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FA-78841 / Image orientation metadata / Open access

Pixel bake turns tag-6 photos counter-clockwise · case 01

Portrait phone photos tagged 6 are baked upside down relative to what every viewer shows.

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

ROOT CAUSE

The tag-6 branch samples grid[c][w-1-r], the counter-clockwise source, instead of grid[h-1-c][r].

VERIFIED REPAIR

Sample grid[h-1-c][r] so the stored left column, read bottom to top, becomes the top row.

Unsuccessful approach: Mirroring from the width (w-1-c) instead of the height is only right for square images and wraps negative indexes on tall ones.

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[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[c][w - 1 - 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], [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]], 6), [[21, 11, 1]]], [([[1], [11], [21], [31]], 8), [[1, 11, 21, 31]]], [([[1, 2, 3, 4]], 5), [[1], [2], [3], [4]]], [([[1, 2, 3, 4]], 2), [[4, 3, 2, 1]]], [([[1, 2], [11, 12], [21, 22], [31, 32]], 2), [[2, 1], [12, 11], [22, 21], [32, 31]]], [([[1, 2, 3]], 4), [[1, 2, 3]]], [([[1, 2, 3], [11, 12, 13], [21, 22, 23]], 6), [[21, 11, 1], [22, 12, 2], [23, 13, 3]]]], [[([[2, 3], [12, 13], [22, 23], [32, 33]], 6), [[32, 22, 12, 2], [33, 23, 13, 3]]], [([[2], [12]], 6), [[12, 2]]], [([[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]], 1), [[2]]], [([[2, 3, 4], [12, 13, 14]], 5), [[2, 12], [3, 13], [4, 14]]], [([[2, 3, 4]], 3), [[4, 3, 2]]], [([[2], [12], [22]], 6), [[22, 12, 2]]]], [[([[3], [13]], 6), [[13, 3]]], [([[3, 4], [13, 14], [23, 24]], 6), [[23, 13, 3], [24, 14, 4]]], [([[3, 4], [13, 14], [23, 24], [33, 34]], 8), [[4, 14, 24, 34], [3, 13, 23, 33]]], [([[3]], 8), [[3]]], [([[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], [13]], 3), [[13], [3]]], [([[3, 4, 5, 6], [13, 14, 15, 16]], 0), [[3, 4, 5, 6], [13, 14, 15, 16]]], [([[3, 4, 5, 6], [13, 14, 15, 16], [23, 24, 25, 26], [33, 34, 35, 36]], 6), [[33, 23, 13, 3], [34, 24, 14, 4], [35, 25, 15, 5], [36, 26, 16, 6]]]], [[([[4], [14]], 6), [[14, 4]]], [([[4], [14], [24]], 6), [[24, 14, 4]]], [([[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), [[4]]], [([[4, 5, 6, 7], [14, 15, 16, 17], [24, 25, 26, 27], [34, 35, 36, 37]], 6), [[34, 24, 14, 4], [35, 25, 15, 5], [36, 26, 16, 6], [37, 27, 17, 7]]]], [[([[5], [15], [25], [35]], 6), [[35, 25, 15, 5]]], [([[5, 6], [15, 16], [25, 26], [35, 36]], 6), [[35, 25, 15, 5], [36, 26, 16, 6]]], [([[5], [15], [25]], 2), [[5], [15], [25]]], [([[5], [15]], 4), [[15], [5]]], [([[5, 6]], 9), [[5, 6]]], [([[5]], 6), [[5]]], [([[5], [15], [25], [35]], 2), [[5], [15], [25], [35]]], [([[5], [15], [25]], 6), [[25, 15, 5]]]]]
labels = ["regression: tag 6 clockwise source index", "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 6 clockwise source index 0[[4, 14, 24, 34], [3, 13, 23, 33], [2, 12, 22, 32], [1, 11, 21, 31]][[31, 21, 11, 1], [32, 22, 12, 2], [33, 23, 13, 3], [34, 24, 14, 4]]Failed
repair trap 1[[1, 11, 21]][[21, 11, 1]]Failed
combined fault 2[[1, 11, 21, 31]][[1, 11, 21, 31]]Passed
control 3[[1], [2], [3], [4]][[1], [2], [3], [4]]Passed
control 4[[4, 3, 2, 1]][[4, 3, 2, 1]]Passed
boundary 5[[2, 1], [12, 11], [22, 21], [32, 31]][[2, 1], [12, 11], [22, 21], [32, 31]]Passed
boundary 6[[1, 2, 3]][[1, 2, 3]]Passed
control 7[[3, 13, 23], [2, 12, 22], [1, 11, 21]][[21, 11, 1], [22, 12, 2], [23, 13, 3]]Failed

SHA-256 / ab912af2ecd836662d053fd6d0d53c8078e68e8fb81697c49bed6f9654055f57

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][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[w - 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], [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]], 6), [[21, 11, 1]]], [([[1], [11], [21], [31]], 8), [[1, 11, 21, 31]]], [([[1, 2, 3, 4]], 5), [[1], [2], [3], [4]]], [([[1, 2, 3, 4]], 2), [[4, 3, 2, 1]]], [([[1, 2], [11, 12], [21, 22], [31, 32]], 2), [[2, 1], [12, 11], [22, 21], [32, 31]]], [([[1, 2, 3]], 4), [[1, 2, 3]]], [([[1, 2, 3], [11, 12, 13], [21, 22, 23]], 6), [[21, 11, 1], [22, 12, 2], [23, 13, 3]]]], [[([[2, 3], [12, 13], [22, 23], [32, 33]], 6), [[32, 22, 12, 2], [33, 23, 13, 3]]], [([[2], [12]], 6), [[12, 2]]], [([[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]], 1), [[2]]], [([[2, 3, 4], [12, 13, 14]], 5), [[2, 12], [3, 13], [4, 14]]], [([[2, 3, 4]], 3), [[4, 3, 2]]], [([[2], [12], [22]], 6), [[22, 12, 2]]]], [[([[3], [13]], 6), [[13, 3]]], [([[3, 4], [13, 14], [23, 24]], 6), [[23, 13, 3], [24, 14, 4]]], [([[3, 4], [13, 14], [23, 24], [33, 34]], 8), [[4, 14, 24, 34], [3, 13, 23, 33]]], [([[3]], 8), [[3]]], [([[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], [13]], 3), [[13], [3]]], [([[3, 4, 5, 6], [13, 14, 15, 16]], 0), [[3, 4, 5, 6], [13, 14, 15, 16]]], [([[3, 4, 5, 6], [13, 14, 15, 16], [23, 24, 25, 26], [33, 34, 35, 36]], 6), [[33, 23, 13, 3], [34, 24, 14, 4], [35, 25, 15, 5], [36, 26, 16, 6]]]], [[([[4], [14]], 6), [[14, 4]]], [([[4], [14], [24]], 6), [[24, 14, 4]]], [([[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), [[4]]], [([[4, 5, 6, 7], [14, 15, 16, 17], [24, 25, 26, 27], [34, 35, 36, 37]], 6), [[34, 24, 14, 4], [35, 25, 15, 5], [36, 26, 16, 6], [37, 27, 17, 7]]]], [[([[5], [15], [25], [35]], 6), [[35, 25, 15, 5]]], [([[5, 6], [15, 16], [25, 26], [35, 36]], 6), [[35, 25, 15, 5], [36, 26, 16, 6]]], [([[5], [15], [25]], 2), [[5], [15], [25]]], [([[5], [15]], 4), [[15], [5]]], [([[5, 6]], 9), [[5, 6]]], [([[5]], 6), [[5]]], [([[5], [15], [25], [35]], 2), [[5], [15], [25], [35]]], [([[5], [15], [25]], 6), [[25, 15, 5]]]]]
labels = ["regression: tag 6 clockwise source index", "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 6 clockwise source index 0[[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
repair trap 1[[1, 21, 11]][[21, 11, 1]]Failed
combined fault 2[[1, 11, 21, 31]][[1, 11, 21, 31]]Passed
control 3[[1], [2], [3], [4]][[1], [2], [3], [4]]Passed
control 4[[4, 3, 2, 1]][[4, 3, 2, 1]]Passed
boundary 5[[2, 1], [12, 11], [22, 21], [32, 31]][[2, 1], [12, 11], [22, 21], [32, 31]]Passed
boundary 6[[1, 2, 3]][[1, 2, 3]]Passed
control 7[[21, 11, 1], [22, 12, 2], [23, 13, 3]][[21, 11, 1], [22, 12, 2], [23, 13, 3]]Passed

SHA-256 / aa00c2f6897a4ac0990bbef372ebdeef1875e46df17909da1cc2157049df55a3

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], [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]], 6), [[21, 11, 1]]], [([[1], [11], [21], [31]], 8), [[1, 11, 21, 31]]], [([[1, 2, 3, 4]], 5), [[1], [2], [3], [4]]], [([[1, 2, 3, 4]], 2), [[4, 3, 2, 1]]], [([[1, 2], [11, 12], [21, 22], [31, 32]], 2), [[2, 1], [12, 11], [22, 21], [32, 31]]], [([[1, 2, 3]], 4), [[1, 2, 3]]], [([[1, 2, 3], [11, 12, 13], [21, 22, 23]], 6), [[21, 11, 1], [22, 12, 2], [23, 13, 3]]]], [[([[2, 3], [12, 13], [22, 23], [32, 33]], 6), [[32, 22, 12, 2], [33, 23, 13, 3]]], [([[2], [12]], 6), [[12, 2]]], [([[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]], 1), [[2]]], [([[2, 3, 4], [12, 13, 14]], 5), [[2, 12], [3, 13], [4, 14]]], [([[2, 3, 4]], 3), [[4, 3, 2]]], [([[2], [12], [22]], 6), [[22, 12, 2]]]], [[([[3], [13]], 6), [[13, 3]]], [([[3, 4], [13, 14], [23, 24]], 6), [[23, 13, 3], [24, 14, 4]]], [([[3, 4], [13, 14], [23, 24], [33, 34]], 8), [[4, 14, 24, 34], [3, 13, 23, 33]]], [([[3]], 8), [[3]]], [([[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], [13]], 3), [[13], [3]]], [([[3, 4, 5, 6], [13, 14, 15, 16]], 0), [[3, 4, 5, 6], [13, 14, 15, 16]]], [([[3, 4, 5, 6], [13, 14, 15, 16], [23, 24, 25, 26], [33, 34, 35, 36]], 6), [[33, 23, 13, 3], [34, 24, 14, 4], [35, 25, 15, 5], [36, 26, 16, 6]]]], [[([[4], [14]], 6), [[14, 4]]], [([[4], [14], [24]], 6), [[24, 14, 4]]], [([[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), [[4]]], [([[4, 5, 6, 7], [14, 15, 16, 17], [24, 25, 26, 27], [34, 35, 36, 37]], 6), [[34, 24, 14, 4], [35, 25, 15, 5], [36, 26, 16, 6], [37, 27, 17, 7]]]], [[([[5], [15], [25], [35]], 6), [[35, 25, 15, 5]]], [([[5, 6], [15, 16], [25, 26], [35, 36]], 6), [[35, 25, 15, 5], [36, 26, 16, 6]]], [([[5], [15], [25]], 2), [[5], [15], [25]]], [([[5], [15]], 4), [[15], [5]]], [([[5, 6]], 9), [[5, 6]]], [([[5]], 6), [[5]]], [([[5], [15], [25], [35]], 2), [[5], [15], [25], [35]]], [([[5], [15], [25]], 6), [[25, 15, 5]]]]]
labels = ["regression: tag 6 clockwise source index", "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 6 clockwise source index 0[[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
repair trap 1[[21, 11, 1]][[21, 11, 1]]Passed
combined fault 2[[1, 11, 21, 31]][[1, 11, 21, 31]]Passed
control 3[[1], [2], [3], [4]][[1], [2], [3], [4]]Passed
control 4[[4, 3, 2, 1]][[4, 3, 2, 1]]Passed
boundary 5[[2, 1], [12, 11], [22, 21], [32, 31]][[2, 1], [12, 11], [22, 21], [32, 31]]Passed
boundary 6[[1, 2, 3]][[1, 2, 3]]Passed
control 7[[21, 11, 1], [22, 12, 2], [23, 13, 3]][[21, 11, 1], [22, 12, 2], [23, 13, 3]]Passed

SHA-256 / 4e8a5e945d6311d7ced3fa2dba37fa1c9072a8bb69c72e17aae2a839ba45ecb6

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 2026-09-29T14:49:39.207224+00:00.

Case digest / 2976057049abb8f85beff875400021c164bc4eeedce931e37873cf4936f1d50d