FAILURE MAP
← Case archive

FA-79261 / Image orientation metadata / Open access

Tap mapping applies the forward tag-6 rotation instead of its inverse · case 01

Tap-to-focus on portrait photos selects a point mirrored across the diagonal.

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

ROOT CAUSE

The display-to-stored conversion reuses the stored-to-display formula for tag 6.

VERIFIED REPAIR

Invert the clockwise rotation: x = display y, y = h - 1 - display x.

Unsuccessful approach: Using the width as the mirror extent is the tag-8 inverse, not tag 6.

Case contract

A viewer letterboxes the displayed image (contain fit, centred) inside a view [vw, vh]. Map a tap [tx, ty] in view coordinates to the stored pixel [x, y] of an image of stored size [w, h] with orientation tag 1..8 (invalid -> 1); tags 5..8 swap displayed axes. Taps in the letterbox bars or on the far edge return None; the displayed pixel is floor of the exact position, then mapped back through the inverse of the orientation.

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
import math
from fractions import Fraction
N = 1
observations = []
def solve(view, size, tag, tap):
    vw, vh = view
    w, h = size
    tx, ty = tap
    if tag not in range(1, 9):
        tag = 1
    dw, dh = (h, w) if tag >= 5 else (w, h)
    s = min(Fraction(vw, dw), Fraction(vh, dh))
    ox = (vw - dw * s) / 2
    oy = (vh - dh * s) / 2
    dx = (tx - ox) / s
    dy = (ty - oy) / s
    if dx < 0 or dy < 0 or dx >= dw or dy >= dh:
        return None
    px, py = math.floor(dx), math.floor(dy)
    if tag == 1:
        return [px, py]
    if tag == 2:
        return [w - 1 - px, py]
    if tag == 3:
        return [w - 1 - px, h - 1 - py]
    if tag == 4:
        return [px, h - 1 - py]
    if tag == 5:
        return [py, px]
    if tag == 6:
        return [h - 1 - py, px]
    if tag == 7:
        return [w - 1 - py, h - 1 - px]
    return [w - 1 - py, px]
def check(label, actual, expected):
    observations.append({"check": label, "actual": actual, "expected": expected, "passed": actual == expected})
fixtures = [[[([38, 23], [5, 8], 6, [12, 1]), [0, 5]], [([13, 35], [3, 2], 6, [12, 19]), [1, 0]], [([40, 25], [5, 4], 8, [32, 13]), None], [([35, 16], [9, 2], 5, [3, 11]), None], [([13, 34], [5, 3], 1, [10, 31]), None], [([17, 19], [3, 9], 1, [7, 11]), [0, 5]], [([13, 26], [7, 5], 8, [9, 3]), None], [([22, 27], [6, 9], 6, [18, 15]), [3, 1]]], [[([38, 27], [8, 8], 6, [10, 21]), [6, 6]], [([22, 10], [5, 9], 6, [17, 5]), [2, 1]], [([22, 28], [8, 7], 6, [5, 13]), [3, 5]], [([40, 21], [2, 9], 3, [13, 12]), None], [([25, 26], [2, 9], 6, [18, 0]), None], [([21, 19], [8, 6], 3, [19, 2]), [0, 5]], [([29, 40], [2, 5], 3, [22, 11]), [0, 3]], [([23, 36], [6, 4], 6, [14, 11]), [1, 1]]], [[([8, 30], [2, 5], 6, [7, 15]), [1, 0]], [([9, 19], [5, 6], 6, [1, 9]), [2, 5]], [([17, 38], [4, 3], 4, [2, 16]), [0, 2]], [([35, 17], [7, 6], 1, [31, 5]), None], [([22, 15], [4, 6], 7, [16, 2]), [3, 1]], [([29, 33], [4, 5], 5, [5, 29]), None], [([37, 32], [8, 3], 3, [9, 25]), None], [([15, 28], [7, 3], 6, [4, 18]), [4, 2]]], [[([36, 34], [5, 7], 6, [14, 25]), [4, 4]], [([36, 37], [6, 8], 6, [29, 28]), [5, 1]], [([22, 29], [9, 2], 3, [8, 26]), None], [([35, 16], [3, 9], 2, [10, 1]), None], [([39, 33], [9, 7], 1, [6, 23]), [1, 5]], [([20, 23], [3, 9], 0, [20, 12]), None], [([29, 39], [9, 2], 8, [0, 36]), None], [([35, 10], [4, 8], 6, [17, 8]), [3, 4]]], [[([39, 29], [4, 8], 6, [11, 19]), [2, 5]], [([15, 17], [5, 7], 6, [8, 9]), [2, 3]], [([29, 39], [7, 6], 6, [23, 25]), [4, 1]], [([29, 20], [4, 2], 6, [24, 13]), None], [([22, 31], [8, 9], 5, [14, 4]), None], [([29, 29], [7, 9], 8, [12, 2]), None], [([15, 21], [6, 7], 7, [6, 5]), [5, 4]], [([38, 33], [8, 5], 6, [29, 25]), [6, 0]]]]
labels = ["regression: inverse mapping for tag 6", "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: inverse mapping for tag 6 0[7, 2][0, 5]Failed
repair trap 1[0, 1][1, 0]Failed
combined fault 2NoneNonePassed
control 3NoneNonePassed
control 4NoneNonePassed
boundary 5[0, 5][0, 5]Passed
boundary 6NoneNonePassed
control 7[5, 7][3, 1]Failed

SHA-256 / 7e74c106633bf5e1ba68de73e4f51a9225fc6df7f4fc45009773137a59d56bbd

2 / The unsuccessful fix

Exit 1
"""Failure Map reference implementation. Python standard library only."""
import json
import math
from fractions import Fraction
N = 1
observations = []
def solve(view, size, tag, tap):
    vw, vh = view
    w, h = size
    tx, ty = tap
    if tag not in range(1, 9):
        tag = 1
    dw, dh = (h, w) if tag >= 5 else (w, h)
    s = min(Fraction(vw, dw), Fraction(vh, dh))
    ox = (vw - dw * s) / 2
    oy = (vh - dh * s) / 2
    dx = (tx - ox) / s
    dy = (ty - oy) / s
    if dx < 0 or dy < 0 or dx >= dw or dy >= dh:
        return None
    px, py = math.floor(dx), math.floor(dy)
    if tag == 1:
        return [px, py]
    if tag == 2:
        return [w - 1 - px, py]
    if tag == 3:
        return [w - 1 - px, h - 1 - py]
    if tag == 4:
        return [px, h - 1 - py]
    if tag == 5:
        return [py, px]
    if tag == 6:
        return [py, w - 1 - px]
    if tag == 7:
        return [w - 1 - py, h - 1 - px]
    return [w - 1 - py, px]
def check(label, actual, expected):
    observations.append({"check": label, "actual": actual, "expected": expected, "passed": actual == expected})
fixtures = [[[([38, 23], [5, 8], 6, [12, 1]), [0, 5]], [([13, 35], [3, 2], 6, [12, 19]), [1, 0]], [([40, 25], [5, 4], 8, [32, 13]), None], [([35, 16], [9, 2], 5, [3, 11]), None], [([13, 34], [5, 3], 1, [10, 31]), None], [([17, 19], [3, 9], 1, [7, 11]), [0, 5]], [([13, 26], [7, 5], 8, [9, 3]), None], [([22, 27], [6, 9], 6, [18, 15]), [3, 1]]], [[([38, 27], [8, 8], 6, [10, 21]), [6, 6]], [([22, 10], [5, 9], 6, [17, 5]), [2, 1]], [([22, 28], [8, 7], 6, [5, 13]), [3, 5]], [([40, 21], [2, 9], 3, [13, 12]), None], [([25, 26], [2, 9], 6, [18, 0]), None], [([21, 19], [8, 6], 3, [19, 2]), [0, 5]], [([29, 40], [2, 5], 3, [22, 11]), [0, 3]], [([23, 36], [6, 4], 6, [14, 11]), [1, 1]]], [[([8, 30], [2, 5], 6, [7, 15]), [1, 0]], [([9, 19], [5, 6], 6, [1, 9]), [2, 5]], [([17, 38], [4, 3], 4, [2, 16]), [0, 2]], [([35, 17], [7, 6], 1, [31, 5]), None], [([22, 15], [4, 6], 7, [16, 2]), [3, 1]], [([29, 33], [4, 5], 5, [5, 29]), None], [([37, 32], [8, 3], 3, [9, 25]), None], [([15, 28], [7, 3], 6, [4, 18]), [4, 2]]], [[([36, 34], [5, 7], 6, [14, 25]), [4, 4]], [([36, 37], [6, 8], 6, [29, 28]), [5, 1]], [([22, 29], [9, 2], 3, [8, 26]), None], [([35, 16], [3, 9], 2, [10, 1]), None], [([39, 33], [9, 7], 1, [6, 23]), [1, 5]], [([20, 23], [3, 9], 0, [20, 12]), None], [([29, 39], [9, 2], 8, [0, 36]), None], [([35, 10], [4, 8], 6, [17, 8]), [3, 4]]], [[([39, 29], [4, 8], 6, [11, 19]), [2, 5]], [([15, 17], [5, 7], 6, [8, 9]), [2, 3]], [([29, 39], [7, 6], 6, [23, 25]), [4, 1]], [([29, 20], [4, 2], 6, [24, 13]), None], [([22, 31], [8, 9], 5, [14, 4]), None], [([29, 29], [7, 9], 8, [12, 2]), None], [([15, 21], [6, 7], 7, [6, 5]), [5, 4]], [([38, 33], [8, 5], 6, [29, 25]), [6, 0]]]]
labels = ["regression: inverse mapping for tag 6", "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: inverse mapping for tag 6 0[0, 2][0, 5]Failed
repair trap 1[1, 1][1, 0]Failed
combined fault 2NoneNonePassed
control 3NoneNonePassed
control 4NoneNonePassed
boundary 5[0, 5][0, 5]Passed
boundary 6NoneNonePassed
control 7[3, -2][3, 1]Failed

SHA-256 / 8a7e66f3294a5694096a294d84e6a1cbe28bf72f3b2ad362d5b1e5c70328d7ab

3 / The verified repair

Exit 0
"""Failure Map reference implementation. Python standard library only."""
import json
import math
from fractions import Fraction
N = 1
observations = []
def solve(view, size, tag, tap):
    vw, vh = view
    w, h = size
    tx, ty = tap
    if tag not in range(1, 9):
        tag = 1
    dw, dh = (h, w) if tag >= 5 else (w, h)
    s = min(Fraction(vw, dw), Fraction(vh, dh))
    ox = (vw - dw * s) / 2
    oy = (vh - dh * s) / 2
    dx = (tx - ox) / s
    dy = (ty - oy) / s
    if dx < 0 or dy < 0 or dx >= dw or dy >= dh:
        return None
    px, py = math.floor(dx), math.floor(dy)
    if tag == 1:
        return [px, py]
    if tag == 2:
        return [w - 1 - px, py]
    if tag == 3:
        return [w - 1 - px, h - 1 - py]
    if tag == 4:
        return [px, h - 1 - py]
    if tag == 5:
        return [py, px]
    if tag == 6:
        return [py, h - 1 - px]
    if tag == 7:
        return [w - 1 - py, h - 1 - px]
    return [w - 1 - py, px]
def check(label, actual, expected):
    observations.append({"check": label, "actual": actual, "expected": expected, "passed": actual == expected})
fixtures = [[[([38, 23], [5, 8], 6, [12, 1]), [0, 5]], [([13, 35], [3, 2], 6, [12, 19]), [1, 0]], [([40, 25], [5, 4], 8, [32, 13]), None], [([35, 16], [9, 2], 5, [3, 11]), None], [([13, 34], [5, 3], 1, [10, 31]), None], [([17, 19], [3, 9], 1, [7, 11]), [0, 5]], [([13, 26], [7, 5], 8, [9, 3]), None], [([22, 27], [6, 9], 6, [18, 15]), [3, 1]]], [[([38, 27], [8, 8], 6, [10, 21]), [6, 6]], [([22, 10], [5, 9], 6, [17, 5]), [2, 1]], [([22, 28], [8, 7], 6, [5, 13]), [3, 5]], [([40, 21], [2, 9], 3, [13, 12]), None], [([25, 26], [2, 9], 6, [18, 0]), None], [([21, 19], [8, 6], 3, [19, 2]), [0, 5]], [([29, 40], [2, 5], 3, [22, 11]), [0, 3]], [([23, 36], [6, 4], 6, [14, 11]), [1, 1]]], [[([8, 30], [2, 5], 6, [7, 15]), [1, 0]], [([9, 19], [5, 6], 6, [1, 9]), [2, 5]], [([17, 38], [4, 3], 4, [2, 16]), [0, 2]], [([35, 17], [7, 6], 1, [31, 5]), None], [([22, 15], [4, 6], 7, [16, 2]), [3, 1]], [([29, 33], [4, 5], 5, [5, 29]), None], [([37, 32], [8, 3], 3, [9, 25]), None], [([15, 28], [7, 3], 6, [4, 18]), [4, 2]]], [[([36, 34], [5, 7], 6, [14, 25]), [4, 4]], [([36, 37], [6, 8], 6, [29, 28]), [5, 1]], [([22, 29], [9, 2], 3, [8, 26]), None], [([35, 16], [3, 9], 2, [10, 1]), None], [([39, 33], [9, 7], 1, [6, 23]), [1, 5]], [([20, 23], [3, 9], 0, [20, 12]), None], [([29, 39], [9, 2], 8, [0, 36]), None], [([35, 10], [4, 8], 6, [17, 8]), [3, 4]]], [[([39, 29], [4, 8], 6, [11, 19]), [2, 5]], [([15, 17], [5, 7], 6, [8, 9]), [2, 3]], [([29, 39], [7, 6], 6, [23, 25]), [4, 1]], [([29, 20], [4, 2], 6, [24, 13]), None], [([22, 31], [8, 9], 5, [14, 4]), None], [([29, 29], [7, 9], 8, [12, 2]), None], [([15, 21], [6, 7], 7, [6, 5]), [5, 4]], [([38, 33], [8, 5], 6, [29, 25]), [6, 0]]]]
labels = ["regression: inverse mapping for tag 6", "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: inverse mapping for tag 6 0[0, 5][0, 5]Passed
repair trap 1[1, 0][1, 0]Passed
combined fault 2NoneNonePassed
control 3NoneNonePassed
control 4NoneNonePassed
boundary 5[0, 5][0, 5]Passed
boundary 6NoneNonePassed
control 7[3, 1][3, 1]Passed

SHA-256 / 77deb3127e7778c28a757901abb898c0764ef52728786287260acb2b36173574

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 2026-09-29T14:49:43.046152+00:00.

Case digest / 9a41543783b40dfa7694ee034fe810af5ab7fad0aef9f437a8526f699af0d821