source installation requires a C++ compiler.
- Package is actively maintained with recent releases.
License · maintenance · safety
LGPL-3.0-or-later (copyleft) — Licensed under LGPL-3.0-or-later (copyleft). Derivative works and modifications must be distributed under compatible terms; static or dynamic linking in proprietary software may require license compliance review.
last release 2026-07-02 (43 days) · last repo commit 2026-07-23 · 267 stars
0 known vulnerabilities (OSV.dev, 2026-08-14) · 101,514 downloads/mo, #12,926 on PyPI
Alternatives
Verify before relying
import edt
import numpy as np
labels = np.ones(shape=(512, 512, 512), dtype=np.uint32, order='F')
dt = edt.edt(labels, anisotropy=(6, 6, 30), black_border=True, parallel=4)- Performance characteristics for typical connectomics workloads (e.g., actual speedup vs. scipy.ndimage.distance_transform_edt).
- Memory overhead of voxel_graph feature and practical use cases beyond the experimental warning.
What it is and what it does
edt is a compiled Python library that computes Euclidean distance transforms on labeled volumetric data. It handles 1D, 2D, and 3D arrays and supports anisotropic voxel spacing (e.g., different resolutions along each axis), which is common in microscopy and connectomics datasets. The package processes multiple labels simultaneously in a single pass, avoiding the need to compute transforms separately for each label.
The library is built on a C++ core with a Python wrapper and depends only on numpy. It offers both standard Euclidean distance and squared Euclidean distance variants, signed distance fields, and optional multi-threaded computation. Special optimizations exist for binary images. The package is designed for scientific and research workflows, particularly in connectomics and image analysis, where large labeled volumes require fast distance computations.
Use it for
- Compute distance transforms on densely labeled 3D connectomics volumes to support skeletonization algorithms like TEASAR.
- Correct for anisotropic voxel spacing in microscopy data (e.g., different X/Y vs. Z resolution) during distance field computation.
- Extract individual label components from a multi-label volume and process their distance transforms sequentially.
- Generate signed distance fields for geometric analysis of labeled structures in volumetric medical or biological imaging.
- Accelerate batch distance transform operations on binary images using specialized optimizations.
Worth the install?
AI-flagged interpretation of the facts on this page. Verify before relying on it.
Yes.
edt is actively maintained, production-stable, has no known vulnerabilities, and offers genuine performance advantages for multi-label and anisotropic distance transforms in scientific workflows. The LGPL-3.0-or-later license requires compliance review if used in proprietary software. Medium install friction is acceptable given prebuilt wheels for common platforms; source builds require a C++ compiler.
Install
edt on PyPI
Before you install
Medium install friction due to compiled C++ components; prebuilt wheels available for Python 3.10–3.13 on macOS (x86_64 and ARM64), Linux (x86_64 and aarch64), and Windows; source installation requires a C++ compiler. Package is actively maintained with recent releases.
Requires numpy; source installation requires a C++ compiler and development headers (e.g., python3-dev on Linux).
License in practice
Licensed under LGPL-3.0-or-later (copyleft). Derivative works and modifications must be distributed under compatible terms; static or dynamic linking in proprietary software may require license compliance review.
Quickstart
import edt
import numpy as np
labels = np.ones(shape=(512, 512, 512), dtype=np.uint32, order='F')
dt = edt.edt(labels, anisotropy=(6, 6, 30), black_border=True, parallel=4)Verify before relying
- Performance characteristics for typical connectomics workloads (e.g., actual speedup vs. scipy.ndimage.distance_transform_edt).
- Memory overhead of voxel_graph feature and practical use cases beyond the experimental warning.
Package facts
| License | LGPL-3.0-or-later copyleft |
| Python support | Supports the current Python release <4,>=3.8 |
| Install friction | Medium. Platform-specific wheel |
| Runtime dependencies | 1 packagenumpy |
| Maintenance | Actively maintained 43 days since the last release |
| Last repo commit | |
| First released | |
| Downloads | 101,514 / month, #12,926 on PyPI 30-day window, as of 2026-08-14 |
| Known vulnerabilities | None known OSV.dev, checked 2026-08-14 |
| Classifiers | Development Status :: 5 - Production/StableIntended Audience :: DevelopersIntended Audience :: Science/ResearchOperating System :: MacOSOperating System :: POSIXProgramming Language :: PythonProgramming Language :: Python :: 3Programming Language :: Python :: 3.10Programming Language :: Python :: 3.11Programming Language :: Python :: 3.12Programming Language :: Python :: 3.13Programming Language :: Python :: 3.14Programming Language :: Python :: 3.9Topic :: Scientific/EngineeringTopic :: Utilities |
Evidence: edt-3.1.2-cp310-cp310-macosx_10_9_x86_64.whl; edt-3.1.2-cp310-cp310-macosx_11_0_arm64.whl; edt-3.1.2-cp310-cp310-manylinux_2_26_aarch64.manylinux_2_28_aarch64.whl; edt-3.1.2-cp310-cp310-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl; edt-3.1.2-cp310-cp310-win32.whl; edt-3.1.2-cp310-cp310-win_amd64.whl; edt-3.1.2-cp311-cp311-macosx_10_9_x86_64.whl; edt-3.1.2-cp311-cp311-macosx_11_0_arm64.whl; edt-3.1.2-cp311-cp311-manylinux_2_26_aarch64.manylinux_2_28_aarch64.whl; edt-3.1.2-cp311-cp311-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl; edt-3.1.2-cp311-cp311-win32.whl; edt-3.1.2-cp311-cp311-win_amd64.whl; edt-3.1.2-cp312-cp312-macosx_10_13_x86_64.whl; edt-3.1.2-cp312-cp312-macosx_11_0_arm64.whl; edt-3.1.2-cp312-cp312-manylinux_2_26_aarch64.manylinux_2_28_aarch64.whl; edt-3.1.2-cp312-cp312-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl; edt-3.1.2-cp312-cp312-win32.whl; edt-3.1.2-cp312-cp312-win_amd64.whl; edt-3.1.2-cp313-cp313-macosx_10_13_x86_64.whl; edt-3.1.2-cp313-cp313-macosx_11_0_arm64.whl
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