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Prepare researcher handoff and fix training validation integrity - #17
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Prepare AutoMorph for researcher handoff by keeping landmark crops from the same source image together during validation, fixing default YOLO model lookup, and preserving the native checkpoint when recovering completed training.
Update the README, training tutorial, environment example, and research handoff guide with current workflows, metric limitations, provenance requirements, and publication acceptance criteria. Repair test collection and configuration isolation, provide a Python 3.10 setup default, and add frontend/backend CI checks.
Validation: 157 backend tests, 25 frontend tests, frontend lint, TypeScript/Vite build, and 14 backend import checks passed locally. The automated local review/test/documentation gate passed. Scientific accuracy certification still requires an external specimen-level evaluation and confirmed model/data provenance and rights.