Upload front + back photos for automated vision analysis (deskew + lighting normalization + Claude grading), or score manually. Backend deterministic TAG-style scoring with PSA / BGS mapping.
Each photo is deskewed (perspective-corrected) and contrast-normalized server-side before Claude vision grades it. Front is required; back is strongly recommended; an angled-light shot improves surface defect detection.
Zoomed views of a single region. Skips card-detect but applies sharpening to expose micro-defects (hairline scratches, print dots, tiny edge nicks). Pick the region so detected defects get attributed correctly.
Drop a short clip walking around the card (front → corners → back, ideally with angled-light passes for surface). Backend extracts ~6 of the sharpest, most-diverse frames via OpenCV (Laplacian-variance sharpness ranking, timeline-spread filtering) then feeds them to Claude as a unified profile. Max 500MB.
Pre-filled by vision analysis when you upload photos. Tweak then click “Run Analysis” to re-grade with your manual adjustments.
None added. The engine treats missing evidence as risk, not clean condition.
Upload photos or fill the form, then click Analyze. Backend at https://grading-ai-analysis.onrender.com runs preprocessing (OpenCV deskew + CLAHE) → Claude vision → grading_engine.build_engine_score.