FreePublished on GitHub

antspy

Use ANTsPy/antspyx for medical image IO, ANTsImage metadata, image operations, registration, segmentation, visualization, and learning helper workflows.

The English summary is being prepared. Showing the original description.

VectorSpaceLab/AREX-Skill

See how to install

Files included (40)

SKILL.md4.6 KB
references/api-index.md2.7 KB
references/package-overview.md3.1 KB
references/repo-provenance.md1.4 KB
references/repo-routing-metadata.json488 B
references/troubleshooting.md4.4 KB
scripts/antspy_environment_check.py2.8 KB
scripts/run_antspy_smoke_suite.py2.8 KB
sub-skills/image-core/references/api-reference.md12.7 KB
sub-skills/image-core/references/troubleshooting.md9.6 KB
sub-skills/image-core/references/workflows.md7.7 KB
sub-skills/image-core/scripts/antspy_image_smoke.py4.3 KB
sub-skills/image-core/SKILL.md4.4 KB
sub-skills/image-ops-math/references/api-reference.md11.6 KB
sub-skills/image-ops-math/references/imath-reference.md8.0 KB
sub-skills/image-ops-math/references/troubleshooting.md8.6 KB
sub-skills/image-ops-math/references/workflows.md10.1 KB
sub-skills/image-ops-math/scripts/antspy_ops_smoke.py4.6 KB
sub-skills/image-ops-math/SKILL.md3.0 KB
sub-skills/learning-deeplearn/references/api-reference.md10.4 KB
sub-skills/learning-deeplearn/references/troubleshooting.md8.0 KB
sub-skills/learning-deeplearn/references/workflows.md9.7 KB
sub-skills/learning-deeplearn/scripts/antspy_deeplearn_smoke.py6.2 KB
sub-skills/learning-deeplearn/SKILL.md4.8 KB
sub-skills/registration-transforms/references/api-reference.md12.4 KB
sub-skills/registration-transforms/references/transform-types.md8.3 KB
sub-skills/registration-transforms/references/troubleshooting.md7.5 KB
sub-skills/registration-transforms/references/workflows.md13.5 KB
sub-skills/registration-transforms/scripts/antspy_registration_smoke.py4.6 KB
sub-skills/registration-transforms/SKILL.md4.7 KB
sub-skills/segmentation-labels/references/api-reference.md8.6 KB
sub-skills/segmentation-labels/references/troubleshooting.md7.2 KB
sub-skills/segmentation-labels/references/workflows.md9.7 KB
sub-skills/segmentation-labels/scripts/antspy_segmentation_smoke.py4.8 KB
sub-skills/segmentation-labels/SKILL.md3.8 KB
sub-skills/visualization-interop/references/api-reference.md12.4 KB
sub-skills/visualization-interop/references/troubleshooting.md10.4 KB
sub-skills/visualization-interop/references/workflows.md10.7 KB
sub-skills/visualization-interop/scripts/antspy_plotting_smoke.py6.8 KB
sub-skills/visualization-interop/SKILL.md4.2 KB

SKILL.md (original)

Review the instructions the agent will receive before you install.

ANTsPy Repo Skill

Use this repo skill when a task involves the Python package distributed as antspyx and imported as ants: medical image IO, ANTsImage objects, preprocessing, registration, transforms, segmentation, labels, plotting, interoperability, or ANTsPy learning/deeplearn helper utilities.

Start Here

Install the package with pip install antspyx or conda install conda-forge::antspyx.
Verify the public import with python -c "import ants; print(ants.__name__)".
Run scripts/antspy_environment_check.py for a tiny import/API smoke check.
Read references/package-overview.md for package scope, compiled-backend caveats, and workflow boundaries.
Read references/troubleshooting.md when installation, import, compiled libraries, physical-space metadata, optional dependencies, or expensive algorithms fail.
Check references/repo-provenance.md before deciding whether this skill is stale for a newer ANTsPy checkout.

Route by Task

User task	Read
Create, read, write, clone, index, compare, or validate `ants.ANTsImage` objects and physical metadata	image-core
Smooth, denoise, mask, crop, pad, slice, resample, threshold, run `iMath`, compute image metrics, or use morphology	image-ops-math
Register images, apply transforms to images or points, inspect transform files, build templates, run motion correction, or compute Jacobians	registration-transforms
Run Atropos, k-means, Otsu, priors, joint label fusion, label stats, overlap, geometry, label matrices, centroids, or point images	segmentation-labels
Save plots headlessly, build overlays/grids/movies, handle RGB/vector channels, convert image lists/matrices, or interoperate with nibabel/SimpleITK	visualization-interop
Use sparse/eigen learning helpers, patch extraction/reconstruction, one-hot labels, random augmentation, simulated bias fields, or learning-oriented crop/pad helpers	learning-deeplearn

Cross-Cutting Rules

Import with import ants; do not import antspyx as a module.
ANTsPy wraps compiled ANTs/ITK code. A successful pip install is not enough if importing ants fails; run the environment check script before debugging workflow code.
ANTsImage values and physical metadata are both important. Validate shape, dimension, origin, spacing, and direction before mixing images, masks, labels, transforms, overlays, or matrices.
Use label-safe interpolation such as nearestNeighbor or genericLabel for labels and masks. Use linear-style interpolation for intensity images unless the workflow requires otherwise.
Prefer small synthetic images for smoke checks and troubleshooting. Full nonlinear registration, joint label fusion, high-resolution 3-D operations, and template building can be expensive.
Keep ANTsPyNet, neural-network model training, and application-specific medical pipelines outside this skill unless the task only uses ANTsPy helper utilities.

Shared References and Scripts

Package overview: package identity, public workflow map, data model, optional dependencies, and version caveats.
API index: quick map from common ants.* functions to the owning sub-skill and detailed reference.
Troubleshooting: install/import failures, wheel/source-build problems, shadowed imports, physical-space errors, optional dependencies, and expensive workflow triage.
Repo provenance: source commit, dirty-state baseline, package versions, and evidence paths used for this generated skill.
Routing metadata: structured scenario metadata consumed by the managed repo-skills-router during import.
Environment check: tiny import/API smoke check for antspyx.
Smoke suite: runs the bundled sub-skill smoke scripts with the current Python interpreter.

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Install

Install with a command

npx skills add https://github.com/VectorSpaceLab/AREX-Skill --skill antspy

Paste it into your terminal and run it (requires Node.js). You can choose which agents to install it for, such as Claude Code or Codex.

Ask your agent

Please install the following Agent Skill.
https://github.com/VectorSpaceLab/AREX-Skill/tree/main/skills/repositories/repo-skills/antspy

First review SKILL.md and the bundled files and confirm there is nothing suspicious (such as sending data externally or reading credentials). Then place it in ~/.claude/skills/antspy/ for Claude Code, or ~/.agents/skills/antspy/ for Codex.

Send this text to Claude Code or Codex as is. It checks the contents before installing.

View source on GitHub

Repository: VectorSpaceLab/AREX-Skill
Stars: 338
Forks: 26
Category: Media
License: Apache-2.0
Original language: English
Last updated: Sep 3, 2026

A skill is a set of instructions and scripts for an agent. cccskills does not guarantee that skills are safe. Review the contents before you install.