{"abstract":"Portrait thumbnails come back with landscape dimensions for rotated photos.","category":"Image orientation metadata","checks":8,"contract":"Input [stored_w, stored_h, tag, box_w, box_h]. Compute the displayed thumbnail size: tags 5..8 swap the displayed dimensions (other values, including invalid tags, do not). Scale = min(box_w/dw, box_h/dh, 1) exactly (never upscale); each side is rounded half up and is at least 1 pixel.","evaluation_group":"w2-image-orientation-metadata-thumbnail-fit","failed_approach":"Swapping both the image and the box fits the displayed image into the wrong box.","family":"w2-image-orientation-metadata-thumbnail-fit-rotated-box","id":"FA-78971","implementations":{"attempt":{"sha256":"ef00e4d0c3debd053d5844f54034e44805c66164f7901395956c63f0eca55f13","source":"\"\"\"Failure Map reference implementation. Python standard library only.\"\"\"\nimport json\nimport math\nfrom fractions import Fraction\nN = 1\nobservations = []\ndef solve(x):\n    w, h, tag, bw, bh = x\n    if tag in (5, 6, 7, 8):\n        w, h = h, w\n        bw, bh = bh, bw\n    s = min(Fraction(bw, w), Fraction(bh, h), Fraction(1))\n    tw = max(1, math.floor(w * s + Fraction(1, 2)))\n    th = max(1, math.floor(h * s + Fraction(1, 2)))\n    return [tw, th]\ndef check(label, actual, expected):\n    observations.append({\"check\": label, \"actual\": actual, \"expected\": expected, \"passed\": actual == expected})\nfixtures = [[[[25, 2, 6, 76, 343], [2, 25]], [[5, 1, 8, 10, 2], [1, 2]], [[15, 7, 6, 165, 2], [1, 2]], [[5, 2, 2, 10, 2], [5, 2]], [[3, 2, 3, 2, 33], [2, 1]], [[58, 7, 2, 2, 277], [2, 1]], [[15, 7, 1, 2, 10], [2, 1]], [[3, 1, 6, 10, 10], [1, 3]]], [[[17, 50, 7, 72, 27], [50, 17]], [[15, 35, 6, 31, 10], [23, 10]], [[5, 2, 1, 19, 25], [5, 2]], [[25, 7, 2, 2, 145], [2, 1]], [[15, 2, 0, 2, 2], [2, 1]], [[5, 4382, 0, 2, 337], [1, 337]], [[3, 7, 4, 2, 6], [2, 5]], [[4728, 23, 5, 14, 18], [1, 18]]], [[[15, 1, 8, 10, 42], [1, 15]], [[5, 34, 6, 2, 10], [2, 1]], [[12, 1369, 3, 1, 30], [1, 30]], [[15, 1, 1, 11, 291], [11, 1]], [[2, 1, 3, 2, 2], [2, 1]], [[15, 1, 3, 2, 10], [2, 1]], [[1669, 12, 4, 2, 2], [2, 1]], [[25, 7, 7, 10, 345], [7, 25]]], [[[5, 2, 8, 2, 10], [2, 5]], [[25, 1, 6, 10, 150], [1, 25]], [[5, 22, 5, 2, 17], [2, 1]], [[3, 5, 2, 2, 22], [2, 3]], [[1584, 7, 0, 266, 9], [266, 1]], [[51, 2, 3, 26, 45], [26, 1]], [[378, 2, 1, 2, 294], [2, 1]], [[1283, 2, 6, 10, 2], [1, 2]]], [[[2114, 2, 8, 15, 246], [1, 246]], [[25, 2, 6, 10, 2], [1, 2]], [[35, 33, 6, 10, 382], [10, 11]], [[3903, 7, 9, 364, 10], [364, 1]], [[25, 2, 4, 54, 2], [25, 2]], [[3018, 47, 4, 2, 10], [2, 1]], [[15, 1, 2, 14, 14], [14, 1]], [[3907, 2, 8, 28, 202], [1, 202]]]]\nlabels = [\"regression: rotated image versus rotated box\", \"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":"83b850ab76a184eafdf122402fb387ee9fb26d9b36a8d6e027f3f547cc3ad6ed","source":"\"\"\"Failure Map reference implementation. Python standard library only.\"\"\"\nimport json\nimport math\nfrom fractions import Fraction\nN = 1\nobservations = []\ndef solve(x):\n    w, h, tag, bw, bh = x\n    if tag in (5, 6, 7, 8):\n        bw, bh = bh, bw\n    s = min(Fraction(bw, w), Fraction(bh, h), Fraction(1))\n    tw = max(1, math.floor(w * s + Fraction(1, 2)))\n    th = max(1, math.floor(h * s + Fraction(1, 2)))\n    return [tw, th]\ndef check(label, actual, expected):\n    observations.append({\"check\": label, \"actual\": actual, \"expected\": expected, \"passed\": actual == expected})\nfixtures = [[[[25, 2, 6, 76, 343], [2, 25]], [[5, 1, 8, 10, 2], [1, 2]], [[15, 7, 6, 165, 2], [1, 2]], [[5, 2, 2, 10, 2], [5, 2]], [[3, 2, 3, 2, 33], [2, 1]], [[58, 7, 2, 2, 277], [2, 1]], [[15, 7, 1, 2, 10], [2, 1]], [[3, 1, 6, 10, 10], [1, 3]]], [[[17, 50, 7, 72, 27], [50, 17]], [[15, 35, 6, 31, 10], [23, 10]], [[5, 2, 1, 19, 25], [5, 2]], [[25, 7, 2, 2, 145], [2, 1]], [[15, 2, 0, 2, 2], [2, 1]], [[5, 4382, 0, 2, 337], [1, 337]], [[3, 7, 4, 2, 6], [2, 5]], [[4728, 23, 5, 14, 18], [1, 18]]], [[[15, 1, 8, 10, 42], [1, 15]], [[5, 34, 6, 2, 10], [2, 1]], [[12, 1369, 3, 1, 30], [1, 30]], [[15, 1, 1, 11, 291], [11, 1]], [[2, 1, 3, 2, 2], [2, 1]], [[15, 1, 3, 2, 10], [2, 1]], [[1669, 12, 4, 2, 2], [2, 1]], [[25, 7, 7, 10, 345], [7, 25]]], [[[5, 2, 8, 2, 10], [2, 5]], [[25, 1, 6, 10, 150], [1, 25]], [[5, 22, 5, 2, 17], [2, 1]], [[3, 5, 2, 2, 22], [2, 3]], [[1584, 7, 0, 266, 9], [266, 1]], [[51, 2, 3, 26, 45], [26, 1]], [[378, 2, 1, 2, 294], [2, 1]], [[1283, 2, 6, 10, 2], [1, 2]]], [[[2114, 2, 8, 15, 246], [1, 246]], [[25, 2, 6, 10, 2], [1, 2]], [[35, 33, 6, 10, 382], [10, 11]], [[3903, 7, 9, 364, 10], [364, 1]], [[25, 2, 4, 54, 2], [25, 2]], [[3018, 47, 4, 2, 10], [2, 1]], [[15, 1, 2, 14, 14], [14, 1]], [[3907, 2, 8, 28, 202], [1, 202]]]]\nlabels = [\"regression: rotated image versus rotated box\", \"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"},"fixed":{"sha256":"04ad3560b26b7ab62f82d0e7d177e8fe03e67b4779c8cc58027360e64736c431","source":"\"\"\"Failure Map reference implementation. Python standard library only.\"\"\"\nimport json\nimport math\nfrom fractions import Fraction\nN = 1\nobservations = []\ndef solve(x):\n    w, h, tag, bw, bh = x\n    if tag in (5, 6, 7, 8):\n        w, h = h, w\n    s = min(Fraction(bw, w), Fraction(bh, h), Fraction(1))\n    tw = max(1, math.floor(w * s + Fraction(1, 2)))\n    th = max(1, math.floor(h * s + Fraction(1, 2)))\n    return [tw, th]\ndef check(label, actual, expected):\n    observations.append({\"check\": label, \"actual\": actual, \"expected\": expected, \"passed\": actual == expected})\nfixtures = [[[[25, 2, 6, 76, 343], [2, 25]], [[5, 1, 8, 10, 2], [1, 2]], [[15, 7, 6, 165, 2], [1, 2]], [[5, 2, 2, 10, 2], [5, 2]], [[3, 2, 3, 2, 33], [2, 1]], [[58, 7, 2, 2, 277], [2, 1]], [[15, 7, 1, 2, 10], [2, 1]], [[3, 1, 6, 10, 10], [1, 3]]], [[[17, 50, 7, 72, 27], [50, 17]], [[15, 35, 6, 31, 10], [23, 10]], [[5, 2, 1, 19, 25], [5, 2]], [[25, 7, 2, 2, 145], [2, 1]], [[15, 2, 0, 2, 2], [2, 1]], [[5, 4382, 0, 2, 337], [1, 337]], [[3, 7, 4, 2, 6], [2, 5]], [[4728, 23, 5, 14, 18], [1, 18]]], [[[15, 1, 8, 10, 42], [1, 15]], [[5, 34, 6, 2, 10], [2, 1]], [[12, 1369, 3, 1, 30], [1, 30]], [[15, 1, 1, 11, 291], [11, 1]], [[2, 1, 3, 2, 2], [2, 1]], [[15, 1, 3, 2, 10], [2, 1]], [[1669, 12, 4, 2, 2], [2, 1]], [[25, 7, 7, 10, 345], [7, 25]]], [[[5, 2, 8, 2, 10], [2, 5]], [[25, 1, 6, 10, 150], [1, 25]], [[5, 22, 5, 2, 17], [2, 1]], [[3, 5, 2, 2, 22], [2, 3]], [[1584, 7, 0, 266, 9], [266, 1]], [[51, 2, 3, 26, 45], [26, 1]], [[378, 2, 1, 2, 294], [2, 1]], [[1283, 2, 6, 10, 2], [1, 2]]], [[[2114, 2, 8, 15, 246], [1, 246]], [[25, 2, 6, 10, 2], [1, 2]], [[35, 33, 6, 10, 382], [10, 11]], [[3903, 7, 9, 364, 10], [364, 1]], [[25, 2, 4, 54, 2], [25, 2]], [[3018, 47, 4, 2, 10], [2, 1]], [[15, 1, 2, 14, 14], [14, 1]], [[3907, 2, 8, 28, 202], [1, 202]]]]\nlabels = [\"regression: rotated image versus rotated box\", \"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-thumbnail-fit-rotated-box","generated_at":"2026-09-29T14:49:40.266871+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.","repair":"Swap the image dimensions into display orientation and fit them into the unmodified box.","root_cause":"For tags 5..8 the box dimensions are exchanged instead of the image dimensions, so the result is in stored orientation.","sha256":"2fb5a551b6e7b4c081a5e01260680b3f1c72904954ed5f718284d5d272cb14b2","title":"Thumbnailer rotates the bounding box instead of the image · case 01","variant":1,"variant_policy":"Five numbered records share a model and may reuse boundary fixtures.","verification":{"attempt":{"elapsed_ms":40.672,"exit_code":1,"observations":[{"actual":[2,25],"check":"regression: rotated image versus rotated box 0","expected":[2,25],"passed":true},{"actual":[1,5],"check":"repair trap 1","expected":[1,2],"passed":false},{"actual":[2,4],"check":"combined fault 2","expected":[1,2],"passed":false},{"actual":[5,2],"check":"control 3","expected":[5,2],"passed":true},{"actual":[2,1],"check":"control 4","expected":[2,1],"passed":true},{"actual":[2,1],"check":"boundary 5","expected":[2,1],"passed":true},{"actual":[2,1],"check":"boundary 6","expected":[2,1],"passed":true},{"actual":[1,3],"check":"control 7","expected":[1,3],"passed":true}],"passed":false,"stderr":"","stdout":"{\"observations\": [{\"check\": \"regression: rotated image versus rotated box 0\", \"actual\": [2, 25], \"expected\": [2, 25], \"passed\": true}, {\"check\": \"repair trap 1\", \"actual\": [1, 5], \"expected\": [1, 2], \"passed\": false}, {\"check\": \"combined fault 2\", \"actual\": [2, 4], \"expected\": [1, 2], \"passed\": false}, {\"check\": \"control 3\", \"actual\": [5, 2], \"expected\": [5, 2], \"passed\": true}, {\"check\": \"control 4\", \"actual\": [2, 1], \"expected\": [2, 1], \"passed\": true}, {\"check\": \"boundary 5\", \"actual\": [2, 1], \"expected\": [2, 1], \"passed\": true}, {\"check\": \"boundary 6\", \"actual\": [2, 1], \"expected\": [2, 1], \"passed\": true}, {\"check\": \"control 7\", \"actual\": [1, 3], \"expected\": [1, 3], \"passed\": true}], \"passed\": false}\n"},"broken":{"elapsed_ms":42.585,"exit_code":1,"observations":[{"actual":[25,2],"check":"regression: rotated image versus rotated box 0","expected":[2,25],"passed":false},{"actual":[2,1],"check":"repair trap 1","expected":[1,2],"passed":false},{"actual":[2,1],"check":"combined fault 2","expected":[1,2],"passed":false},{"actual":[5,2],"check":"control 3","expected":[5,2],"passed":true},{"actual":[2,1],"check":"control 4","expected":[2,1],"passed":true},{"actual":[2,1],"check":"boundary 5","expected":[2,1],"passed":true},{"actual":[2,1],"check":"boundary 6","expected":[2,1],"passed":true},{"actual":[3,1],"check":"control 7","expected":[1,3],"passed":false}],"passed":false,"stderr":"","stdout":"{\"observations\": [{\"check\": \"regression: rotated image versus rotated box 0\", \"actual\": [25, 2], \"expected\": [2, 25], \"passed\": false}, {\"check\": \"repair trap 1\", \"actual\": [2, 1], \"expected\": [1, 2], \"passed\": false}, {\"check\": \"combined fault 2\", \"actual\": [2, 1], \"expected\": [1, 2], \"passed\": false}, {\"check\": \"control 3\", \"actual\": [5, 2], \"expected\": [5, 2], \"passed\": true}, {\"check\": \"control 4\", \"actual\": [2, 1], \"expected\": [2, 1], \"passed\": true}, {\"check\": \"boundary 5\", \"actual\": [2, 1], \"expected\": [2, 1], \"passed\": true}, {\"check\": \"boundary 6\", \"actual\": [2, 1], \"expected\": [2, 1], \"passed\": true}, {\"check\": \"control 7\", \"actual\": [3, 1], \"expected\": [1, 3], \"passed\": false}], \"passed\": false}\n"},"fixed":{"elapsed_ms":42.543,"exit_code":0,"observations":[{"actual":[2,25],"check":"regression: rotated image versus rotated box 0","expected":[2,25],"passed":true},{"actual":[1,2],"check":"repair trap 1","expected":[1,2],"passed":true},{"actual":[1,2],"check":"combined fault 2","expected":[1,2],"passed":true},{"actual":[5,2],"check":"control 3","expected":[5,2],"passed":true},{"actual":[2,1],"check":"control 4","expected":[2,1],"passed":true},{"actual":[2,1],"check":"boundary 5","expected":[2,1],"passed":true},{"actual":[2,1],"check":"boundary 6","expected":[2,1],"passed":true},{"actual":[1,3],"check":"control 7","expected":[1,3],"passed":true}],"passed":true,"stderr":"","stdout":"{\"observations\": [{\"check\": \"regression: rotated image versus rotated box 0\", \"actual\": [2, 25], \"expected\": [2, 25], \"passed\": true}, {\"check\": \"repair trap 1\", \"actual\": [1, 2], \"expected\": [1, 2], \"passed\": true}, {\"check\": \"combined fault 2\", \"actual\": [1, 2], \"expected\": [1, 2], \"passed\": true}, {\"check\": \"control 3\", \"actual\": [5, 2], \"expected\": [5, 2], \"passed\": true}, {\"check\": \"control 4\", \"actual\": [2, 1], \"expected\": [2, 1], \"passed\": true}, {\"check\": \"boundary 5\", \"actual\": [2, 1], \"expected\": [2, 1], \"passed\": true}, {\"check\": \"boundary 6\", \"actual\": [2, 1], \"expected\": [2, 1], \"passed\": true}, {\"check\": \"control 7\", \"actual\": [1, 3], \"expected\": [1, 3], \"passed\": true}], \"passed\": true}\n"}},"verified":true,"visibility":"public"}