FA-78886 / Image orientation metadata / Open access
Region mapping transposes before applying stored-space flips · case 01
Boxes on rotated photos are mirrored or pushed outside the displayed frame.
ROOT CAUSE
The decomposition table describes flips in stored space followed by a transpose, but the code transposes first and then flips with stored extents.
VERIFIED REPAIR
Apply the stored-space flips first, then exchange the axes.
Unsuccessful approach: Swapping the extents after an early transpose flips in display space, which turns tag 6 into tag 8 and vice versa.
Case contract
Map a half-open face/crop region [x, y, width, height] given in stored pixel space of an image of size [w, h] into displayed space for orientation tag 1..8. The region is first clipped to the stored image; an empty clipped region returns None, and an unknown tag returns None. Mirroring a half-open interval [a, b) over extent e gives [e-b, e-a); tags 5..8 exchange axes after the flips.
Why this case matters
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.
1 / The failure
Exit 1"""Failure Map reference implementation. Python standard library only."""
import json
N = 1
observations = []
def solve(size, tag, box):
w, h = size
x0, y0, bw, bh = box
x1 = min(x0 + bw, w)
y1 = min(y0 + bh, h)
x0 = max(x0, 0)
y0 = max(y0, 0)
if x1 <= x0 or y1 <= y0:
return None
table = {1: (0, 0, 0), 2: (1, 0, 0), 3: (1, 1, 0), 4: (0, 1, 0), 5: (0, 0, 1), 6: (0, 1, 1), 7: (1, 1, 1), 8: (1, 0, 1)}
if tag not in table:
return None
fx, fy, tr = table[tag]
if tr:
x0, y0, x1, y1 = y0, x0, y1, x1
if fx:
x0, x1 = w - x1, w - x0
if fy:
y0, y1 = h - y1, h - y0
return [x0, y0, x1 - x0, y1 - y0]
def check(label, actual, expected):
observations.append({"check": label, "actual": actual, "expected": expected, "passed": actual == expected})
fixtures = [[[([5, 1], 6, [-3, -2, 5, 4]), [0, 0, 1, 2]], [([3, 3], 6, [-1, 0, 2, 1]), [2, 0, 1, 1]], [([7, 5], 1, [6, -1, 4, 0]), None], [([3, 4], 3, [-2, 3, 0, 2]), None], [([2, 4], 8, [2, 1, 3, 3]), None], [([2, 4], 7, [1, -3, 3, 3]), None], [([2, 6], 6, [4, -1, 1, 4]), None], [([5, 6], 8, [-2, 0, 4, 1]), [0, 3, 1, 2]]], [[([3, 5], 8, [0, 4, 2, 2]), [4, 1, 1, 2]], [([4, 1], 8, [2, -3, 3, 5]), [0, 0, 1, 2]], [([3, 5], 0, [-3, -2, 2, 4]), None], [([3, 1], 1, [2, 2, 2, 0]), None], [([4, 1], 3, [6, 3, 2, 4]), None], [([5, 5], 6, [6, 3, 5, 0]), None], [([4, 5], 1, [1, 2, 5, 4]), [1, 2, 3, 3]], [([4, 7], 6, [2, 6, 5, 3]), [0, 2, 1, 2]]], [[([5, 2], 8, [1, 1, 5, 1]), [1, 0, 1, 4]], [([6, 4], 6, [-2, 1, 5, 5]), [0, 0, 3, 3]], [([4, 5], 8, [2, -2, 0, 2]), None], [([1, 5], 9, [2, 3, 4, 4]), None], [([6, 1], 2, [2, 1, 3, 0]), None], [([1, 2], 9, [-2, 1, 1, 3]), None], [([5, 1], 8, [5, 0, 5, 0]), None], [([6, 4], 6, [2, 1, 3, 4]), [0, 2, 3, 3]]], [[([4, 6], 7, [2, 4, 1, 5]), [0, 1, 2, 1]], [([6, 3], 8, [3, 2, 2, 5]), [2, 1, 1, 2]], [([4, 3], 6, [-2, 2, 5, 1]), [0, 0, 1, 3]], [([3, 6], 8, [6, -2, 2, 3]), None], [([7, 7], 2, [-2, 0, 0, 4]), None], [([2, 5], 1, [1, 6, 5, 2]), None], [([5, 5], 1, [6, 1, 5, 4]), None], [([7, 5], 8, [0, 4, 5, 5]), [4, 2, 1, 5]]], [[([7, 3], 6, [4, -2, 1, 3]), [2, 4, 1, 1]], [([1, 4], 6, [0, 2, 4, 1]), [1, 0, 1, 1]], [([7, 4], 6, [2, 1, 5, 2]), [1, 2, 2, 5]], [([1, 1], 7, [1, -3, 2, 0]), None], [([4, 5], 6, [1, 3, 0, 5]), None], [([4, 1], 0, [2, 4, 5, 5]), None], [([6, 7], 7, [6, 0, 3, 1]), None], [([7, 1], 7, [0, -2, 5, 4]), [0, 2, 1, 5]]]]
labels = ["regression: transpose before flips", "repair trap", "combined fault", "control", "control", "boundary", "boundary", "control"]
for i, (args, expected) in enumerate(fixtures[N-1]):
check("%s %d" % (labels[i % len(labels)], i), solve(*args), expected)
print(json.dumps({"observations": observations, "passed": all(x["passed"] for x in observations)}, ensure_ascii=False))
raise SystemExit(0 if all(x["passed"] for x in observations) else 1)
| Boundary fixture | Actual | Expected | Outcome |
|---|---|---|---|
| regression: transpose before flips 0 | [0, -1, 1, 2] | [0, 0, 1, 2] | Failed |
| repair trap 1 | [0, 2, 1, 1] | [2, 0, 1, 1] | Failed |
| combined fault 2 | None | None | Passed |
| control 3 | None | None | Passed |
| control 4 | None | None | Passed |
| boundary 5 | None | None | Passed |
| boundary 6 | None | None | Passed |
| control 7 | [4, 0, 1, 2] | [0, 3, 1, 2] | Failed |
SHA-256 / 426493423471c8897edfde7070b35adb74c85e7fde4a1382de7bdf9d733256d1
2 / The unsuccessful fix
Exit 1"""Failure Map reference implementation. Python standard library only."""
import json
N = 1
observations = []
def solve(size, tag, box):
w, h = size
x0, y0, bw, bh = box
x1 = min(x0 + bw, w)
y1 = min(y0 + bh, h)
x0 = max(x0, 0)
y0 = max(y0, 0)
if x1 <= x0 or y1 <= y0:
return None
table = {1: (0, 0, 0), 2: (1, 0, 0), 3: (1, 1, 0), 4: (0, 1, 0), 5: (0, 0, 1), 6: (0, 1, 1), 7: (1, 1, 1), 8: (1, 0, 1)}
if tag not in table:
return None
fx, fy, tr = table[tag]
if tr:
x0, y0, x1, y1 = y0, x0, y1, x1
w, h = h, w
if fx:
x0, x1 = w - x1, w - x0
if fy:
y0, y1 = h - y1, h - y0
return [x0, y0, x1 - x0, y1 - y0]
def check(label, actual, expected):
observations.append({"check": label, "actual": actual, "expected": expected, "passed": actual == expected})
fixtures = [[[([5, 1], 6, [-3, -2, 5, 4]), [0, 0, 1, 2]], [([3, 3], 6, [-1, 0, 2, 1]), [2, 0, 1, 1]], [([7, 5], 1, [6, -1, 4, 0]), None], [([3, 4], 3, [-2, 3, 0, 2]), None], [([2, 4], 8, [2, 1, 3, 3]), None], [([2, 4], 7, [1, -3, 3, 3]), None], [([2, 6], 6, [4, -1, 1, 4]), None], [([5, 6], 8, [-2, 0, 4, 1]), [0, 3, 1, 2]]], [[([3, 5], 8, [0, 4, 2, 2]), [4, 1, 1, 2]], [([4, 1], 8, [2, -3, 3, 5]), [0, 0, 1, 2]], [([3, 5], 0, [-3, -2, 2, 4]), None], [([3, 1], 1, [2, 2, 2, 0]), None], [([4, 1], 3, [6, 3, 2, 4]), None], [([5, 5], 6, [6, 3, 5, 0]), None], [([4, 5], 1, [1, 2, 5, 4]), [1, 2, 3, 3]], [([4, 7], 6, [2, 6, 5, 3]), [0, 2, 1, 2]]], [[([5, 2], 8, [1, 1, 5, 1]), [1, 0, 1, 4]], [([6, 4], 6, [-2, 1, 5, 5]), [0, 0, 3, 3]], [([4, 5], 8, [2, -2, 0, 2]), None], [([1, 5], 9, [2, 3, 4, 4]), None], [([6, 1], 2, [2, 1, 3, 0]), None], [([1, 2], 9, [-2, 1, 1, 3]), None], [([5, 1], 8, [5, 0, 5, 0]), None], [([6, 4], 6, [2, 1, 3, 4]), [0, 2, 3, 3]]], [[([4, 6], 7, [2, 4, 1, 5]), [0, 1, 2, 1]], [([6, 3], 8, [3, 2, 2, 5]), [2, 1, 1, 2]], [([4, 3], 6, [-2, 2, 5, 1]), [0, 0, 1, 3]], [([3, 6], 8, [6, -2, 2, 3]), None], [([7, 7], 2, [-2, 0, 0, 4]), None], [([2, 5], 1, [1, 6, 5, 2]), None], [([5, 5], 1, [6, 1, 5, 4]), None], [([7, 5], 8, [0, 4, 5, 5]), [4, 2, 1, 5]]], [[([7, 3], 6, [4, -2, 1, 3]), [2, 4, 1, 1]], [([1, 4], 6, [0, 2, 4, 1]), [1, 0, 1, 1]], [([7, 4], 6, [2, 1, 5, 2]), [1, 2, 2, 5]], [([1, 1], 7, [1, -3, 2, 0]), None], [([4, 5], 6, [1, 3, 0, 5]), None], [([4, 1], 0, [2, 4, 5, 5]), None], [([6, 7], 7, [6, 0, 3, 1]), None], [([7, 1], 7, [0, -2, 5, 4]), [0, 2, 1, 5]]]]
labels = ["regression: transpose before flips", "repair trap", "combined fault", "control", "control", "boundary", "boundary", "control"]
for i, (args, expected) in enumerate(fixtures[N-1]):
check("%s %d" % (labels[i % len(labels)], i), solve(*args), expected)
print(json.dumps({"observations": observations, "passed": all(x["passed"] for x in observations)}, ensure_ascii=False))
raise SystemExit(0 if all(x["passed"] for x in observations) else 1)
| Boundary fixture | Actual | Expected | Outcome |
|---|---|---|---|
| regression: transpose before flips 0 | [0, 3, 1, 2] | [0, 0, 1, 2] | Failed |
| repair trap 1 | [0, 2, 1, 1] | [2, 0, 1, 1] | Failed |
| combined fault 2 | None | None | Passed |
| control 3 | None | None | Passed |
| control 4 | None | None | Passed |
| boundary 5 | None | None | Passed |
| boundary 6 | None | None | Passed |
| control 7 | [5, 0, 1, 2] | [0, 3, 1, 2] | Failed |
SHA-256 / b5e558e8f49e053455c8dd2a844ab608b5f47d129285366fff96349fcdc9308c
3 / The verified repair
Exit 0"""Failure Map reference implementation. Python standard library only."""
import json
N = 1
observations = []
def solve(size, tag, box):
w, h = size
x0, y0, bw, bh = box
x1 = min(x0 + bw, w)
y1 = min(y0 + bh, h)
x0 = max(x0, 0)
y0 = max(y0, 0)
if x1 <= x0 or y1 <= y0:
return None
table = {1: (0, 0, 0), 2: (1, 0, 0), 3: (1, 1, 0), 4: (0, 1, 0), 5: (0, 0, 1), 6: (0, 1, 1), 7: (1, 1, 1), 8: (1, 0, 1)}
if tag not in table:
return None
fx, fy, tr = table[tag]
if fx:
x0, x1 = w - x1, w - x0
if fy:
y0, y1 = h - y1, h - y0
if tr:
x0, y0, x1, y1 = y0, x0, y1, x1
return [x0, y0, x1 - x0, y1 - y0]
def check(label, actual, expected):
observations.append({"check": label, "actual": actual, "expected": expected, "passed": actual == expected})
fixtures = [[[([5, 1], 6, [-3, -2, 5, 4]), [0, 0, 1, 2]], [([3, 3], 6, [-1, 0, 2, 1]), [2, 0, 1, 1]], [([7, 5], 1, [6, -1, 4, 0]), None], [([3, 4], 3, [-2, 3, 0, 2]), None], [([2, 4], 8, [2, 1, 3, 3]), None], [([2, 4], 7, [1, -3, 3, 3]), None], [([2, 6], 6, [4, -1, 1, 4]), None], [([5, 6], 8, [-2, 0, 4, 1]), [0, 3, 1, 2]]], [[([3, 5], 8, [0, 4, 2, 2]), [4, 1, 1, 2]], [([4, 1], 8, [2, -3, 3, 5]), [0, 0, 1, 2]], [([3, 5], 0, [-3, -2, 2, 4]), None], [([3, 1], 1, [2, 2, 2, 0]), None], [([4, 1], 3, [6, 3, 2, 4]), None], [([5, 5], 6, [6, 3, 5, 0]), None], [([4, 5], 1, [1, 2, 5, 4]), [1, 2, 3, 3]], [([4, 7], 6, [2, 6, 5, 3]), [0, 2, 1, 2]]], [[([5, 2], 8, [1, 1, 5, 1]), [1, 0, 1, 4]], [([6, 4], 6, [-2, 1, 5, 5]), [0, 0, 3, 3]], [([4, 5], 8, [2, -2, 0, 2]), None], [([1, 5], 9, [2, 3, 4, 4]), None], [([6, 1], 2, [2, 1, 3, 0]), None], [([1, 2], 9, [-2, 1, 1, 3]), None], [([5, 1], 8, [5, 0, 5, 0]), None], [([6, 4], 6, [2, 1, 3, 4]), [0, 2, 3, 3]]], [[([4, 6], 7, [2, 4, 1, 5]), [0, 1, 2, 1]], [([6, 3], 8, [3, 2, 2, 5]), [2, 1, 1, 2]], [([4, 3], 6, [-2, 2, 5, 1]), [0, 0, 1, 3]], [([3, 6], 8, [6, -2, 2, 3]), None], [([7, 7], 2, [-2, 0, 0, 4]), None], [([2, 5], 1, [1, 6, 5, 2]), None], [([5, 5], 1, [6, 1, 5, 4]), None], [([7, 5], 8, [0, 4, 5, 5]), [4, 2, 1, 5]]], [[([7, 3], 6, [4, -2, 1, 3]), [2, 4, 1, 1]], [([1, 4], 6, [0, 2, 4, 1]), [1, 0, 1, 1]], [([7, 4], 6, [2, 1, 5, 2]), [1, 2, 2, 5]], [([1, 1], 7, [1, -3, 2, 0]), None], [([4, 5], 6, [1, 3, 0, 5]), None], [([4, 1], 0, [2, 4, 5, 5]), None], [([6, 7], 7, [6, 0, 3, 1]), None], [([7, 1], 7, [0, -2, 5, 4]), [0, 2, 1, 5]]]]
labels = ["regression: transpose before flips", "repair trap", "combined fault", "control", "control", "boundary", "boundary", "control"]
for i, (args, expected) in enumerate(fixtures[N-1]):
check("%s %d" % (labels[i % len(labels)], i), solve(*args), expected)
print(json.dumps({"observations": observations, "passed": all(x["passed"] for x in observations)}, ensure_ascii=False))
raise SystemExit(0 if all(x["passed"] for x in observations) else 1)
| Boundary fixture | Actual | Expected | Outcome |
|---|---|---|---|
| regression: transpose before flips 0 | [0, 0, 1, 2] | [0, 0, 1, 2] | Passed |
| repair trap 1 | [2, 0, 1, 1] | [2, 0, 1, 1] | Passed |
| combined fault 2 | None | None | Passed |
| control 3 | None | None | Passed |
| control 4 | None | None | Passed |
| boundary 5 | None | None | Passed |
| boundary 6 | None | None | Passed |
| control 7 | [0, 3, 1, 2] | [0, 3, 1, 2] | Passed |
SHA-256 / 7063ecdb0c11892b7fa63801389b931f33e33de7ffc43399b9ba1e77e2e0c77c
Verification & scope
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.
Observations recorded using Python 3.12.14 at 2026-09-29T14:49:39.292219+00:00.
Case digest / 4d3e9cc9332cd1d253f52665d26bb2ed801e5d40aaf86491220443159375b5e4