Rafhan Mazaya FathurrahmanandClaude Fable 5
e76ccb60a6
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
48 lines
2.1 KiB
JavaScript
48 lines
2.1 KiB
JavaScript
// One-off script: freeze the current 74-image product-scan Validation Set into
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// a dedicated, stable folder (sources/product-test-images-fixed/) so re-running
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// the accuracy harness always scores the exact same images, independent of
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// whatever new photos get dropped into the live-intake folder
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// (sources/product-test-images/, still fed by the /manual-label-scan page).
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// Renames each image "<index> <no_sku>.<ext>" (index = its stable position,
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// 1-based) and updates product_manual_labels.json's flat-filename entries to
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// match. Run once from backend/: node scripts/freeze-validation-set.mjs
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import fs from "fs";
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import path from "path";
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const LIVE_DIR = path.join("sources", "product-test-images");
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const FIXED_DIR = path.join("sources", "product-test-images-fixed");
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const LABELS_PATH = path.join("sources", "product_manual_labels.json");
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const labels = JSON.parse(fs.readFileSync(LABELS_PATH, "utf8"));
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const flatEntries = labels.filter((l) => !l.filename.includes("/"));
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if (!fs.existsSync(FIXED_DIR)) fs.mkdirSync(FIXED_DIR, { recursive: true });
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// Resolve by SKU prefix (not entry.filename directly) so this script is
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// idempotent/rerunnable even after a previous run already renamed
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// entry.filename to "<index> <sku>.<ext>" — the live-intake folder always
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// keeps its original "<sku> <product>__<camera-filename>.<ext>" names.
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const liveFiles = fs.readdirSync(LIVE_DIR);
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function findSourceFile(no_sku) {
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const match = liveFiles.find((f) => f.startsWith(`${no_sku} `) || f.startsWith(`${no_sku}__`));
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if (!match) return null;
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return path.join(LIVE_DIR, match);
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}
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let copied = 0;
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flatEntries.forEach((entry, i) => {
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const index = i + 1;
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const srcPath = findSourceFile(entry.no_sku);
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if (!srcPath) {
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throw new Error(`Missing source image for ${entry.no_sku} in ${LIVE_DIR}`);
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}
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const ext = path.extname(srcPath);
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const newFilename = `${index} ${entry.no_sku}${ext}`;
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fs.copyFileSync(srcPath, path.join(FIXED_DIR, newFilename));
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entry.filename = newFilename;
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copied++;
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});
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fs.writeFileSync(LABELS_PATH, JSON.stringify(labels, null, 2), "utf8");
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console.log(`Copied ${copied} images into ${FIXED_DIR} and updated ${LABELS_PATH}.`);
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