Add confidence-returning template matching (score / multi-scale / find-all)

[JE-Chen]

Summary

Round-11, automation-core (visual lane). The existing matcher (je_open_cv.find_object) is single-scale and discards the correlation score — no way to rank candidates, set a confidence threshold and read it back, match a DPI/zoom-scaled control, or enumerate every occurrence.

Layers

• Headless core: je_auto_control/utils/visual_match/visual_match.py — Match (x/y/width/height/score/scale/center), match_template (best, multi-scale), match_template_all (all, NMS-deduped), best_matches (top-N). Injectable haystack (ndarray/path/PIL) → headless-testable; OpenCV/NumPy imported lazily (via the je_open_cv dep). No PySide6.
• Facade: re-exported (Match aliased to TemplateMatch) + __all__.
• Executor: AC_match_template → {found, match}, AC_match_template_all → {count, matches}.
• MCP: ac_match_template / ac_match_template_all.
• Script Builder: two CommandSpecs under Image.

Tests / docs

• test/unit_test/headless/test_visual_match_batch.py — 8 headless tests (score+box, no-match, find-all+NMS, multi-scale on a non-self-similar texture, unknown-method ValueError, to_dict + wiring + facade) on synthetic arrays, guarded by pytest.importorskip("cv2").
• EN/Zh feature docs v127_features_doc.rst + toctrees; 3 WHATS_NEW entries.

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[codacy-production]

Not up to standards ⛔

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[sonarqubecloud]

Quality Gate passed

Issues
0 New issues
0 Accepted issues

Measures
0 Security Hotspots
0.0% Coverage on New Code
0.0% Duplication on New Code

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