2026-07-15 re-run of the 79-image benchmark: the tiled full-res pass, VL
text-line evidence, and VL SKU retry deployed at end of 2026-07-14 produce
ZERO flips vs the 79.7% baseline (only img1's expiry pred changed to a
lenient-parse garble). Detail dump: product_scan_detail_20260715.json.
Probe endpoint POST :8120/probe-ocr (temporary, remove before production):
OCRs a crop of a container-local image through arbitrary preprocessing
recipes (scale/blur/close/CLAHE/threshold) and alternate readers - VL
layout-parsing with/without layout detection, direct VLM chat on :8118,
lazily-loaded PP-OCRv5 server det/rec. Probing the dot-matrix expiry crops
of img2/img41 with every combination shows none of the stack's models can
read these prints (VL tags them as pictures, VLM hallucinates, v5-server
skips them) - the 21 expiry non-detections are a model capability ceiling,
not a pipeline bug.
Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01Gr6HH7JrdsXX8AARejQboM
Accuracy work on the 79-image product-scan validation set (user goal: 90%):
- classify_ocr_server.py: 0/90/180/270-degree expiry-date search (stops at
first hit, 0-degree fallback); classification decoupled onto the upright
image (rotated frames regressed DINOv2 -6pts until this); cross-line date
stitching; tiled full-res OCR pass (defeats the 4000px downscale that
killed small inkjet dates); VL-pipeline expiry fallback with
keyword-anchored anti-hallucination guard; VL text lines merged into
text_lines + VL SKU retry. Visualization endpoints removed entirely
(Visual/Spotting grids - unused by frontend, 3x per-scan GPU cost).
- product-scan.ts: coverage-normalized OCR-evidence re-ranking of DINOv2
top-K (tuned offline: +8/-0 on top-1 misses), re-ranked class mapped to
sku_master by SKU prefix; classifier timeout 90s->240s for fallback paths.
- Frozen benchmark: product-test-images-fixed/ (79 renamed images) +
freeze/seed/build-undetected/capture/experiment scripts; labels trimmed to
the 79 validation entries (training rows kept in .bak-with-training);
5 TRAINED-ON SKUs replaced with fresh held-out photos.
- manual-label-scan page: shows last batch-test AI prediction under every
field by default (new /api/product-scan-results); serves the fixed folder;
fixed total hydration failure via allowedDevOrigins 127.0.0.1.
- Measured (all-79, zero failures): sku/name 87.3%, expiry 64.6%, overall
79.7%. Tiles/VL-evidence/VL-SKU deployed but not yet batch-measured.
Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01Gr6HH7JrdsXX8AARejQboM
fhanyuh
