FAILURE MAP
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FA-78891 / Image orientation metadata / Open access

Region clipping grows boxes that start outside the image · case 01

A face box partly above or left of the frame becomes larger after clipping.

Verified by executionVariant 1 · 8 checks per implementationDownload source bundle ↓JSON ↗

ROOT CAUSE

The origin is clamped to zero before the far edge is computed, so the far edge moves outward by the clipped amount.

VERIFIED REPAIR

Compute the far edges from the original origin, then clamp the origin.

Unsuccessful approach: Fixing the order only for x still grows boxes that start above the frame.

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
    x0 = max(x0, 0)
    y0 = max(y0, 0)
    x1 = min(x0 + bw, w)
    y1 = min(y0 + bh, h)
    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]], [([5, 4], 1, [-2, 2, 5, 5]), [0, 2, 3, 2]], [([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, 6], 6, [4, -1, 1, 4]), None], [([2, 4], 4, [-1, 5, 2, 4]), None], [([2, 4], 7, [1, -3, 3, 3]), None]], [[([6, 6], 4, [-3, 4, 2, 4]), None], [([2, 4], 7, [-3, -2, 2, 5]), None], [([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]], [([7, 3], 5, [0, -1, 2, 2]), [0, 0, 1, 2]]], [[([6, 1], 1, [-2, -3, 5, 3]), None], [([7, 4], 8, [-3, 1, 2, 2]), None], [([3, 7], 7, [-3, 2, 2, 3]), None], [([4, 5], 8, [2, -2, 0, 2]), None], [([6, 4], 6, [2, 1, 3, 4]), [0, 2, 3, 3]], [([1, 5], 9, [2, 3, 4, 4]), None], [([6, 1], 2, [2, 1, 3, 0]), None], [([6, 3], 8, [-2, -3, 4, 3]), None]], [[([7, 2], 8, [4, -2, 1, 2]), None], [([6, 2], 2, [-1, 1, 5, 5]), [2, 1, 4, 1]], [([4, 5], 8, [-1, -2, 1, 4]), None], [([3, 7], 7, [-1, 6, 2, 0]), None], [([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, 6], 2, [-2, 1, 1, 4]), None]], [[([1, 7], 6, [-3, -3, 2, 5]), None], [([2, 7], 8, [-2, 2, 2, 1]), None], [([5, 6], 7, [-2, 2, 3, 5]), [0, 4, 4, 1]], [([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], [([3, 2], 8, [-2, -1, 5, 1]), None]]]
labels = ["regression: clip before computing far edge", "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 fixtureActualExpectedOutcome
regression: clip before computing far edge 0[0, 0, 1, 5][0, 0, 1, 2]Failed
repair trap 1[0, 2, 5, 2][0, 2, 3, 2]Failed
combined fault 2NoneNonePassed
control 3NoneNonePassed
control 4NoneNonePassed
boundary 5NoneNonePassed
boundary 6NoneNonePassed
control 7[1, 0, 3, 1]NoneFailed

SHA-256 / 823de6b7236d4c5b74ce2d86d5e476cf2f158a1c5055f284cab5e1753453ece9

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
    x0 = max(x0, 0)
    x1 = min(x0 + bw, w)
    y1 = min(y0 + bh, h)
    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]], [([5, 4], 1, [-2, 2, 5, 5]), [0, 2, 3, 2]], [([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, 6], 6, [4, -1, 1, 4]), None], [([2, 4], 4, [-1, 5, 2, 4]), None], [([2, 4], 7, [1, -3, 3, 3]), None]], [[([6, 6], 4, [-3, 4, 2, 4]), None], [([2, 4], 7, [-3, -2, 2, 5]), None], [([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]], [([7, 3], 5, [0, -1, 2, 2]), [0, 0, 1, 2]]], [[([6, 1], 1, [-2, -3, 5, 3]), None], [([7, 4], 8, [-3, 1, 2, 2]), None], [([3, 7], 7, [-3, 2, 2, 3]), None], [([4, 5], 8, [2, -2, 0, 2]), None], [([6, 4], 6, [2, 1, 3, 4]), [0, 2, 3, 3]], [([1, 5], 9, [2, 3, 4, 4]), None], [([6, 1], 2, [2, 1, 3, 0]), None], [([6, 3], 8, [-2, -3, 4, 3]), None]], [[([7, 2], 8, [4, -2, 1, 2]), None], [([6, 2], 2, [-1, 1, 5, 5]), [2, 1, 4, 1]], [([4, 5], 8, [-1, -2, 1, 4]), None], [([3, 7], 7, [-1, 6, 2, 0]), None], [([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, 6], 2, [-2, 1, 1, 4]), None]], [[([1, 7], 6, [-3, -3, 2, 5]), None], [([2, 7], 8, [-2, 2, 2, 1]), None], [([5, 6], 7, [-2, 2, 3, 5]), [0, 4, 4, 1]], [([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], [([3, 2], 8, [-2, -1, 5, 1]), None]]]
labels = ["regression: clip before computing far edge", "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 fixtureActualExpectedOutcome
regression: clip before computing far edge 0[0, 0, 1, 5][0, 0, 1, 2]Failed
repair trap 1[0, 2, 5, 2][0, 2, 3, 2]Failed
combined fault 2NoneNonePassed
control 3NoneNonePassed
control 4NoneNonePassed
boundary 5NoneNonePassed
boundary 6NoneNonePassed
control 7NoneNonePassed

SHA-256 / fcc3b70cdfed5b756538ba1ad65fc1cb185cabc79f57f2c33d835c7a1ccc9072

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]], [([5, 4], 1, [-2, 2, 5, 5]), [0, 2, 3, 2]], [([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, 6], 6, [4, -1, 1, 4]), None], [([2, 4], 4, [-1, 5, 2, 4]), None], [([2, 4], 7, [1, -3, 3, 3]), None]], [[([6, 6], 4, [-3, 4, 2, 4]), None], [([2, 4], 7, [-3, -2, 2, 5]), None], [([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]], [([7, 3], 5, [0, -1, 2, 2]), [0, 0, 1, 2]]], [[([6, 1], 1, [-2, -3, 5, 3]), None], [([7, 4], 8, [-3, 1, 2, 2]), None], [([3, 7], 7, [-3, 2, 2, 3]), None], [([4, 5], 8, [2, -2, 0, 2]), None], [([6, 4], 6, [2, 1, 3, 4]), [0, 2, 3, 3]], [([1, 5], 9, [2, 3, 4, 4]), None], [([6, 1], 2, [2, 1, 3, 0]), None], [([6, 3], 8, [-2, -3, 4, 3]), None]], [[([7, 2], 8, [4, -2, 1, 2]), None], [([6, 2], 2, [-1, 1, 5, 5]), [2, 1, 4, 1]], [([4, 5], 8, [-1, -2, 1, 4]), None], [([3, 7], 7, [-1, 6, 2, 0]), None], [([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, 6], 2, [-2, 1, 1, 4]), None]], [[([1, 7], 6, [-3, -3, 2, 5]), None], [([2, 7], 8, [-2, 2, 2, 1]), None], [([5, 6], 7, [-2, 2, 3, 5]), [0, 4, 4, 1]], [([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], [([3, 2], 8, [-2, -1, 5, 1]), None]]]
labels = ["regression: clip before computing far edge", "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 fixtureActualExpectedOutcome
regression: clip before computing far edge 0[0, 0, 1, 2][0, 0, 1, 2]Passed
repair trap 1[0, 2, 3, 2][0, 2, 3, 2]Passed
combined fault 2NoneNonePassed
control 3NoneNonePassed
control 4NoneNonePassed
boundary 5NoneNonePassed
boundary 6NoneNonePassed
control 7NoneNonePassed

SHA-256 / 6b41d691a0880b1fb361b56e2710bcd6577810a14f3e89b2b2fa292ab9699923

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 2026-09-29T14:49:39.326265+00:00.

Case digest / ec586863414c8c86375284e26e9b490ca8a2f9fe65445468d0ffe7fc684bd7ff