{"abstract":"Restoring a deduplicated photo turns it a half turn away from the upload.","category":"Image orientation metadata","checks":8,"contract":"For duplicate detection, bring a pixel grid into a canonical orientation: of the eight orientations (tags 1..8, same pixel mapping as EXIF baking), pick the one whose key (height, width, row-major pixels) is smallest; ties go to the lowest tag. Return [tag, inverse_tag, canonical_grid] where the inverse tag restores the original (6 and 8 are mutual inverses, every other tag is self-inverse).","contract_signature":"grid","evaluation_group":"w2-image-orientation-metadata-dedup-canonical-orientation","failed_approach":"Transpose and transverse are their own inverses; exchanging them is wrong.","family":"w2-image-orientation-metadata-dedup-canonical-orientation-inverse-map","id":"FA-79311","implementations":{"attempt":{"sha256":"914a76d0cd32741235fff18db5c01e790393537f78e197b04325532019f93a5f","source":"\"\"\"Failure Map reference implementation. Python standard library only.\"\"\"\nimport json\n\nN = 1\nobservations = []\ndef solve(grid):\n    h = len(grid)\n    w = len(grid[0])\n    def src(t, r, c):\n        return {1: (r, c), 2: (r, w - 1 - c), 3: (h - 1 - r, w - 1 - c), 4: (h - 1 - r, c),\n                5: (c, r), 6: (h - 1 - c, r), 7: (h - 1 - c, w - 1 - r), 8: (c, w - 1 - r)}[t]\n    best = None\n    for t in range(1, 9):\n        oh, ow = (w, h) if t >= 5 else (h, w)\n        img = [[grid[src(t, r, c)[0]][src(t, r, c)[1]] for c in range(ow)] for r in range(oh)]\n        key = (oh, ow, [v for row in img for v in row])\n        if best is None or key < best[0]:\n            best = (key, t, img)\n    inverse = {5: 7, 7: 5}.get(best[1], best[1])\n    return [best[1], inverse, best[2]]\ndef check(label, actual, expected):\n    observations.append({\"check\": label, \"actual\": actual, \"expected\": expected, \"passed\": actual == expected})\nfixtures = [[[[[5, 2], [9, 7], [6, 9]], [8, 6, [[2, 7, 9], [5, 9, 6]]]], [[[0, 0], [1, 1], [0, 1]], [5, 5, [[0, 1, 0], [0, 1, 1]]]], [[[3, 1], [2, 6], [9, 2]], [8, 6, [[1, 6, 2], [3, 2, 9]]]], [[[4, 7, 0]], [2, 2, [[0, 7, 4]]]], [[[6, 3, 0], [0, 8, 5], [1, 5, 5]], [2, 2, [[0, 3, 6], [5, 8, 0], [5, 5, 1]]]], [[[7]], [1, 1, [[7]]]], [[[0, 1, 1]], [1, 1, [[0, 1, 1]]]], [[[0, 1], [0, 0], [0, 0]], [6, 8, [[0, 0, 0], [0, 0, 1]]]]], [[[[4], [3], [0]], [6, 8, [[0, 3, 4]]]], [[[9], [8]], [6, 8, [[8, 9]]]], [[[4, 4]], [1, 1, [[4, 4]]]], [[[0, 0, 0], [0, 1, 1]], [1, 1, [[0, 0, 0], [0, 1, 1]]]], [[[9]], [1, 1, [[9]]]], [[[1, 0, 1]], [1, 1, [[1, 0, 1]]]], [[[8, 6, 5], [0, 7, 5], [2, 0, 8]], [4, 4, [[2, 0, 8], [0, 7, 5], [8, 6, 5]]]], [[[1, 1], [4, 4], [9, 1]], [8, 6, [[1, 4, 1], [1, 4, 9]]]]], [[[[4], [7], [2]], [6, 8, [[2, 7, 4]]]], [[[5], [4]], [6, 8, [[4, 5]]]], [[[8, 9], [6, 5], [4, 8]], [6, 8, [[4, 6, 8], [8, 5, 9]]]], [[[0, 3]], [1, 1, [[0, 3]]]], [[[1, 0, 0], [1, 0, 0]], [2, 2, [[0, 0, 1], [0, 0, 1]]]], [[[6, 5, 2]], [2, 2, [[2, 5, 6]]]], [[[4, 0, 8], [5, 8, 1], [9, 9, 6]], [1, 1, [[4, 0, 8], [5, 8, 1], [9, 9, 6]]]], [[[0, 0], [1, 0], [1, 1]], [8, 6, [[0, 0, 1], [0, 1, 1]]]]], [[[[1, 1], [8, 1], [9, 9]], [8, 6, [[1, 1, 9], [1, 8, 9]]]], [[[4], [5], [0]], [6, 8, [[0, 5, 4]]]], [[[8], [4], [3]], [6, 8, [[3, 4, 8]]]], [[[8, 7, 3], [3, 8, 4]], [2, 2, [[3, 7, 8], [4, 8, 3]]]], [[[3, 8, 5]], [1, 1, [[3, 8, 5]]]], [[[3, 8]], [1, 1, [[3, 8]]]], [[[9, 4], [2, 1]], [3, 3, [[1, 2], [4, 9]]]], [[[6, 7, 5], [1, 9, 6], [6, 4, 6]], [8, 6, [[5, 6, 6], [7, 9, 4], [6, 1, 6]]]]], [[[[5, 0], [5, 5], [8, 7]], [8, 6, [[0, 5, 7], [5, 5, 8]]]], [[[0], [1], [0]], [5, 5, [[0, 1, 0]]]], [[[3], [1]], [6, 8, [[1, 3]]]], [[[3, 2, 0], [2, 8, 5], [9, 0, 9]], [2, 2, [[0, 2, 3], [5, 8, 2], [9, 0, 9]]]], [[[4, 9, 9], [3, 6, 8]], [4, 4, [[3, 6, 8], [4, 9, 9]]]], [[[3, 0, 4]], [1, 1, [[3, 0, 4]]]], [[[2, 0, 5], [5, 0, 3], [2, 8, 2]], [1, 1, [[2, 0, 5], [5, 0, 3], [2, 8, 2]]]], [[[9, 6], [3, 3], [3, 5]], [6, 8, [[3, 3, 9], [5, 3, 6]]]]]]\nlabels = [\"regression: restoring inverse tag\", \"repair trap\", \"combined fault\", \"control\", \"control\", \"boundary\", \"boundary\", \"control\"]\nfor i, (args, expected) in enumerate(fixtures[N-1]):\n    check(\"%s %d\" % (labels[i % len(labels)], i), solve(args), expected)\nprint(json.dumps({\"observations\": observations, \"passed\": all(x[\"passed\"] for x in observations)}, ensure_ascii=False))\nraise SystemExit(0 if all(x[\"passed\"] for x in observations) else 1)\n"},"broken":{"sha256":"c2817685287bd65e4c9d1dcce2d8ffc4e293f60c2aa1a285cadfb95cf5d6b543","source":"\"\"\"Failure Map reference implementation. Python standard library only.\"\"\"\nimport json\n\nN = 1\nobservations = []\ndef solve(grid):\n    h = len(grid)\n    w = len(grid[0])\n    def src(t, r, c):\n        return {1: (r, c), 2: (r, w - 1 - c), 3: (h - 1 - r, w - 1 - c), 4: (h - 1 - r, c),\n                5: (c, r), 6: (h - 1 - c, r), 7: (h - 1 - c, w - 1 - r), 8: (c, w - 1 - r)}[t]\n    best = None\n    for t in range(1, 9):\n        oh, ow = (w, h) if t >= 5 else (h, w)\n        img = [[grid[src(t, r, c)[0]][src(t, r, c)[1]] for c in range(ow)] for r in range(oh)]\n        key = (oh, ow, [v for row in img for v in row])\n        if best is None or key < best[0]:\n            best = (key, t, img)\n    inverse = best[1]\n    return [best[1], inverse, best[2]]\ndef check(label, actual, expected):\n    observations.append({\"check\": label, \"actual\": actual, \"expected\": expected, \"passed\": actual == expected})\nfixtures = [[[[[5, 2], [9, 7], [6, 9]], [8, 6, [[2, 7, 9], [5, 9, 6]]]], [[[0, 0], [1, 1], [0, 1]], [5, 5, [[0, 1, 0], [0, 1, 1]]]], [[[3, 1], [2, 6], [9, 2]], [8, 6, [[1, 6, 2], [3, 2, 9]]]], [[[4, 7, 0]], [2, 2, [[0, 7, 4]]]], [[[6, 3, 0], [0, 8, 5], [1, 5, 5]], [2, 2, [[0, 3, 6], [5, 8, 0], [5, 5, 1]]]], [[[7]], [1, 1, [[7]]]], [[[0, 1, 1]], [1, 1, [[0, 1, 1]]]], [[[0, 1], [0, 0], [0, 0]], [6, 8, [[0, 0, 0], [0, 0, 1]]]]], [[[[4], [3], [0]], [6, 8, [[0, 3, 4]]]], [[[9], [8]], [6, 8, [[8, 9]]]], [[[4, 4]], [1, 1, [[4, 4]]]], [[[0, 0, 0], [0, 1, 1]], [1, 1, [[0, 0, 0], [0, 1, 1]]]], [[[9]], [1, 1, [[9]]]], [[[1, 0, 1]], [1, 1, [[1, 0, 1]]]], [[[8, 6, 5], [0, 7, 5], [2, 0, 8]], [4, 4, [[2, 0, 8], [0, 7, 5], [8, 6, 5]]]], [[[1, 1], [4, 4], [9, 1]], [8, 6, [[1, 4, 1], [1, 4, 9]]]]], [[[[4], [7], [2]], [6, 8, [[2, 7, 4]]]], [[[5], [4]], [6, 8, [[4, 5]]]], [[[8, 9], [6, 5], [4, 8]], [6, 8, [[4, 6, 8], [8, 5, 9]]]], [[[0, 3]], [1, 1, [[0, 3]]]], [[[1, 0, 0], [1, 0, 0]], [2, 2, [[0, 0, 1], [0, 0, 1]]]], [[[6, 5, 2]], [2, 2, [[2, 5, 6]]]], [[[4, 0, 8], [5, 8, 1], [9, 9, 6]], [1, 1, [[4, 0, 8], [5, 8, 1], [9, 9, 6]]]], [[[0, 0], [1, 0], [1, 1]], [8, 6, [[0, 0, 1], [0, 1, 1]]]]], [[[[1, 1], [8, 1], [9, 9]], [8, 6, [[1, 1, 9], [1, 8, 9]]]], [[[4], [5], [0]], [6, 8, [[0, 5, 4]]]], [[[8], [4], [3]], [6, 8, [[3, 4, 8]]]], [[[8, 7, 3], [3, 8, 4]], [2, 2, [[3, 7, 8], [4, 8, 3]]]], [[[3, 8, 5]], [1, 1, [[3, 8, 5]]]], [[[3, 8]], [1, 1, [[3, 8]]]], [[[9, 4], [2, 1]], [3, 3, [[1, 2], [4, 9]]]], [[[6, 7, 5], [1, 9, 6], [6, 4, 6]], [8, 6, [[5, 6, 6], [7, 9, 4], [6, 1, 6]]]]], [[[[5, 0], [5, 5], [8, 7]], [8, 6, [[0, 5, 7], [5, 5, 8]]]], [[[0], [1], [0]], [5, 5, [[0, 1, 0]]]], [[[3], [1]], [6, 8, [[1, 3]]]], [[[3, 2, 0], [2, 8, 5], [9, 0, 9]], [2, 2, [[0, 2, 3], [5, 8, 2], [9, 0, 9]]]], [[[4, 9, 9], [3, 6, 8]], [4, 4, [[3, 6, 8], [4, 9, 9]]]], [[[3, 0, 4]], [1, 1, [[3, 0, 4]]]], [[[2, 0, 5], [5, 0, 3], [2, 8, 2]], [1, 1, [[2, 0, 5], [5, 0, 3], [2, 8, 2]]]], [[[9, 6], [3, 3], [3, 5]], [6, 8, [[3, 3, 9], [5, 3, 6]]]]]]\nlabels = [\"regression: restoring inverse tag\", \"repair trap\", \"combined fault\", \"control\", \"control\", \"boundary\", \"boundary\", \"control\"]\nfor i, (args, expected) in enumerate(fixtures[N-1]):\n    check(\"%s %d\" % (labels[i % len(labels)], i), solve(args), expected)\nprint(json.dumps({\"observations\": observations, \"passed\": all(x[\"passed\"] for x in observations)}, ensure_ascii=False))\nraise SystemExit(0 if all(x[\"passed\"] for x in observations) else 1)\n"}},"limitations":"A deterministic bounded teaching model with a stipulated contract; it makes no claim of conformance to any published specification. This reproducer isolates one failure mechanism. Results cover the supplied fixtures. Variants within a family share a test contract and should remain grouped when constructing evaluation splits. Related mechanisms with a shared evaluation_group must also remain together; these controlled models are not independent production incidents.","method":"Deterministic executable model with adversarial boundary fixtures.","provenance":{"created_by":"Failure Map","dependencies":"Python standard library","family":"w2-image-orientation-metadata-dedup-canonical-orientation-inverse-map","generated_at":"2026-09-29T14:49:43.351227+00:00","license":"CC0-1.0","python":"3.12.14","seed":1,"split":"open-access"},"relevance":"Camera, phone and scanner images carry an orientation hint separately from the stored pixels; galleries, thumbnailers, editors and upload pipelines must interpret it consistently or photos appear sideways, mirrored or doubly rotated.","root_cause":"The inverse of a quarter turn is reported as the same quarter turn.","sha256":"260c2b1af4453977b82b72257f12b688b4052e75bdf5a90a2f42cbaa5b6293be","title":"Canonical restore tag treats quarter turns as self-inverse · case 01","variant":1,"variant_policy":"Five numbered records share a model and may reuse boundary fixtures.","verified":true,"visibility":"public","verification":{"attempt":{"elapsed_ms":42.437,"exit_code":1,"observations":[{"actual":[8,8,[[2,7,9],[5,9,6]]],"check":"regression: restoring inverse tag 0","expected":[8,6,[[2,7,9],[5,9,6]]],"passed":false},{"actual":[5,7,[[0,1,0],[0,1,1]]],"check":"repair trap 1","expected":[5,5,[[0,1,0],[0,1,1]]],"passed":false},{"actual":[8,8,[[1,6,2],[3,2,9]]],"check":"combined fault 2","expected":[8,6,[[1,6,2],[3,2,9]]],"passed":false},{"actual":[2,2,[[0,7,4]]],"check":"control 3","expected":[2,2,[[0,7,4]]],"passed":true},{"actual":[2,2,[[0,3,6],[5,8,0],[5,5,1]]],"check":"control 4","expected":[2,2,[[0,3,6],[5,8,0],[5,5,1]]],"passed":true},{"actual":[1,1,[[7]]],"check":"boundary 5","expected":[1,1,[[7]]],"passed":true},{"actual":[1,1,[[0,1,1]]],"check":"boundary 6","expected":[1,1,[[0,1,1]]],"passed":true},{"actual":[6,6,[[0,0,0],[0,0,1]]],"check":"control 7","expected":[6,8,[[0,0,0],[0,0,1]]],"passed":false}],"passed":false,"stderr":"","stdout":"{\"observations\": [{\"check\": \"regression: restoring inverse tag 0\", \"actual\": [8, 8, [[2, 7, 9], [5, 9, 6]]], \"expected\": [8, 6, [[2, 7, 9], [5, 9, 6]]], \"passed\": false}, {\"check\": \"repair trap 1\", \"actual\": [5, 7, [[0, 1, 0], [0, 1, 1]]], \"expected\": [5, 5, [[0, 1, 0], [0, 1, 1]]], \"passed\": false}, {\"check\": \"combined fault 2\", \"actual\": [8, 8, [[1, 6, 2], [3, 2, 9]]], \"expected\": [8, 6, [[1, 6, 2], [3, 2, 9]]], \"passed\": false}, {\"check\": \"control 3\", \"actual\": [2, 2, [[0, 7, 4]]], \"expected\": [2, 2, [[0, 7, 4]]], \"passed\": true}, {\"check\": \"control 4\", \"actual\": [2, 2, [[0, 3, 6], [5, 8, 0], [5, 5, 1]]], \"expected\": [2, 2, [[0, 3, 6], [5, 8, 0], [5, 5, 1]]], \"passed\": true}, {\"check\": \"boundary 5\", \"actual\": [1, 1, [[7]]], \"expected\": [1, 1, [[7]]], \"passed\": true}, {\"check\": \"boundary 6\", \"actual\": [1, 1, [[0, 1, 1]]], \"expected\": [1, 1, [[0, 1, 1]]], \"passed\": true}, {\"check\": \"control 7\", \"actual\": [6, 6, [[0, 0, 0], [0, 0, 1]]], \"expected\": [6, 8, [[0, 0, 0], [0, 0, 1]]], \"passed\": false}], \"passed\": false}\n"},"broken":{"elapsed_ms":39.887,"exit_code":1,"observations":[{"actual":[8,8,[[2,7,9],[5,9,6]]],"check":"regression: restoring inverse tag 0","expected":[8,6,[[2,7,9],[5,9,6]]],"passed":false},{"actual":[5,5,[[0,1,0],[0,1,1]]],"check":"repair trap 1","expected":[5,5,[[0,1,0],[0,1,1]]],"passed":true},{"actual":[8,8,[[1,6,2],[3,2,9]]],"check":"combined fault 2","expected":[8,6,[[1,6,2],[3,2,9]]],"passed":false},{"actual":[2,2,[[0,7,4]]],"check":"control 3","expected":[2,2,[[0,7,4]]],"passed":true},{"actual":[2,2,[[0,3,6],[5,8,0],[5,5,1]]],"check":"control 4","expected":[2,2,[[0,3,6],[5,8,0],[5,5,1]]],"passed":true},{"actual":[1,1,[[7]]],"check":"boundary 5","expected":[1,1,[[7]]],"passed":true},{"actual":[1,1,[[0,1,1]]],"check":"boundary 6","expected":[1,1,[[0,1,1]]],"passed":true},{"actual":[6,6,[[0,0,0],[0,0,1]]],"check":"control 7","expected":[6,8,[[0,0,0],[0,0,1]]],"passed":false}],"passed":false,"stderr":"","stdout":"{\"observations\": [{\"check\": \"regression: restoring inverse tag 0\", \"actual\": [8, 8, [[2, 7, 9], [5, 9, 6]]], \"expected\": [8, 6, [[2, 7, 9], [5, 9, 6]]], \"passed\": false}, {\"check\": \"repair trap 1\", \"actual\": [5, 5, [[0, 1, 0], [0, 1, 1]]], \"expected\": [5, 5, [[0, 1, 0], [0, 1, 1]]], \"passed\": true}, {\"check\": \"combined fault 2\", \"actual\": [8, 8, [[1, 6, 2], [3, 2, 9]]], \"expected\": [8, 6, [[1, 6, 2], [3, 2, 9]]], \"passed\": false}, {\"check\": \"control 3\", \"actual\": [2, 2, [[0, 7, 4]]], \"expected\": [2, 2, [[0, 7, 4]]], \"passed\": true}, {\"check\": \"control 4\", \"actual\": [2, 2, [[0, 3, 6], [5, 8, 0], [5, 5, 1]]], \"expected\": [2, 2, [[0, 3, 6], [5, 8, 0], [5, 5, 1]]], \"passed\": true}, {\"check\": \"boundary 5\", \"actual\": [1, 1, [[7]]], \"expected\": [1, 1, [[7]]], \"passed\": true}, {\"check\": \"boundary 6\", \"actual\": [1, 1, [[0, 1, 1]]], \"expected\": [1, 1, [[0, 1, 1]]], \"passed\": true}, {\"check\": \"control 7\", \"actual\": [6, 6, [[0, 0, 0], [0, 0, 1]]], \"expected\": [6, 8, [[0, 0, 0], [0, 0, 1]]], \"passed\": false}], \"passed\": false}\n"}},"member_only":{"stages":["fixed"],"fields":["implementations.fixed","verification.fixed","harness","repair"],"note":"The verified repair, its recorded checks, the repair description, and the scoring harness are available to members."}}