FAILURE MAP
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FA-78861 / Image orientation metadata / Open access

Pixel bake mirrors tag 2 across the wrong axis · case 01

Horizontally mirrored scans come out vertically flipped.

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

ROOT CAUSE

The tag-2 branch reverses rows (vertical flip) rather than columns.

VERIFIED REPAIR

Reverse the column index: grid[r][w-1-c].

Unsuccessful approach: Negative indexing with -c leaves column 0 in place and shifts the rest by one.

Case contract

Bake an EXIF-style orientation tag (1..8) into a row-major pixel grid so the result displays upright. Tags 2/4 mirror horizontally/vertically, 3 rotates 180, 6 rotates 90 clockwise, 8 rotates 90 counter-clockwise, 5 transposes and 7 transverses; tags outside 1..8 are treated as 1. Tags 5..8 swap the output width and height.

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(grid, tag):
    h = len(grid)
    w = len(grid[0]) if h else 0
    if tag not in range(1, 9):
        tag = 1
    if tag in (5, 6, 7, 8):
        out_h, out_w = w, h
    else:
        out_h, out_w = h, w
    out = []
    for r in range(out_h):
        row = []
        for c in range(out_w):
            if tag == 1:
                v = grid[r][c]
            elif tag == 2:
                v = grid[h - 1 - r][c]
            elif tag == 3:
                v = grid[h - 1 - r][w - 1 - c]
            elif tag == 4:
                v = grid[h - 1 - r][c]
            elif tag == 5:
                v = grid[c][r]
            elif tag == 6:
                v = grid[h - 1 - c][r]
            elif tag == 7:
                v = grid[h - 1 - c][w - 1 - r]
            else:
                v = grid[c][w - 1 - r]
            row.append(v)
        out.append(row)
    return out
def check(label, actual, expected):
    observations.append({"check": label, "actual": actual, "expected": expected, "passed": actual == expected})
fixtures = [[[([[1, 2, 3, 4]], 2), [[4, 3, 2, 1]]], [([[1, 2, 3, 4], [11, 12, 13, 14]], 2), [[4, 3, 2, 1], [14, 13, 12, 11]]], [([[1, 2, 3, 4], [11, 12, 13, 14], [21, 22, 23, 24], [31, 32, 33, 34]], 6), [[31, 21, 11, 1], [32, 22, 12, 2], [33, 23, 13, 3], [34, 24, 14, 4]]], [([[1], [11], [21], [31]], 8), [[1, 11, 21, 31]]], [([[1, 2, 3], [11, 12, 13], [21, 22, 23]], 6), [[21, 11, 1], [22, 12, 2], [23, 13, 3]]], [([[1, 2, 3, 4]], 5), [[1], [2], [3], [4]]], [([[1, 2, 3]], 4), [[1, 2, 3]]], [([[1, 2], [11, 12], [21, 22], [31, 32]], 2), [[2, 1], [12, 11], [22, 21], [32, 31]]]], [[([[2, 3, 4, 5], [12, 13, 14, 15], [22, 23, 24, 25]], 2), [[5, 4, 3, 2], [15, 14, 13, 12], [25, 24, 23, 22]]], [([[2, 3], [12, 13], [22, 23], [32, 33]], 2), [[3, 2], [13, 12], [23, 22], [33, 32]]], [([[2, 3, 4, 5], [12, 13, 14, 15]], 9), [[2, 3, 4, 5], [12, 13, 14, 15]]], [([[2, 3, 4], [12, 13, 14], [22, 23, 24]], 0), [[2, 3, 4], [12, 13, 14], [22, 23, 24]]], [([[2, 3, 4], [12, 13, 14], [22, 23, 24], [32, 33, 34]], 6), [[32, 22, 12, 2], [33, 23, 13, 3], [34, 24, 14, 4]]], [([[2]], 1), [[2]]], [([[2, 3, 4, 5], [12, 13, 14, 15]], 6), [[12, 2], [13, 3], [14, 4], [15, 5]]], [([[2, 3, 4, 5]], 2), [[5, 4, 3, 2]]]], [[([[3, 4, 5], [13, 14, 15]], 2), [[5, 4, 3], [15, 14, 13]]], [([[3, 4, 5, 6]], 2), [[6, 5, 4, 3]]], [([[3, 4, 5, 6]], 8), [[6], [5], [4], [3]]], [([[3, 4], [13, 14], [23, 24], [33, 34]], 8), [[4, 14, 24, 34], [3, 13, 23, 33]]], [([[3]], 8), [[3]]], [([[3, 4], [13, 14], [23, 24]], 6), [[23, 13, 3], [24, 14, 4]]], [([[3, 4, 5, 6], [13, 14, 15, 16], [23, 24, 25, 26]], 8), [[6, 16, 26], [5, 15, 25], [4, 14, 24], [3, 13, 23]]], [([[3, 4], [13, 14]], 2), [[4, 3], [14, 13]]]], [[([[4, 5, 6, 7], [14, 15, 16, 17], [24, 25, 26, 27], [34, 35, 36, 37]], 2), [[7, 6, 5, 4], [17, 16, 15, 14], [27, 26, 25, 24], [37, 36, 35, 34]]], [([[4, 5, 6], [14, 15, 16]], 2), [[6, 5, 4], [16, 15, 14]]], [([[4, 5], [14, 15]], 2), [[5, 4], [15, 14]]], [([[4, 5, 6, 7], [14, 15, 16, 17], [24, 25, 26, 27]], 9), [[4, 5, 6, 7], [14, 15, 16, 17], [24, 25, 26, 27]]], [([[4, 5, 6], [14, 15, 16]], 3), [[16, 15, 14], [6, 5, 4]]], [([[4, 5], [14, 15]], 5), [[4, 14], [5, 15]]], [([[4, 5, 6, 7], [14, 15, 16, 17], [24, 25, 26, 27], [34, 35, 36, 37]], 9), [[4, 5, 6, 7], [14, 15, 16, 17], [24, 25, 26, 27], [34, 35, 36, 37]]], [([[4, 5, 6]], 2), [[6, 5, 4]]]], [[([[5], [15]], 2), [[5], [15]]], [([[5, 6, 7], [15, 16, 17], [25, 26, 27]], 2), [[7, 6, 5], [17, 16, 15], [27, 26, 25]]], [([[5, 6, 7]], 2), [[7, 6, 5]]], [([[5], [15]], 4), [[15], [5]]], [([[5, 6]], 9), [[5, 6]]], [([[5]], 6), [[5]]], [([[5, 6, 7, 8], [15, 16, 17, 18], [25, 26, 27, 28]], 3), [[28, 27, 26, 25], [18, 17, 16, 15], [8, 7, 6, 5]]], [([[5], [15], [25], [35]], 2), [[5], [15], [25], [35]]]]]
labels = ["regression: tag 2 mirror axis", "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: tag 2 mirror axis 0[[1, 2, 3, 4]][[4, 3, 2, 1]]Failed
repair trap 1[[11, 12, 13, 14], [1, 2, 3, 4]][[4, 3, 2, 1], [14, 13, 12, 11]]Failed
combined fault 2[[31, 21, 11, 1], [32, 22, 12, 2], [33, 23, 13, 3], [34, 24, 14, 4]][[31, 21, 11, 1], [32, 22, 12, 2], [33, 23, 13, 3], [34, 24, 14, 4]]Passed
control 3[[1, 11, 21, 31]][[1, 11, 21, 31]]Passed
control 4[[21, 11, 1], [22, 12, 2], [23, 13, 3]][[21, 11, 1], [22, 12, 2], [23, 13, 3]]Passed
boundary 5[[1], [2], [3], [4]][[1], [2], [3], [4]]Passed
boundary 6[[1, 2, 3]][[1, 2, 3]]Passed
control 7[[31, 32], [21, 22], [11, 12], [1, 2]][[2, 1], [12, 11], [22, 21], [32, 31]]Failed

SHA-256 / 99cd169eab676b905360013b7779851ba7bc5b49b185938f0c8c2d07505dc564

2 / The unsuccessful fix

Exit 1
"""Failure Map reference implementation. Python standard library only."""
import json

N = 1
observations = []
def solve(grid, tag):
    h = len(grid)
    w = len(grid[0]) if h else 0
    if tag not in range(1, 9):
        tag = 1
    if tag in (5, 6, 7, 8):
        out_h, out_w = w, h
    else:
        out_h, out_w = h, w
    out = []
    for r in range(out_h):
        row = []
        for c in range(out_w):
            if tag == 1:
                v = grid[r][c]
            elif tag == 2:
                v = grid[r][-c]
            elif tag == 3:
                v = grid[h - 1 - r][w - 1 - c]
            elif tag == 4:
                v = grid[h - 1 - r][c]
            elif tag == 5:
                v = grid[c][r]
            elif tag == 6:
                v = grid[h - 1 - c][r]
            elif tag == 7:
                v = grid[h - 1 - c][w - 1 - r]
            else:
                v = grid[c][w - 1 - r]
            row.append(v)
        out.append(row)
    return out
def check(label, actual, expected):
    observations.append({"check": label, "actual": actual, "expected": expected, "passed": actual == expected})
fixtures = [[[([[1, 2, 3, 4]], 2), [[4, 3, 2, 1]]], [([[1, 2, 3, 4], [11, 12, 13, 14]], 2), [[4, 3, 2, 1], [14, 13, 12, 11]]], [([[1, 2, 3, 4], [11, 12, 13, 14], [21, 22, 23, 24], [31, 32, 33, 34]], 6), [[31, 21, 11, 1], [32, 22, 12, 2], [33, 23, 13, 3], [34, 24, 14, 4]]], [([[1], [11], [21], [31]], 8), [[1, 11, 21, 31]]], [([[1, 2, 3], [11, 12, 13], [21, 22, 23]], 6), [[21, 11, 1], [22, 12, 2], [23, 13, 3]]], [([[1, 2, 3, 4]], 5), [[1], [2], [3], [4]]], [([[1, 2, 3]], 4), [[1, 2, 3]]], [([[1, 2], [11, 12], [21, 22], [31, 32]], 2), [[2, 1], [12, 11], [22, 21], [32, 31]]]], [[([[2, 3, 4, 5], [12, 13, 14, 15], [22, 23, 24, 25]], 2), [[5, 4, 3, 2], [15, 14, 13, 12], [25, 24, 23, 22]]], [([[2, 3], [12, 13], [22, 23], [32, 33]], 2), [[3, 2], [13, 12], [23, 22], [33, 32]]], [([[2, 3, 4, 5], [12, 13, 14, 15]], 9), [[2, 3, 4, 5], [12, 13, 14, 15]]], [([[2, 3, 4], [12, 13, 14], [22, 23, 24]], 0), [[2, 3, 4], [12, 13, 14], [22, 23, 24]]], [([[2, 3, 4], [12, 13, 14], [22, 23, 24], [32, 33, 34]], 6), [[32, 22, 12, 2], [33, 23, 13, 3], [34, 24, 14, 4]]], [([[2]], 1), [[2]]], [([[2, 3, 4, 5], [12, 13, 14, 15]], 6), [[12, 2], [13, 3], [14, 4], [15, 5]]], [([[2, 3, 4, 5]], 2), [[5, 4, 3, 2]]]], [[([[3, 4, 5], [13, 14, 15]], 2), [[5, 4, 3], [15, 14, 13]]], [([[3, 4, 5, 6]], 2), [[6, 5, 4, 3]]], [([[3, 4, 5, 6]], 8), [[6], [5], [4], [3]]], [([[3, 4], [13, 14], [23, 24], [33, 34]], 8), [[4, 14, 24, 34], [3, 13, 23, 33]]], [([[3]], 8), [[3]]], [([[3, 4], [13, 14], [23, 24]], 6), [[23, 13, 3], [24, 14, 4]]], [([[3, 4, 5, 6], [13, 14, 15, 16], [23, 24, 25, 26]], 8), [[6, 16, 26], [5, 15, 25], [4, 14, 24], [3, 13, 23]]], [([[3, 4], [13, 14]], 2), [[4, 3], [14, 13]]]], [[([[4, 5, 6, 7], [14, 15, 16, 17], [24, 25, 26, 27], [34, 35, 36, 37]], 2), [[7, 6, 5, 4], [17, 16, 15, 14], [27, 26, 25, 24], [37, 36, 35, 34]]], [([[4, 5, 6], [14, 15, 16]], 2), [[6, 5, 4], [16, 15, 14]]], [([[4, 5], [14, 15]], 2), [[5, 4], [15, 14]]], [([[4, 5, 6, 7], [14, 15, 16, 17], [24, 25, 26, 27]], 9), [[4, 5, 6, 7], [14, 15, 16, 17], [24, 25, 26, 27]]], [([[4, 5, 6], [14, 15, 16]], 3), [[16, 15, 14], [6, 5, 4]]], [([[4, 5], [14, 15]], 5), [[4, 14], [5, 15]]], [([[4, 5, 6, 7], [14, 15, 16, 17], [24, 25, 26, 27], [34, 35, 36, 37]], 9), [[4, 5, 6, 7], [14, 15, 16, 17], [24, 25, 26, 27], [34, 35, 36, 37]]], [([[4, 5, 6]], 2), [[6, 5, 4]]]], [[([[5], [15]], 2), [[5], [15]]], [([[5, 6, 7], [15, 16, 17], [25, 26, 27]], 2), [[7, 6, 5], [17, 16, 15], [27, 26, 25]]], [([[5, 6, 7]], 2), [[7, 6, 5]]], [([[5], [15]], 4), [[15], [5]]], [([[5, 6]], 9), [[5, 6]]], [([[5]], 6), [[5]]], [([[5, 6, 7, 8], [15, 16, 17, 18], [25, 26, 27, 28]], 3), [[28, 27, 26, 25], [18, 17, 16, 15], [8, 7, 6, 5]]], [([[5], [15], [25], [35]], 2), [[5], [15], [25], [35]]]]]
labels = ["regression: tag 2 mirror axis", "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: tag 2 mirror axis 0[[1, 4, 3, 2]][[4, 3, 2, 1]]Failed
repair trap 1[[1, 4, 3, 2], [11, 14, 13, 12]][[4, 3, 2, 1], [14, 13, 12, 11]]Failed
combined fault 2[[31, 21, 11, 1], [32, 22, 12, 2], [33, 23, 13, 3], [34, 24, 14, 4]][[31, 21, 11, 1], [32, 22, 12, 2], [33, 23, 13, 3], [34, 24, 14, 4]]Passed
control 3[[1, 11, 21, 31]][[1, 11, 21, 31]]Passed
control 4[[21, 11, 1], [22, 12, 2], [23, 13, 3]][[21, 11, 1], [22, 12, 2], [23, 13, 3]]Passed
boundary 5[[1], [2], [3], [4]][[1], [2], [3], [4]]Passed
boundary 6[[1, 2, 3]][[1, 2, 3]]Passed
control 7[[1, 2], [11, 12], [21, 22], [31, 32]][[2, 1], [12, 11], [22, 21], [32, 31]]Failed

SHA-256 / e9ca208d7bf241d14280e3cfa8fdca2389b0c1ec9584233032a691f13a2c143d

3 / The verified repair

Exit 0
"""Failure Map reference implementation. Python standard library only."""
import json

N = 1
observations = []
def solve(grid, tag):
    h = len(grid)
    w = len(grid[0]) if h else 0
    if tag not in range(1, 9):
        tag = 1
    if tag in (5, 6, 7, 8):
        out_h, out_w = w, h
    else:
        out_h, out_w = h, w
    out = []
    for r in range(out_h):
        row = []
        for c in range(out_w):
            if tag == 1:
                v = grid[r][c]
            elif tag == 2:
                v = grid[r][w - 1 - c]
            elif tag == 3:
                v = grid[h - 1 - r][w - 1 - c]
            elif tag == 4:
                v = grid[h - 1 - r][c]
            elif tag == 5:
                v = grid[c][r]
            elif tag == 6:
                v = grid[h - 1 - c][r]
            elif tag == 7:
                v = grid[h - 1 - c][w - 1 - r]
            else:
                v = grid[c][w - 1 - r]
            row.append(v)
        out.append(row)
    return out
def check(label, actual, expected):
    observations.append({"check": label, "actual": actual, "expected": expected, "passed": actual == expected})
fixtures = [[[([[1, 2, 3, 4]], 2), [[4, 3, 2, 1]]], [([[1, 2, 3, 4], [11, 12, 13, 14]], 2), [[4, 3, 2, 1], [14, 13, 12, 11]]], [([[1, 2, 3, 4], [11, 12, 13, 14], [21, 22, 23, 24], [31, 32, 33, 34]], 6), [[31, 21, 11, 1], [32, 22, 12, 2], [33, 23, 13, 3], [34, 24, 14, 4]]], [([[1], [11], [21], [31]], 8), [[1, 11, 21, 31]]], [([[1, 2, 3], [11, 12, 13], [21, 22, 23]], 6), [[21, 11, 1], [22, 12, 2], [23, 13, 3]]], [([[1, 2, 3, 4]], 5), [[1], [2], [3], [4]]], [([[1, 2, 3]], 4), [[1, 2, 3]]], [([[1, 2], [11, 12], [21, 22], [31, 32]], 2), [[2, 1], [12, 11], [22, 21], [32, 31]]]], [[([[2, 3, 4, 5], [12, 13, 14, 15], [22, 23, 24, 25]], 2), [[5, 4, 3, 2], [15, 14, 13, 12], [25, 24, 23, 22]]], [([[2, 3], [12, 13], [22, 23], [32, 33]], 2), [[3, 2], [13, 12], [23, 22], [33, 32]]], [([[2, 3, 4, 5], [12, 13, 14, 15]], 9), [[2, 3, 4, 5], [12, 13, 14, 15]]], [([[2, 3, 4], [12, 13, 14], [22, 23, 24]], 0), [[2, 3, 4], [12, 13, 14], [22, 23, 24]]], [([[2, 3, 4], [12, 13, 14], [22, 23, 24], [32, 33, 34]], 6), [[32, 22, 12, 2], [33, 23, 13, 3], [34, 24, 14, 4]]], [([[2]], 1), [[2]]], [([[2, 3, 4, 5], [12, 13, 14, 15]], 6), [[12, 2], [13, 3], [14, 4], [15, 5]]], [([[2, 3, 4, 5]], 2), [[5, 4, 3, 2]]]], [[([[3, 4, 5], [13, 14, 15]], 2), [[5, 4, 3], [15, 14, 13]]], [([[3, 4, 5, 6]], 2), [[6, 5, 4, 3]]], [([[3, 4, 5, 6]], 8), [[6], [5], [4], [3]]], [([[3, 4], [13, 14], [23, 24], [33, 34]], 8), [[4, 14, 24, 34], [3, 13, 23, 33]]], [([[3]], 8), [[3]]], [([[3, 4], [13, 14], [23, 24]], 6), [[23, 13, 3], [24, 14, 4]]], [([[3, 4, 5, 6], [13, 14, 15, 16], [23, 24, 25, 26]], 8), [[6, 16, 26], [5, 15, 25], [4, 14, 24], [3, 13, 23]]], [([[3, 4], [13, 14]], 2), [[4, 3], [14, 13]]]], [[([[4, 5, 6, 7], [14, 15, 16, 17], [24, 25, 26, 27], [34, 35, 36, 37]], 2), [[7, 6, 5, 4], [17, 16, 15, 14], [27, 26, 25, 24], [37, 36, 35, 34]]], [([[4, 5, 6], [14, 15, 16]], 2), [[6, 5, 4], [16, 15, 14]]], [([[4, 5], [14, 15]], 2), [[5, 4], [15, 14]]], [([[4, 5, 6, 7], [14, 15, 16, 17], [24, 25, 26, 27]], 9), [[4, 5, 6, 7], [14, 15, 16, 17], [24, 25, 26, 27]]], [([[4, 5, 6], [14, 15, 16]], 3), [[16, 15, 14], [6, 5, 4]]], [([[4, 5], [14, 15]], 5), [[4, 14], [5, 15]]], [([[4, 5, 6, 7], [14, 15, 16, 17], [24, 25, 26, 27], [34, 35, 36, 37]], 9), [[4, 5, 6, 7], [14, 15, 16, 17], [24, 25, 26, 27], [34, 35, 36, 37]]], [([[4, 5, 6]], 2), [[6, 5, 4]]]], [[([[5], [15]], 2), [[5], [15]]], [([[5, 6, 7], [15, 16, 17], [25, 26, 27]], 2), [[7, 6, 5], [17, 16, 15], [27, 26, 25]]], [([[5, 6, 7]], 2), [[7, 6, 5]]], [([[5], [15]], 4), [[15], [5]]], [([[5, 6]], 9), [[5, 6]]], [([[5]], 6), [[5]]], [([[5, 6, 7, 8], [15, 16, 17, 18], [25, 26, 27, 28]], 3), [[28, 27, 26, 25], [18, 17, 16, 15], [8, 7, 6, 5]]], [([[5], [15], [25], [35]], 2), [[5], [15], [25], [35]]]]]
labels = ["regression: tag 2 mirror axis", "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: tag 2 mirror axis 0[[4, 3, 2, 1]][[4, 3, 2, 1]]Passed
repair trap 1[[4, 3, 2, 1], [14, 13, 12, 11]][[4, 3, 2, 1], [14, 13, 12, 11]]Passed
combined fault 2[[31, 21, 11, 1], [32, 22, 12, 2], [33, 23, 13, 3], [34, 24, 14, 4]][[31, 21, 11, 1], [32, 22, 12, 2], [33, 23, 13, 3], [34, 24, 14, 4]]Passed
control 3[[1, 11, 21, 31]][[1, 11, 21, 31]]Passed
control 4[[21, 11, 1], [22, 12, 2], [23, 13, 3]][[21, 11, 1], [22, 12, 2], [23, 13, 3]]Passed
boundary 5[[1], [2], [3], [4]][[1], [2], [3], [4]]Passed
boundary 6[[1, 2, 3]][[1, 2, 3]]Passed
control 7[[2, 1], [12, 11], [22, 21], [32, 31]][[2, 1], [12, 11], [22, 21], [32, 31]]Passed

SHA-256 / 807683b7dbf27fa954b753ecbcf853ddf81fae6c5bb21ee363596a7a746e30f1

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 2026-09-29T14:49:39.243936+00:00.

Case digest / b66edbec2304bfe0f96959fbc2a07a38494567a20ede23171a4fc39536e283c6