pyALDIC-3D

Stereo / 3D Digital Image Correlation desktop application — full-field 3D shape, displacement, and surface strain from a synchronized two-camera setup.

What it is

pyALDIC-3D is an independent, self-contained application for stereo (two-camera) Digital Image Correlation. Point it at two synchronized image sequences and a stereo calibration, and it reconstructs the specimen surface in 3D and tracks its displacement and Green–Lagrange surface strain through the sequence — all in millimetre-native world coordinates (the left camera is the world origin).

It is built on top of the pyALDIC-2D platform (arXiv:2607.22755, preprint under review), which it consumes as a pinned, read-only library (al-dic==0.7.*) for the underlying 2D correlation engine (Augmented-Lagrangian DIC: local IC-GN subproblems coupled to a global FEM regularizer). Everything above the 2D solver — stereo calibration, correspondence strategies, triangulation, 3D surface strain, the 3D visualization layer, the project format, and the workflow — is pyALDIC-3D's own.

The algorithm follows the MATLAB 3D-Stereo-ALDIC reference (Tong et al., Experimental Mechanics, 2025) as a mathematical model, ported into idiomatic, tested Python — not a literal translation.

Scope (honest): v1 supports a two-camera stereo rig. The data model is N-camera-ready, but N-camera (>2) support is planned for post-v1.

Key features

Install

pyALDIC-3D targets Python ≥ 3.10. The al-dic==0.7.* 2D engine resolves automatically from PyPI.

From PyPI — available from v1.0.0

Releases from v1.0.0 onward are published on PyPI as al-dic-3d (see docs/RELEASING.md for the release process):

# 1. Create an environment (conda shown; a venv works too)
conda create -n pyaldic3d python=3.12
conda activate pyaldic3d

# 2. Install (GUI and 3D view included)
pip install al-dic-3d

From source (development)

git clone https://github.com/zachtong/pyALDIC-3D.git
cd pyALDIC-3D
pip install -e ".[dev]"

A bare pip install al-dic-3d is full-featured: it ships the desktop GUI (PySide6) and the interactive 3D view (pyvista/VTK) alongside the headless compute stack (numpy, scipy, OpenCV, al-dic). GUI and 3D imports are lazy, so al-dic-3d run / calibrate still work on headless servers where Qt or OpenGL cannot initialize. The historical [gui] / [viz3d] extras remain as no-op compatibility aliases; [dev] adds pytest, ruff, pre-commit, and matplotlib for the test suite and report tooling.

pip install -e ../pyALDIC     # 2D engine, editable (reports 0.7.x)
pip install -e ".[dev]"
pre-commit install            # optional hooks

Quickstart

The repo ships a tiny sample dataset under examples/Images_Stereo_Sample3_images/ — three synchronized left/right stereo pairs of a speckled D-specimen (Stereo-DIC Challenge 1.0 "Sample 3") plus a DICe-format calibration. It is small (3 frames), but enough to run the full pipeline end to end.

GUI

al-dic-3d gui

Then follow examples/quickstart/README.md: load the L/ and R/ folders as the left/right cameras, import cal.xml as the calibration, draw an ROI, click Run 3D Analysis, and inspect the displacement/strain fields and the 3D view.

CLI (headless)

A ready-to-run config lives at examples/quickstart/config.toml:

al-dic-3d run examples/quickstart/config.toml -o examples/quickstart/out

This reconstructs the surface and computes surface strain for all three frames and writes, under -o:

• quickstart.npz / quickstart.mat — the unified result archive: points3D (n_frames, n_pts, 3), per-frame displacement stacks U / V / W / mag, strain stacks exx / eyy / exy / e1 / e2 / max_shear / von_mises, plus the raw correspondence (xL / xR / quality / reproj_error).
• quickstart_parameters_<timestamp>.json — the full run configuration (always written).

Verified run: 3 frames, ~1,300 nodes, median per-frame validity 100 %, completing in seconds on a laptop. The reconstructed surface sits ~377–390 mm from the left camera (world origin), consistent with the calibration.

CLI reference

al-dic-3d (equivalently python -m al_dic_3d) has three subcommands:

run — headless pipeline

al-dic-3d run CONFIG [-o DIR] [-q] [--formats LIST]

Config sections: [calibration] (file, format), [sequence] (left, right, optional masks), [roi] (xmin/xmax/ymin/ymax, or an arbitrary-shape mask image), [matching] (strategy, reference mode, subset/step, search ranges, initial guess, …), [strain], [quality], [output], [advanced]. See the shipped config.toml for a minimal example.

gui — desktop application

al-dic-3d gui [SESSION]

Launches the workflow GUI (included in every install). An optional .aldic3d project path opens straight into that session.

calibrate — built-in stereo calibration

al-dic-3d calibrate --left GLOB --right GLOB --board {chessboard,charuco,circles,coded} \
                    --cols COLS --rows ROWS [--square MM | --spacing MM] [-o OUT.yaml] ...

Detects the board in synchronized L/R image sets, solves per-camera intrinsics + stereo extrinsics with QC (worst-pair rejection, epipolar validation), and writes an OpenCV YAML that run consumes as [calibration] file=... format=opencv_yaml. Options include --marker/--dict (ChArUco), --spacing/--dot/--asymmetric (circle/coded boards), --joint, --tangential, --fix-k3, --release-object, --bundle, and --verify-left/--verify-right for independent known-distance verification. Run al-dic-3d calibrate --help for the full list.

Calibration

Calibration is the accuracy-critical step in stereo-DIC. pyALDIC-3D gives you three paths, all converging on one internal stereo rig:

1. Built-in calibration (recommended) — OpenCV-based, from board image pairs, with QC the MATLAB reference does not have (per-image error bars, threshold-based rejection + re-solve, coverage/pose diagnostics). Supports chessboard, ChArUco, circle grids, and a custom coded circular target (three concentric locator rings).
2. Import an existing calibration from one of 6 formats — MATLAB/OpenCV (matlabcv), MatchID (matchid), MMC (mmc), DICe (dice), OpenCorr (opencorr), or OpenCV-YAML (opencv_yaml).
3. Manual entry of intrinsics/extrinsics as a fallback.

Correspondence is computed on raw (unrectified) images; distortion is removed on point coordinates only, immediately before triangulation, so the speckle is never resampled.

Positioning

pyALDIC-3D is the Python successor to the MATLAB 3D-Stereo-ALDIC code — the same AL-DIC stereo-DIC method, re-implemented as a tested, GUI-driven, self-contained application with a built-in calibration front end and a modern 3D visualization/export layer.

Relative to other open stereo-DIC tools: MATLAB-based MultiDIC offers N-camera (>2) support that pyALDIC-3D does not yet have (N-camera is planned post-v1); pyALDIC-3D's differentiators are the Augmented-Lagrangian global–local solver, adaptive quadtree refinement, built-in QC-instrumented calibration, and a Python/Qt stack with no MATLAB license requirement. No head-to-head accuracy benchmark is claimed here — see the validation reports in the architecture docs for measured results.

Documentation

• User guide — docs/user-guide/ (start at index.md): overview, installation & launching, and task-oriented walkthroughs.
• Architecture & decision baseline — docs/architecture/ (start at 00_INDEX.md): technical baseline, correspondence- strategy study, decision log, and the full version changelog.
• Reference notes — docs/COORDINATES.md, docs/strain3d_math.md, docs/DEPENDS_ON_2D.md.

Citation

pyALDIC-3D has its own scholarly identity, independent of the 2D project. Citation metadata ships in CITATION.cff — GitHub renders a "Cite this repository" button from it. A dedicated Zenodo concept DOI is pending the first public release (Zenodo mints it automatically when the first GitHub Release is published; it will then be added here and to CITATION.cff), and a standalone SoftwareX article ("Part 2") is forthcoming.

To cite the software itself today:

@software{tong2026pyaldic3dsoftware,
  author  = {Tong, Zixiang},
  title   = {pyALDIC-3D: stereo / 3D Digital Image Correlation built on the
             pyALDIC platform},
  year    = {2026},
  url     = {https://github.com/zachtong/pyALDIC-3D},
  version = {1.0.0},
  note    = {Zenodo DOI pending first release}
}

Please also cite the underlying method, the MATLAB reference it ports, and the 2D software it is built on:

@article{tong2025stereoaldic,
  author  = {Tong, Zixiang and Yang, Jin},
  title   = {3D Stereo Adaptive Mesh Augmented Lagrangian Digital Image Correlation},
  journal = {Experimental Mechanics},
  year    = {2025},
  doi     = {10.1007/s11340-025-01225-7}
}

@article{yang2019aldic,
  author  = {Yang, Jin and Bhattacharya, Kaushik},
  title   = {Augmented Lagrangian Digital Image Correlation},
  journal = {Experimental Mechanics},
  volume  = {59},
  pages   = {187--205},
  year    = {2019},
  doi     = {10.1007/s11340-018-00457-0}
}

@article{tong2026pyaldic,
  author  = {Tong, Zixiang and Yang, Jin},
  title   = {pyALDIC: A Python Implementation of Augmented Lagrangian Digital
             Image Correlation with a GUI, Adaptive Meshing, and Mask-Aware
             Subset Splitting},
  journal = {arXiv preprint arXiv:2607.22755},
  year    = {2026},
  doi     = {10.48550/arXiv.2607.22755},
  url     = {https://arxiv.org/abs/2607.22755}
}

The last entry describes the 2D software this application builds on — its architecture, adaptive quadtree meshing and mask-aware subset splitting — and is a preprint under review, not peer-reviewed yet.

A pyALDIC-3D software DOI (Zenodo) and the SoftwareX "Part 2" citation will be added here when available.

Releases & versioning

Package versions follow the single source of truth __version__ in src/al_dic_3d/__init__.py (git tags vX.Y.Z, published to PyPI by CI). The "v1.x" numbers in the docs/architecture/00_INDEX.md changelog are internal documentation milestones, not package versions. The full release runbook (PyPI Trusted Publishing, Zenodo DOI) lives in docs/RELEASING.md.

License

BSD 3-Clause. See LICENSE. The al-dic 2D engine dependency is likewise BSD-3-Clause-licensed.

Acknowledgements

pyALDIC-3D is built on the pyALDIC 2D platform (the al-dic package, described in arXiv:2607.22755 — preprint under review) and follows the MATLAB 3D-Stereo-ALDIC reference. Developed in Dr. Jin Yang's group at The University of Texas at Austin.