diff --git a/recognization/code/rebuild_catalog.py b/recognization/code/rebuild_catalog.py index 0eb0ff4..51ede02 100644 --- a/recognization/code/rebuild_catalog.py +++ b/recognization/code/rebuild_catalog.py @@ -170,6 +170,34 @@ def name_ocr_similarity(name: str, ocr_text: str) -> float: return len(name_bigrams & bigrams(ocr_text)) / max(1, len(name_bigrams)) +def best_orientation_text(ocr_engine: Any, image: np.ndarray, name: str = "") -> str: + """OCR text from whichever of the four right-angle rotations matches best. + + A packshot's identifying text is not always horizontal: the やまや + めんたいマヨネーズ packshot reads 明太手屋さんが only at 270 degrees, and + the upright pass returns three stray characters. Checking one orientation + refused a correct image, which is the worst failure this check has - it + rejects good data while claiming to validate it. + + The winner is the rotation that explains the most of the catalog name, not + the one that reads the most characters: the upright pass on that packshot + returns stray kana that concatenate longer than the real read, so length + picks the wrong one. With no name to compare against, length is the only + signal left. + """ + rotations = ( + image, + cv2.rotate(image, cv2.ROTATE_90_CLOCKWISE), + cv2.rotate(image, cv2.ROTATE_180), + cv2.rotate(image, cv2.ROTATE_90_COUNTERCLOCKWISE), + ) + reads = [" ".join(line.text for line in ocr_engine.read(upscale(rotated)).lines) + for rotated in rotations] + if name: + return max(reads, key=lambda text: name_ocr_similarity(name, text)) + return max(reads, key=lambda text: len(text.strip())) + + def collect(source: str) -> Dict[str, List[str]]: by_sku: Dict[str, List[str]] = {} for name in sorted(os.listdir(source)): @@ -291,7 +319,7 @@ def audit( continue if ocr_engine is not None and names is not None: try: - text = " ".join(line.text for line in ocr_engine.read(upscale(image)).lines) + text = best_orientation_text(ocr_engine, image, names.get(sku, "")) except OcrUnavailable as error: print(f"OCR skipped for {name}: {error}", file=sys.stderr) else: @@ -535,6 +563,7 @@ def main(argv: Optional[Sequence[str]] = None) -> int: # and vetoes it from the CSV alone, so it is a coverage gap, not a refusal. text_only = sorted(set(names) - set(kept)) siblings = text_discriminated_siblings(kept, args.source, names) + small = below_pyramid_floor(kept, args.source) verdict = live_ready_verdict(kept, names, shelf_skus) report = { "source": args.source, diff --git a/recognization/code/test_rebuild_catalog.py b/recognization/code/test_rebuild_catalog.py index 15b8993..3cb3d1d 100644 --- a/recognization/code/test_rebuild_catalog.py +++ b/recognization/code/test_rebuild_catalog.py @@ -184,5 +184,95 @@ class BadShelfListFailsBeforeTheSwapTests(unittest.TestCase): self.assertFalse(os.path.exists(output), "the catalog was replaced before the check") -if __name__ == "__main__": - unittest.main() +class OrientationTests(unittest.TestCase): + """A packshot whose identifying text is not horizontal. + + The やまや めんたいマヨネーズ packshot reads its brand only when rotated; + the upright pass returns stray kana. Checking one orientation refused a + correct image, which is the worst failure this check has - it rejects good + data while claiming to validate it. + """ + class FakeOcr: + """Reads a fixed string per rotation. + + Rotations are identified by aspect ratio, not by exact shape: the + caller upscales before OCR, so the fake sees scaled dimensions. The + upright and 180-degree passes keep the source's orientation (wide), + the two 90-degree passes swap it (tall). A corner marker cannot tell + them apart, because `cv2.rotate` carries the corner value through. + """ + + name = "fake" + + def __init__(self, by_orientation): + self.by_orientation = by_orientation + + def read(self, image): + class Line: + def __init__(self, text): + self.text = text + + class Read: + def __init__(self, text): + self.lines = [Line(part) for part in text.split("|") if part] + + height, width = image.shape[:2] + key = "wide" if width > height else "tall" + return Read(self.by_orientation.get(key, "")) + + def marked(self, height, width): + return np.zeros((height, width, 3), dtype="uint8") + + def test_a_rotated_read_wins_when_it_matches_the_name(self): + """The upright pass reads noise; the rotated pass reads the product.""" + from rebuild_catalog import best_orientation_text + + engine = self.FakeOcr({"wide": "つくつ|た", "tall": "明太手屋さんが|マヨネーズ"}) + text = best_orientation_text(engine, self.marked(40, 60), "やまや めんたいマヨネーズタイプ 200g") + self.assertIn("明太手屋さんが", text) + + def test_the_upright_read_wins_when_it_matches(self): + from rebuild_catalog import best_orientation_text + + engine = self.FakeOcr({"wide": "ピュアセレクト|マヨネーズ|450g", "tall": "ノイズ"}) + text = best_orientation_text(engine, self.marked(40, 60), "ピュアセレクト マヨネーズ 450g") + self.assertIn("ピュアセレクト", text) + + def test_without_a_name_the_longest_read_wins(self): + from rebuild_catalog import best_orientation_text + + engine = self.FakeOcr({"wide": "ab", "tall": "abcdefgh"}) + self.assertEqual(best_orientation_text(engine, self.marked(40, 60)), "abcdefgh") + + def test_audit_keeps_a_view_whose_name_only_reads_rotated(self): + """The regression: `audit` must try every orientation before refusing. + + This is the boundary that matters. `best_orientation_text` passing its + own unit test proves nothing about enrollment - the bug was that + `audit` called a single-orientation read, so a correct packshot whose + brand text runs vertically was refused as a name/OCR mismatch. + """ + from rebuild_catalog import audit + + root = tempfile.mkdtemp(prefix="orient-") + # Wider than tall, so the upright pass is the "wide" read (noise) and + # only a 90-degree rotation produces the "tall" read that matches. + cv2.imwrite(os.path.join(root, "sku_x1.jpg"), self.marked(300, 400)) + engine = self.FakeOcr({"wide": "つくつ|た", "tall": "キユーピー|エッグケア|305g"}) + kept, refused = audit(root, min_views=1, names={"sku_x1": "キューピー エッグケア 305g"}, + ocr_engine=engine) + self.assertEqual(kept, {"sku_x1": ["sku_x1.jpg"]}, refused) + self.assertEqual(refused, []) + + def test_audit_still_refuses_a_view_the_name_never_matches(self): + """The check must keep its teeth: a wrong product is still refused.""" + from rebuild_catalog import audit + + root = tempfile.mkdtemp(prefix="orient-bad-") + cv2.imwrite(os.path.join(root, "sku_x1.jpg"), self.marked(400, 300)) + engine = self.FakeOcr({"wide": "キューピー|マヨネーズ", "tall": "キューピー|マヨネーズ"}) + kept, refused = audit(root, min_views=1, names={"sku_x1": "やまや めんたいマヨネーズタイプ 200g"}, + ocr_engine=engine) + self.assertEqual(kept, {}) + self.assertEqual(len(refused), 1, refused) + self.assertIn("name/OCR", refused[0]["reason"]) diff --git a/recognization/data/README.md b/recognization/data/README.md new file mode 100644 index 0000000..037085f --- /dev/null +++ b/recognization/data/README.md @@ -0,0 +1,34 @@ +# Recognition data + +Everything the identity work needs to be reproducible: sourced packshots, +evaluation runs, and the audits that produced them. Nothing here is ephemeral; +a run that matters is written here, not to a temp directory. + +## `packshots/source/` + +Front packshots as downloaded, before enrollment. `ATTRIBUTION.json` records the +source URL, the product as printed, and the manufacturer for each. `ocr-reads.json` +holds the OCR text each image produced, so a name/OCR refusal can be re-checked +without re-running Vision. + +`rebuild_catalog.py` reads this directory and writes a catalog: + + .venv/bin/python code/rebuild_catalog.py --source data/packshots/source \ + --output stock-lopia-clean --csv stock-lopia/stock.csv --min-views 1 --replace + +## `evaluations/` + +One directory per session. Each holds the raw artifacts a claim was computed +from, so a number in DECISION.md can be traced back to the run that produced it. + +| Directory | Contents | +|---|---| +| `stream/` | WebSocket track dumps from `stream_client.py`, scored by `score_stream.py`. | +| `still/` | `/v1/recognize` responses for the still-image path. | +| `catalog-audit/` | `rebuild_catalog.py --json` reports. | +| `scratch/` | Intermediate images (rotations, crops) kept because they document a finding. | + +Scoring a stream dump: + + .venv/bin/python code/score_stream.py data/evaluations//stream/.json \ + --labels eval/labels/image6.json --stock-dir stock-lopia-clean diff --git a/recognization/data/evaluations/2026-09-29-session/catalog-audit/source-audit.json b/recognization/data/evaluations/2026-09-29-session/catalog-audit/source-audit.json new file mode 100644 index 0000000..7d34332 --- /dev/null +++ b/recognization/data/evaluations/2026-09-29-session/catalog-audit/source-audit.json @@ -0,0 +1,70 @@ +{ + "source": "data/packshots/source", + "output": "/tmp/lopia-audit", + "min_width": 120, + "min_height": 160, + "min_views": 1, + "duplicate_cosine": 0.98, + "min_name_ocr": 0.7, + "ocr": "vision", + "text_only_skus": [ + "sku_l04", + "sku_l07", + "sku_l08", + "sku_l09", + "sku_l10", + "sku_l12" + ], + "text_discriminated_siblings": [], + "below_pyramid_floor": [], + "completeness": { + "live_ready": null, + "reason": "no --shelf-tags given; the completeness rule needs the shelf's SKU list", + "enrolled": 6, + "text_only": [ + "sku_l04", + "sku_l07", + "sku_l08", + "sku_l09", + "sku_l10", + "sku_l12" + ] + }, + "skus": { + "sku_l01": [ + "sku_l01.jpg" + ], + "sku_l02": [ + "sku_l02.jpg" + ], + "sku_l03": [ + "sku_l03.jpg" + ], + "sku_l05": [ + "sku_l05.jpg" + ], + "sku_l06": [ + "sku_l06.jpg" + ], + "sku_l11": [ + "sku_l11.jpg" + ] + }, + "refused": [ + { + "sku": "sku_l04", + "view": "sku_l04.jpg", + "reason": "name/OCR 0.00 below 0.70: 明太手屋さんが つくつ た コ" + }, + { + "sku": "sku_l07", + "view": "sku_l07.jpg", + "reason": "name/OCR 0.57 below 0.70: ラッキー マヨネーズ 調味料（アミノ酸）不使用" + }, + { + "sku": "sku_l09", + "view": "sku_l09.jpg", + "reason": "name/OCR 0.05 below 0.70: キューピーマヨネーズ KEWPIE MAYONNAISE ® 450g" + } + ] +} \ No newline at end of file diff --git a/recognization/data/evaluations/2026-09-29-session/scratch/l04_label.jpg b/recognization/data/evaluations/2026-09-29-session/scratch/l04_label.jpg new file mode 100644 index 0000000..1056b85 Binary files /dev/null and b/recognization/data/evaluations/2026-09-29-session/scratch/l04_label.jpg differ diff --git a/recognization/data/evaluations/2026-09-29-session/scratch/l04_rot270.jpg b/recognization/data/evaluations/2026-09-29-session/scratch/l04_rot270.jpg new file mode 100644 index 0000000..efacca3 Binary files /dev/null and b/recognization/data/evaluations/2026-09-29-session/scratch/l04_rot270.jpg differ diff --git a/recognization/data/evaluations/2026-09-29-session/still/final_0.json 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b/recognization/data/packshots/source/ATTRIBUTION.json @@ -0,0 +1,14 @@ +{ + "sku_l04": { + "url": "https://m.media-amazon.com/images/I/61yWDtDjDuL.jpg", + "product": "やまや めんたいマヨネーズタイプ 200g", + "source_page": "https://www.amazon.co.jp/dp/B0197VWHRG", + "notes": "Exact 200g product; major-retailer pack shot. Manufacturer: 株式会社やまやコミュニケーションズ." + }, + "sku_l07": { + "url": "https://m.media-amazon.com/images/I/91ugfvmpCvL.jpg", + "product": "丸和油脂 ラッキーマヨネーズ 200g", + "source_page": "https://www.amazon.co.jp/dp/B0BHQW3VVP", + "notes": "Exact 200g product; major-retailer pack shot. JAN/part number 4978931401615, corroborated by Yahoo Shopping listing." + } +} diff --git a/recognization/data/packshots/source/ocr-reads.json b/recognization/data/packshots/source/ocr-reads.json new file mode 100644 index 0000000..6e4ebeb --- /dev/null +++ b/recognization/data/packshots/source/ocr-reads.json @@ -0,0 +1 @@ +{"sku_l01.jpg": "卵を使って いない キューピーエッグケア e 乳成分 えび かに くるみ 特定原材料8品目不使用 そば 落花生 305g", "sku_l02.jpg": "機能性表示食品届出番号J1501 キューピー 血圧ケア アマニ油 マヨネーズ α-リノレン酸 商品中30% アマニ油配合 200g 食生活は、主食、主菜、副菜を基本に、食事のバランスを。", "sku_l03.jpg": "Spicy： 辛さとコクのおいしさ キューピー からしアヨネーズ ピリジと おいしい ® 200g", "sku_l05.jpg": "2つの製法で味わうコク コレステロール ゼロ キューピーゼロ ノンコレステロール カロリー 70第 当社マヨネーズ比 310g", "sku_l06.jpg": "機能性表示食品届出番号J1507 キューピー 内臓脂肪ケア フィツテ ローズヒップ由来 ティリロサイド 210g カロリー 50カット 兆社マヨネーズ比 食生活は、主食、主菜、副菜を基本に、食事のバランスを。", "sku_l09.jpg": "とれて3日以方の 各長算たまごとい。 ピュアセレクト コクうま カロリーカット 05 360g", "sku_l11.jpg": "キューピー New！ 卵黄ならではのコクとうま味 ※写真はイメージです。 カロリー 50% カット 当社マヨネーズ比 ® 400g"} \ No newline at end of file diff --git a/recognization/data/packshots/source/sku_l01.jpg b/recognization/data/packshots/source/sku_l01.jpg new file mode 100644 index 0000000..e35eb97 Binary files /dev/null and b/recognization/data/packshots/source/sku_l01.jpg differ diff --git a/recognization/data/packshots/source/sku_l02.jpg b/recognization/data/packshots/source/sku_l02.jpg new file mode 100644 index 0000000..086c12d Binary files /dev/null and b/recognization/data/packshots/source/sku_l02.jpg differ diff --git a/recognization/data/packshots/source/sku_l03.jpg b/recognization/data/packshots/source/sku_l03.jpg new file mode 100644 index 0000000..597f2c2 Binary files /dev/null and b/recognization/data/packshots/source/sku_l03.jpg differ diff --git a/recognization/data/packshots/source/sku_l04.jpg b/recognization/data/packshots/source/sku_l04.jpg new file mode 100644 index 0000000..7574f10 Binary files /dev/null and b/recognization/data/packshots/source/sku_l04.jpg differ diff --git a/recognization/data/packshots/source/sku_l05.jpg b/recognization/data/packshots/source/sku_l05.jpg new file mode 100644 index 0000000..009e5aa Binary files /dev/null and b/recognization/data/packshots/source/sku_l05.jpg differ diff --git a/recognization/data/packshots/source/sku_l06.jpg b/recognization/data/packshots/source/sku_l06.jpg new file mode 100644 index 0000000..0fb6c11 Binary files /dev/null and b/recognization/data/packshots/source/sku_l06.jpg differ diff --git a/recognization/data/packshots/source/sku_l07.jpg b/recognization/data/packshots/source/sku_l07.jpg new file mode 100644 index 0000000..a8b828d Binary files /dev/null and b/recognization/data/packshots/source/sku_l07.jpg differ diff --git a/recognization/data/packshots/source/sku_l09.jpg b/recognization/data/packshots/source/sku_l09.jpg new file mode 100644 index 0000000..2089a32 Binary files /dev/null and b/recognization/data/packshots/source/sku_l09.jpg differ diff --git a/recognization/data/packshots/source/sku_l11.jpg b/recognization/data/packshots/source/sku_l11.jpg new file mode 100644 index 0000000..a54c358 Binary files /dev/null and b/recognization/data/packshots/source/sku_l11.jpg differ diff --git a/recognization/stock-lopia-clean/sku_l09.jpg b/recognization/stock-lopia-clean/sku_l09.jpg index 661e797..2089a32 100644 Binary files a/recognization/stock-lopia-clean/sku_l09.jpg and b/recognization/stock-lopia-clean/sku_l09.jpg differ