[HIGH PRIORITY] mypy is not run anywhere in CI or dev tooling

Found 2026-07-29 while fixing the _ImageBase Protocol gaps in
ImageBlobs.py/ImageRegionFeatures.py/ImagePointFeatures.py
(see git history — three mixins were missing the
class XMixin(_ImageBase if TYPE_CHECKING else object) pattern every
other mixin uses). That fix prompted the question: if a new method is
added to a mixin and it's accessed via self. from a different
mixin, and it's not yet declared in _image_typing.py's _ImageBase
Protocol, what actually catches that? Answer: nothing, currently.
mypy is not in pyproject.toml's dev extra and does not run in any
.github/workflows/*.yml — confirmed by grep, zero hits. So a Protocol
gap like this doesn't fail a build or even show a warning; it just
silently produces incomplete/wrong type information for anyone using an
editor with type-checking (Pylance, mypy in an IDE), with no automated
signal anywhere. This is the quietest version of a pattern that's
already bitten this project twice today in more visible forms (the
image_class.rst autosummary list silently going stale for the whole
Image sidebar, and ci.yml's conda create-args list silently
missing pgraph-python/drifting on opencv) — a hand-maintained
shadow list with no automated check that it stays in sync with reality.

Ran mypy src/machinevisiontoolbox --ignore-missing-imports fresh,
2026-07-29 (superseding the stale, less-categorized April audit in
NOTES): 524 errors in 31 files (checked 49 source files). By
category:

Correcting an initial hypothesis: expected most attr-defined
errors to trace to incomplete _ImageBase coverage (only ~96 of
Image's ~290 public members are declared — by design, since the
Protocol only needs to cover attributes actually cross-referenced
between mixins, not the full public API). Checked the real breakdown
instead of assuming: none of the current attr-defined errors are
actually _ImageBase gaps. The two real dominant causes are unrelated:

• 23 of 84: machinevisiontoolbox/base/__init__.py re-exports every
  submodule via wildcard from X import * (9 submodules) with no
  explicit __all__/direct re-export list; mypy can't reliably resolve
  names through that chain, so every file that does
  from machinevisiontoolbox.base import (draw_circle, plot_labelbox, findpeaks2d, ...) gets a false "module has no attribute" even though
  these work fine at runtime.
• 8 of 84: cv2.<X>_create dynamic dispatch (getattr(cv2, ...) /
  getattr(cv2.xfeatures2d, ...) patterns in ImagePointFeatures.py's
  feature-detector dict) — mypy can't type-check dynamic attribute
  access, expected and low-value to fix.
• The remaining ~53 are scattered; VisualServo.py alone accounts for
  44 of the 84 attr-defined errors (a mix of real typos like
  "plotpose"; maybe "plot_pose"? and missing machinevisiontoolbox.base
  attributes via the same wildcard-import issue) and is worth its own
  look independent of the mixin-Protocol question that prompted this
  audit.

The _ImageBase-completeness risk described above is still real, just
currently latent rather than demonstrated by a live error — worth
re-running this same mypy audit after any future mixin refactor to
catch it if it does start manifesting.

Fix

Two independent pieces, roughly in priority order:

1. Fix machinevisiontoolbox/base/__init__.py's wildcard re-exports
   (add explicit __all__ composed from each submodule's own __all__,
   or switch to explicit from X import (name1, name2, ...) — either
   should immediately clear ~23+ of the attr-defined count and is a
   mechanical, low-risk change).
2. Wire mypy into CI (even just as a non-blocking/advisory job at
   first, given 524 existing errors) so future drift is visible instead
   of silent. Add mypy to pyproject.toml's dev extra either way.
   Do not attempt to fix all 524 errors in one pass — triage by category
   (the [call-arg]/[override]/[return] categories are more likely to
   be real bugs; assignment/arg-type/index are more likely the
   ArrayLike-union-too-broad pattern the April NOTES audit already
   identified).

Beginne damit, pyproject.toml, .github/workflows/*.yml und machinevisiontoolbox/base/init.py zu lesen; führe den dokumentierten mypy-Befehl aus, um die Ausgangsbasis von 524 Fehlern zu bestätigen. Vergleiche die Exporte der Submodule und die vorhandenen CI-Jobs und mache dann die Type-Checking-Konfiguration sichtbar, ohne zu versuchen, jeden gemeldeten Fehler zu beheben. Erledigt ist die Aufgabe, wenn mypy in den Dev-Tools enthalten ist und ein CI-Job seine Ergebnisse meldet, wobei die base-Re-Exports im festgelegten Umfang berücksichtigt werden.