FA-79306 / Image orientation metadata / Open access
Canonical key flattens the grid column by column · case 01
Two services computing the canonical form disagree because one flattens column-major.
ROOT CAUSE
The key is built column-major although the contract compares row-major pixel sequences.
THE FAILURE
The key is built column-major although the contract compares row-major pixel sequences.
Unsuccessful approach: Reversing the row order changes which orientation is minimal.
Case contract
For duplicate detection, bring a pixel grid into a canonical orientation: of the eight orientations (tags 1..8, same pixel mapping as EXIF baking), pick the one whose key (height, width, row-major pixels) is smallest; ties go to the lowest tag. Return [tag, inverse_tag, canonical_grid] where the inverse tag restores the original (6 and 8 are mutual inverses, every other tag is self-inverse).
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):
h = len(grid)
w = len(grid[0])
def src(t, r, c):
return {1: (r, c), 2: (r, w - 1 - c), 3: (h - 1 - r, w - 1 - c), 4: (h - 1 - r, c),
5: (c, r), 6: (h - 1 - c, r), 7: (h - 1 - c, w - 1 - r), 8: (c, w - 1 - r)}[t]
best = None
for t in range(1, 9):
oh, ow = (w, h) if t >= 5 else (h, w)
img = [[grid[src(t, r, c)[0]][src(t, r, c)[1]] for c in range(ow)] for r in range(oh)]
key = (oh, ow, [row[c] for c in range(ow) for row in img])
if best is None or key < best[0]:
best = (key, t, img)
inverse = {6: 8, 8: 6}.get(best[1], best[1])
return [best[1], inverse, best[2]]
def check(label, actual, expected):
observations.append({"check": label, "actual": actual, "expected": expected, "passed": actual == expected})
fixtures = [[[[[6, 3, 0], [0, 8, 5], [1, 5, 5]], [2, 2, [[0, 3, 6], [5, 8, 0], [5, 5, 1]]]], [[[0, 0], [1, 1], [0, 1]], [5, 5, [[0, 1, 0], [0, 1, 1]]]], [[[1, 0, 1], [1, 0, 0], [0, 0, 1]], [4, 4, [[0, 0, 1], [1, 0, 0], [1, 0, 1]]]], [[[4, 7, 0]], [2, 2, [[0, 7, 4]]]], [[[7]], [1, 1, [[7]]]], [[[0, 1, 1]], [1, 1, [[0, 1, 1]]]], [[[3, 4, 4]], [1, 1, [[3, 4, 4]]]], [[[9, 4, 8], [1, 6, 4], [6, 4, 0]], [3, 3, [[0, 4, 6], [4, 6, 1], [8, 4, 9]]]]], [[[[1, 0], [1, 0]], [7, 7, [[0, 0], [1, 1]]]], [[[0, 0, 0], [0, 1, 1]], [1, 1, [[0, 0, 0], [0, 1, 1]]]], [[[7, 5, 8], [6, 1, 6], [1, 6, 7]], [6, 8, [[1, 6, 7], [6, 1, 5], [7, 6, 8]]]], [[[4], [3], [0]], [6, 8, [[0, 3, 4]]]], [[[9]], [1, 1, [[9]]]], [[[1, 0, 1]], [1, 1, [[1, 0, 1]]]], [[[0], [0]], [5, 5, [[0, 0]]]], [[[8, 6, 5], [0, 7, 5], [2, 0, 8]], [4, 4, [[2, 0, 8], [0, 7, 5], [8, 6, 5]]]]], [[[[0, 0, 0], [0, 1, 0], [1, 0, 1]], [1, 1, [[0, 0, 0], [0, 1, 0], [1, 0, 1]]]], [[[4, 5], [7, 8], [5, 5]], [5, 5, [[4, 7, 5], [5, 8, 5]]]], [[[2, 3, 7], [7, 8, 3], [2, 9, 9]], [1, 1, [[2, 3, 7], [7, 8, 3], [2, 9, 9]]]], [[[4], [7], [2]], [6, 8, [[2, 7, 4]]]], [[[4]], [1, 1, [[4]]]], [[[0, 3]], [1, 1, [[0, 3]]]], [[[0], [0]], [5, 5, [[0, 0]]]], [[[0, 0], [1, 1]], [1, 1, [[0, 0], [1, 1]]]]], [[[[9, 6, 1], [5, 6, 6], [8, 1, 0]], [3, 3, [[0, 1, 8], [6, 6, 5], [1, 6, 9]]]], [[[9, 4], [2, 1]], [3, 3, [[1, 2], [4, 9]]]], [[[0, 1, 0], [1, 1, 0], [0, 1, 0]], [7, 7, [[0, 0, 0], [1, 1, 1], [0, 1, 0]]]], [[[5, 9, 8]], [1, 1, [[5, 9, 8]]]], [[[3, 8, 5]], [1, 1, [[3, 8, 5]]]], [[[3, 8]], [1, 1, [[3, 8]]]], [[[0, 1, 0]], [1, 1, [[0, 1, 0]]]], [[[6, 7, 5], [1, 9, 6], [6, 4, 6]], [8, 6, [[5, 6, 6], [7, 9, 4], [6, 1, 6]]]]], [[[[3, 4, 2], [2, 8, 2], [1, 8, 5]], [6, 8, [[1, 2, 3], [8, 8, 4], [5, 2, 2]]]], [[[6, 2], [2, 3], [0, 0]], [6, 8, [[0, 2, 6], [0, 3, 2]]]], [[[0, 0, 0], [1, 1, 1], [1, 1, 0]], [2, 2, [[0, 0, 0], [1, 1, 1], [0, 1, 1]]]], [[[0, 4]], [1, 1, [[0, 4]]]], [[[1]], [1, 1, [[1]]]], [[[4, 8]], [1, 1, [[4, 8]]]], [[[9, 1, 9]], [1, 1, [[9, 1, 9]]]], [[[0, 1, 0], [0, 1, 0], [1, 0, 1]], [5, 5, [[0, 0, 1], [1, 1, 0], [0, 0, 1]]]]]]
labels = ["regression: pixel order in the key", "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: pixel order in the key 0 | [8, 6, [[0, 5, 5], [3, 8, 5], [6, 0, 1]]] | [2, 2, [[0, 3, 6], [5, 8, 0], [5, 5, 1]]] | Failed |
| repair trap 1 | [5, 5, [[0, 1, 0], [0, 1, 1]]] | [5, 5, [[0, 1, 0], [0, 1, 1]]] | Passed |
| combined fault 2 | [6, 8, [[0, 1, 1], [0, 0, 0], [1, 0, 1]]] | [4, 4, [[0, 0, 1], [1, 0, 0], [1, 0, 1]]] | Failed |
| control 3 | [2, 2, [[0, 7, 4]]] | [2, 2, [[0, 7, 4]]] | Passed |
| control 4 | [1, 1, [[7]]] | [1, 1, [[7]]] | Passed |
| boundary 5 | [1, 1, [[0, 1, 1]]] | [1, 1, [[0, 1, 1]]] | Passed |
| boundary 6 | [1, 1, [[3, 4, 4]]] | [1, 1, [[3, 4, 4]]] | Passed |
| control 7 | [7, 7, [[0, 4, 8], [4, 6, 4], [6, 1, 9]]] | [3, 3, [[0, 4, 6], [4, 6, 1], [8, 4, 9]]] | Failed |
SHA-256 / 67e3f422853b0df1970a3bee65a702af312e40b238325479826bbe4e02965445
2 / The unsuccessful fix
Exit 1"""Failure Map reference implementation. Python standard library only."""
import json
N = 1
observations = []
def solve(grid):
h = len(grid)
w = len(grid[0])
def src(t, r, c):
return {1: (r, c), 2: (r, w - 1 - c), 3: (h - 1 - r, w - 1 - c), 4: (h - 1 - r, c),
5: (c, r), 6: (h - 1 - c, r), 7: (h - 1 - c, w - 1 - r), 8: (c, w - 1 - r)}[t]
best = None
for t in range(1, 9):
oh, ow = (w, h) if t >= 5 else (h, w)
img = [[grid[src(t, r, c)[0]][src(t, r, c)[1]] for c in range(ow)] for r in range(oh)]
key = (oh, ow, [v for row in img[::-1] for v in row])
if best is None or key < best[0]:
best = (key, t, img)
inverse = {6: 8, 8: 6}.get(best[1], best[1])
return [best[1], inverse, best[2]]
def check(label, actual, expected):
observations.append({"check": label, "actual": actual, "expected": expected, "passed": actual == expected})
fixtures = [[[[[6, 3, 0], [0, 8, 5], [1, 5, 5]], [2, 2, [[0, 3, 6], [5, 8, 0], [5, 5, 1]]]], [[[0, 0], [1, 1], [0, 1]], [5, 5, [[0, 1, 0], [0, 1, 1]]]], [[[1, 0, 1], [1, 0, 0], [0, 0, 1]], [4, 4, [[0, 0, 1], [1, 0, 0], [1, 0, 1]]]], [[[4, 7, 0]], [2, 2, [[0, 7, 4]]]], [[[7]], [1, 1, [[7]]]], [[[0, 1, 1]], [1, 1, [[0, 1, 1]]]], [[[3, 4, 4]], [1, 1, [[3, 4, 4]]]], [[[9, 4, 8], [1, 6, 4], [6, 4, 0]], [3, 3, [[0, 4, 6], [4, 6, 1], [8, 4, 9]]]]], [[[[1, 0], [1, 0]], [7, 7, [[0, 0], [1, 1]]]], [[[0, 0, 0], [0, 1, 1]], [1, 1, [[0, 0, 0], [0, 1, 1]]]], [[[7, 5, 8], [6, 1, 6], [1, 6, 7]], [6, 8, [[1, 6, 7], [6, 1, 5], [7, 6, 8]]]], [[[4], [3], [0]], [6, 8, [[0, 3, 4]]]], [[[9]], [1, 1, [[9]]]], [[[1, 0, 1]], [1, 1, [[1, 0, 1]]]], [[[0], [0]], [5, 5, [[0, 0]]]], [[[8, 6, 5], [0, 7, 5], [2, 0, 8]], [4, 4, [[2, 0, 8], [0, 7, 5], [8, 6, 5]]]]], [[[[0, 0, 0], [0, 1, 0], [1, 0, 1]], [1, 1, [[0, 0, 0], [0, 1, 0], [1, 0, 1]]]], [[[4, 5], [7, 8], [5, 5]], [5, 5, [[4, 7, 5], [5, 8, 5]]]], [[[2, 3, 7], [7, 8, 3], [2, 9, 9]], [1, 1, [[2, 3, 7], [7, 8, 3], [2, 9, 9]]]], [[[4], [7], [2]], [6, 8, [[2, 7, 4]]]], [[[4]], [1, 1, [[4]]]], [[[0, 3]], [1, 1, [[0, 3]]]], [[[0], [0]], [5, 5, [[0, 0]]]], [[[0, 0], [1, 1]], [1, 1, [[0, 0], [1, 1]]]]], [[[[9, 6, 1], [5, 6, 6], [8, 1, 0]], [3, 3, [[0, 1, 8], [6, 6, 5], [1, 6, 9]]]], [[[9, 4], [2, 1]], [3, 3, [[1, 2], [4, 9]]]], [[[0, 1, 0], [1, 1, 0], [0, 1, 0]], [7, 7, [[0, 0, 0], [1, 1, 1], [0, 1, 0]]]], [[[5, 9, 8]], [1, 1, [[5, 9, 8]]]], [[[3, 8, 5]], [1, 1, [[3, 8, 5]]]], [[[3, 8]], [1, 1, [[3, 8]]]], [[[0, 1, 0]], [1, 1, [[0, 1, 0]]]], [[[6, 7, 5], [1, 9, 6], [6, 4, 6]], [8, 6, [[5, 6, 6], [7, 9, 4], [6, 1, 6]]]]], [[[[3, 4, 2], [2, 8, 2], [1, 8, 5]], [6, 8, [[1, 2, 3], [8, 8, 4], [5, 2, 2]]]], [[[6, 2], [2, 3], [0, 0]], [6, 8, [[0, 2, 6], [0, 3, 2]]]], [[[0, 0, 0], [1, 1, 1], [1, 1, 0]], [2, 2, [[0, 0, 0], [1, 1, 1], [0, 1, 1]]]], [[[0, 4]], [1, 1, [[0, 4]]]], [[[1]], [1, 1, [[1]]]], [[[4, 8]], [1, 1, [[4, 8]]]], [[[9, 1, 9]], [1, 1, [[9, 1, 9]]]], [[[0, 1, 0], [0, 1, 0], [1, 0, 1]], [5, 5, [[0, 0, 1], [1, 1, 0], [0, 0, 1]]]]]]
labels = ["regression: pixel order in the key", "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: pixel order in the key 0 | [3, 3, [[5, 5, 1], [5, 8, 0], [0, 3, 6]]] | [2, 2, [[0, 3, 6], [5, 8, 0], [5, 5, 1]]] | Failed |
| repair trap 1 | [8, 6, [[0, 1, 1], [0, 1, 0]]] | [5, 5, [[0, 1, 0], [0, 1, 1]]] | Failed |
| combined fault 2 | [1, 1, [[1, 0, 1], [1, 0, 0], [0, 0, 1]]] | [4, 4, [[0, 0, 1], [1, 0, 0], [1, 0, 1]]] | Failed |
| control 3 | [2, 2, [[0, 7, 4]]] | [2, 2, [[0, 7, 4]]] | Passed |
| control 4 | [1, 1, [[7]]] | [1, 1, [[7]]] | Passed |
| boundary 5 | [1, 1, [[0, 1, 1]]] | [1, 1, [[0, 1, 1]]] | Passed |
| boundary 6 | [1, 1, [[3, 4, 4]]] | [1, 1, [[3, 4, 4]]] | Passed |
| control 7 | [2, 2, [[8, 4, 9], [4, 6, 1], [0, 4, 6]]] | [3, 3, [[0, 4, 6], [4, 6, 1], [8, 4, 9]]] | Failed |
SHA-256 / 8adc5786ace7e2678d6df17858882eb0764779e4d79e70b7a1496f79ca135cd5
HELD IN THE MEMBER ARCHIVE
The verified repair and its recorded checks are member-only.
This mechanism has 8 recorded checks per implementation. The open-access tier publishes the failure and the unsuccessful fix; the repaired source that passes every check, and the observations that prove it, are available to members.
Every case sharing this mechanism uses the same contract and the same repair, so this one record is held back for all of them.
Member access is invitation-based. Sign in with your invited account to inspect the repair.
Sign in to the archive ↗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 2026-09-29T14:49:43.196618+00:00.
Case digest / 2028524916a62f27a4e0f23c9397126c2cce1fb96df234d7ce1f647c5e0d3f15