cheshm 2.3.0

Pupil, glint, and limbus detection on grayscale eye images, plus iris-texture rigid alignment of two eye images.

cheshm

Cheshm is a cross-platform (Linux, macOS, Windows) C++ library with Python bindings. It packages pupil, glint, and limbus detectors for grayscale eye images, plus rigid alignment of two eye images (glint, pupil, or iris-texture based) and helpers for saving the resulting visualizations to PNG.

To annotate eye images with cheshm's detectors, see EyE Annotation Tool.

Install

uv add cheshm

or with pip:

pip install cheshm

Detectors

Kind	Detector	Paper	Licence
pupil	Simple	—	MIT
pupil	Starburst	Li, Winfield, Parkhurst 2005	GPL
pupil	Swirski2D	Świrski, Bulling, Dodgson 2012	MIT
pupil	ExCuSe	Fuhl et al. 2015	non-commercial
pupil	ElSe	Fuhl et al. 2016	non-commercial
pupil	PuRe	Santini, Fuhl, Kasneci 2018	non-commercial
pupil	PuReST	Santini, Fuhl, Kasneci 2018	non-commercial
pupil	PupilLabs2D	Kassner, Patera, Bulling 2014	LGPL-3.0-or-later
glint	Simple	—	MIT
limbus	Daugman integro-differential	Daugman 1993	MIT
limbus	Daugman active contour	Daugman 2007	MIT
limbus	Pupil-guided active contour	Daugman 2007 variant	MIT

The top-level LICENSE is MIT and covers the framework code; each detector ships its own LICENSE file with the detector's terms. Installing the project from PyPI installs all detectors, but only the ones you import are loaded into your process — so the licence that governs your use is the licence of the detectors you imported:

from cheshm.pupil_detectors.Simple import detect_pupil       # MIT
from cheshm.pupil_detectors.Starburst import detect_pupil    # GPL
from cheshm.pupil_detectors.ExCuSe import detect_pupil       # non-commercial
from cheshm.pupil_detectors.ElSe import detect_pupil         # non-commercial
from cheshm.pupil_detectors.PuRe import detect_pupil         # non-commercial
from cheshm.pupil_detectors.PuReST import PuReST             # non-commercial (stateful tracker)
from cheshm.pupil_detectors.PupilLabs2D import detect_pupil  # LGPL-3.0
from cheshm.glint_detectors.Simple import detect_glints      # MIT
from cheshm.limbus_detectors.daugman.integro_differential import detect_limbus  # MIT
from cheshm.limbus_detectors.daugman.active_contour import detect_limbus        # MIT
from cheshm.limbus_detectors.daugman.pupil_guided import detect_limbus          # MIT

Single-eye contract

Every public function operates on one eye at a time — a single grayscale image. Callers with two eyes call cheshm twice and combine the results.

Alignment

cheshm.align.align_eye_images(ref_img, tgt_img, ref_det, tgt_det, *, step1, step2) registers tgt_img onto ref_img with up to a two-step rigid transform. Either step can be enabled independently:

• Step 1 (translation) anchors on glint centroids (step1="glint"), pupil centres (step1="pupil"), or is skipped (step1=None).
• Step 2 (iris-texture refinement, optional) refines (dx, dy, theta) by minimising mean absolute intensity difference inside an iris-barrel mask built from the limbus + pupil geometry.

Set step1="glint", step2=False for pure glint alignment, step1="pupil", step2=False for pure pupil-centre alignment, step1=None, step2=True for iris-only, or any combination.

Visualization

cheshm.viz writes PNGs that show detector and alignment outputs:

• save_detection_overlay(out_path, img, detections, *, style, label) — draws pupil, glint, and limbus overlays on img. style is a dict keyed by element (pupil_contour, pupil_ellipse, pupil_center, pupil_mask, glint_contour, glint_ellipse, glint_center, limbus_curve, limbus_center) where each value is {show, color, thickness, alpha}.
• save_diff_heatmap(out_path, ref, aligned) — colour-mapped |ref − aligned|.
• save_alignment_overlay(out_path, ref, aligned) — blended reference + aligned image.
• save_alignment_comparison(out_path, ref, target, aligned) — 4-panel: ref | aligned | diff-before | diff-after.

GUI

cheshm-gui opens a Dear PyGui workbench for tuning detector parameters interactively on a folder of images.

cheshm-gui                       # empty workbench
cheshm-gui path/to/folder        # open a folder of eye images
cheshm-gui path/to/a.png p2.png  # open specific files

Development

Cheshm ships precompiled wheels on PyPI for Linux, macOS, and Windows on Python 3.10–3.13, so end users never need to build anything. This section is for users who want to build from source. Building from source needs CMake, a C++20 compiler, OpenCV, and (for PupilLabs2D) Eigen3.

The project uses uv for environment management and scikit-build-core to drive CMake. First-time setup:

cd path/to/cheshm
uv sync

This creates .venv/, installs runtime + build deps, and builds the C++ extensions in editable mode (per [tool.scikit-build] in pyproject.toml).

After changing any C/C++ source, force a recompile:

uv sync --reinstall-package cheshm

Plain uv sync will not notice C/C++ source edits — only pyproject.toml changes.

After changing a binding's signature (a core.cpp under bindings/python/src/), regenerate the matching _core.pyi:

./scripts/regen_stubs.sh

Commit the updated .pyi alongside the .cpp. CI verifies the committed stubs match what stubgen would emit and fails the PR if they drift.

Repo layout

include/cheshm/         public C++ headers (libcheshm_cpp)
  helpers/              shared image-processing helpers (edges, ellipses, image, shape)
  pupil/<Det>/          per-pupil-detector headers
  glint/Simple/         per-glint-detector headers
  limbus/Daugman/       Daugman family (active_contour, integro_differential, pupil_guided)
  align/                rigid alignment headers
  viz/                  visualization headers
src/                    C++ algorithm implementations
bindings/python/
  cheshm/               Python package (PyPI)
  src/                  nanobind C++ glue, one CMake per detector
third_party/poolstl/    vendored parallel-STL backend

Name

In Persian (Farsi), Cheshm (چشم) literally means "eye".

Logo

The nazar / cheshm amulet image is from pngegg.

Acknowledgments

This work received funding from the European Union's Horizon Europe research and innovation funding program under grant agreement No 101072410, Eyes4ICU project.