Reference Analysis Validator
This skill converts “looks close” into measurable gates. For brand/logo/mascot work, do not model or export until a source manifest and validation thresholds exist.
Required outputs
Create these in the asset output folder:
reference_manifest.json— classified source files, expected parts, thresholds.source_analysis/*.json— image metadata, masks/components/landmarks.validation/front_overlay_reference.png— reference and render overlay.validation/front_mask_validation.json— IoU/SSIM/bbox/centroid report.
Workflow
- Classify sources: front, side, back, top, texture atlas, decals, maps, lightmap, aura/context.
- Build/refresh
reference_manifest.jsonwith hard expected counts and view roles. - Extract masks/components from each source using
scripts/reference_manifest_compiler.pyor existing analyzers. - Render model from matching orthographic camera with reference planes hidden.
- Compare reference mask vs render mask using
scripts/render_overlay_validator.py. - Refuse final export if hard gates fail.
Modality rule
Compare like with like. A wireframe edge mask compared against a shaded beauty render gives misleadingly low IoU. For hard gates, render a flat silhouette/matte pass from Blender or compare reference edges to render edges. Use render_overlay_validator.py --reference-mode ... --render-mode ... when the source and render need different mask extraction modes.
Default validation gates
- primary structural part count: exact.
- front silhouette IoU: target >= 0.90 for rigid/logotype shapes; >= 0.82 acceptable for first mascot reconstruction pass.
- bbox center drift: <= 12 px at 1024 px validation size.
- bbox size drift: <= 3% of image dimension.
- face/eye/smile landmark drift: <= 2% of image dimension when landmarks are defined.
Failure policy
If a repeated mismatch occurs, record the measured failure, then route to the missing specialty skill:
- wrong silhouette →
contour-to-mesh - wrong depth/side/back →
orthographic-registration - wrong textures →
atlas-uv-fitting - wrong whole workflow →
mascot-logo-reconstruction
Read when needed
references/metrics-and-thresholds.mdfor metric definitions and recommended gates.
Sources distilled
Official/library docs to prefer while extending this skill:
- OpenCV contour features: moments, area, perimeter, bounding rectangles.
- OpenCV shape matching / Hu moments.
- OpenCV homography and geometric transforms.
- scikit-image SSIM for perceptual comparison.