FA-79016 / Image orientation metadata / Open access
Out-of-range EXIF orientation overrides XMP · case 01
An EXIF value of 0 or 9 is passed to the renderer even though a valid XMP orientation exists.
ROOT CAUSE
The EXIF value is accepted without checking the 1..8 range, so fallback never happens.
VERIFIED REPAIR
Accept EXIF only for integers 1..8 and otherwise continue to XMP.
Unsuccessful approach: A truthiness check still accepts 9 and even the boolean True.
Case contract
Resolve the displayed orientation tag from metadata sources. For HEIF, the container transforms are authoritative and EXIF/XMP are ignored: irot is anticlockwise quarter turns (default 0) applied first, then imir mirrors about the vertical axis (0, left-right) or the horizontal axis (1, top-bottom); the result is mapped to a tag through (k clockwise quarter turns after m mirrors) = {(0,0):1, (0,1):2, (2,0):3, (2,1):4, (3,1):5, (1,0):6, (1,1):7, (3,0):8}. For other containers a valid integer EXIF value 1..8 wins; otherwise an XMP string that is a single digit 1..8 after trimming whitespace; otherwise 1.
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(meta):
from_km = {(0, 0): 1, (0, 1): 2, (2, 0): 3, (2, 1): 4, (3, 1): 5, (1, 0): 6, (1, 1): 7, (3, 0): 8}
c = meta.get('container')
if c == 'heif':
rot = meta.get('irot')
mir = meta.get('imir')
rot = 0 if rot is None else rot % 4
if mir is None:
return from_km[((-rot) % 4, 0)]
if mir == 0:
return from_km[(rot, 1)]
return from_km[((rot + 2) % 4, 1)]
e = meta.get('exif')
if isinstance(e, int) and not isinstance(e, bool):
return e
x = meta.get('xmp')
if isinstance(x, str):
s = x.strip()
if s in ('1', '2', '3', '4', '5', '6', '7', '8'):
return int(s)
return 1
def check(label, actual, expected):
observations.append({"check": label, "actual": actual, "expected": expected, "passed": actual == expected})
fixtures = [[[{'container': 'jpeg', 'exif': 0, 'xmp': '\t5'}, 5], [{'container': 'tiff', 'exif': True, 'xmp': '7 '}, 7], [{'container': 'tiff', 'exif': 9, 'xmp': '6'}, 6], [{'container': 'png'}, 1], [{'container': 'jpeg', 'xmp': '2'}, 2], [{'container': 'heif', 'xmp': '\t5', 'irot': 3}, 6], [{'container': 'tiff'}, 1], [{'container': 'jpeg', 'exif': 9}, 1]], [[{'container': 'jpeg', 'exif': 0}, 1], [{'container': 'jpeg', 'exif': True, 'xmp': '\t5'}, 5], [{'container': 'jpeg', 'exif': 9, 'irot': 2}, 1], [{'container': 'png', 'xmp': '3\n'}, 3], [{'container': 'jpeg', 'xmp': '3\n'}, 3], [{'container': 'heif', 'exif': 5, 'xmp': ' 8', 'imir': 0}, 2], [{'container': 'heif', 'exif': 3, 'xmp': 'x', 'irot': 0}, 1], [{'container': 'jpeg', 'exif': 0, 'xmp': '6'}, 6]], [[{'container': 'jpeg', 'exif': 9, 'xmp': ' 8'}, 8], [{'container': 'jpeg', 'exif': True, 'xmp': '3\n', 'irot': 3, 'imir': 0}, 3], [{'container': 'png', 'exif': 9, 'xmp': '2'}, 2], [{'container': 'tiff'}, 1], [{'container': 'jpeg'}, 1], [{'container': 'heif', 'exif': 6, 'xmp': 'x', 'irot': 2}, 3], [{'container': 'png', 'exif': 1}, 1], [{'container': 'jpeg', 'exif': 0}, 1]], [[{'container': 'jpeg', 'exif': 9, 'xmp': '0', 'irot': 0}, 1], [{'container': 'png', 'exif': 9, 'xmp': ' 8'}, 8], [{'container': 'jpeg', 'exif': 9}, 1], [{'container': 'jpeg', 'exif': 1}, 1], [{'container': 'heif', 'exif': 1, 'xmp': '7 ', 'irot': 2}, 3], [{'container': 'heif', 'xmp': '\t5'}, 1], [{'container': 'jpeg', 'xmp': '7 '}, 7], [{'container': 'jpeg', 'exif': 0, 'xmp': '6'}, 6]], [[{'container': 'tiff', 'exif': 9}, 1], [{'container': 'jpeg', 'exif': 9}, 1], [{'container': 'png', 'exif': 9, 'irot': 3, 'imir': 1}, 1], [{'container': 'png', 'xmp': '7 '}, 7], [{'container': 'heif', 'irot': 2}, 3], [{'container': 'heif', 'xmp': ' 8', 'irot': 1}, 8], [{'container': 'jpeg', 'xmp': 'x'}, 1], [{'container': 'jpeg', 'exif': 9, 'xmp': '2'}, 2]]]
labels = ["regression: EXIF value validation", "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: EXIF value validation 0 | 0 | 5 | Failed |
| repair trap 1 | 7 | 7 | Passed |
| combined fault 2 | 9 | 6 | Failed |
| control 3 | 1 | 1 | Passed |
| control 4 | 2 | 2 | Passed |
| boundary 5 | 6 | 6 | Passed |
| boundary 6 | 1 | 1 | Passed |
| control 7 | 9 | 1 | Failed |
SHA-256 / 94bde50e3c0fd7637cc5dd5437b8b61c9be753a0d28609b6a47f5b1210c83009
2 / The unsuccessful fix
Exit 1"""Failure Map reference implementation. Python standard library only."""
import json
N = 1
observations = []
def solve(meta):
from_km = {(0, 0): 1, (0, 1): 2, (2, 0): 3, (2, 1): 4, (3, 1): 5, (1, 0): 6, (1, 1): 7, (3, 0): 8}
c = meta.get('container')
if c == 'heif':
rot = meta.get('irot')
mir = meta.get('imir')
rot = 0 if rot is None else rot % 4
if mir is None:
return from_km[((-rot) % 4, 0)]
if mir == 0:
return from_km[(rot, 1)]
return from_km[((rot + 2) % 4, 1)]
e = meta.get('exif')
if e:
return e
x = meta.get('xmp')
if isinstance(x, str):
s = x.strip()
if s in ('1', '2', '3', '4', '5', '6', '7', '8'):
return int(s)
return 1
def check(label, actual, expected):
observations.append({"check": label, "actual": actual, "expected": expected, "passed": actual == expected})
fixtures = [[[{'container': 'jpeg', 'exif': 0, 'xmp': '\t5'}, 5], [{'container': 'tiff', 'exif': True, 'xmp': '7 '}, 7], [{'container': 'tiff', 'exif': 9, 'xmp': '6'}, 6], [{'container': 'png'}, 1], [{'container': 'jpeg', 'xmp': '2'}, 2], [{'container': 'heif', 'xmp': '\t5', 'irot': 3}, 6], [{'container': 'tiff'}, 1], [{'container': 'jpeg', 'exif': 9}, 1]], [[{'container': 'jpeg', 'exif': 0}, 1], [{'container': 'jpeg', 'exif': True, 'xmp': '\t5'}, 5], [{'container': 'jpeg', 'exif': 9, 'irot': 2}, 1], [{'container': 'png', 'xmp': '3\n'}, 3], [{'container': 'jpeg', 'xmp': '3\n'}, 3], [{'container': 'heif', 'exif': 5, 'xmp': ' 8', 'imir': 0}, 2], [{'container': 'heif', 'exif': 3, 'xmp': 'x', 'irot': 0}, 1], [{'container': 'jpeg', 'exif': 0, 'xmp': '6'}, 6]], [[{'container': 'jpeg', 'exif': 9, 'xmp': ' 8'}, 8], [{'container': 'jpeg', 'exif': True, 'xmp': '3\n', 'irot': 3, 'imir': 0}, 3], [{'container': 'png', 'exif': 9, 'xmp': '2'}, 2], [{'container': 'tiff'}, 1], [{'container': 'jpeg'}, 1], [{'container': 'heif', 'exif': 6, 'xmp': 'x', 'irot': 2}, 3], [{'container': 'png', 'exif': 1}, 1], [{'container': 'jpeg', 'exif': 0}, 1]], [[{'container': 'jpeg', 'exif': 9, 'xmp': '0', 'irot': 0}, 1], [{'container': 'png', 'exif': 9, 'xmp': ' 8'}, 8], [{'container': 'jpeg', 'exif': 9}, 1], [{'container': 'jpeg', 'exif': 1}, 1], [{'container': 'heif', 'exif': 1, 'xmp': '7 ', 'irot': 2}, 3], [{'container': 'heif', 'xmp': '\t5'}, 1], [{'container': 'jpeg', 'xmp': '7 '}, 7], [{'container': 'jpeg', 'exif': 0, 'xmp': '6'}, 6]], [[{'container': 'tiff', 'exif': 9}, 1], [{'container': 'jpeg', 'exif': 9}, 1], [{'container': 'png', 'exif': 9, 'irot': 3, 'imir': 1}, 1], [{'container': 'png', 'xmp': '7 '}, 7], [{'container': 'heif', 'irot': 2}, 3], [{'container': 'heif', 'xmp': ' 8', 'irot': 1}, 8], [{'container': 'jpeg', 'xmp': 'x'}, 1], [{'container': 'jpeg', 'exif': 9, 'xmp': '2'}, 2]]]
labels = ["regression: EXIF value validation", "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: EXIF value validation 0 | 5 | 5 | Passed |
| repair trap 1 | True | 7 | Failed |
| combined fault 2 | 9 | 6 | Failed |
| control 3 | 1 | 1 | Passed |
| control 4 | 2 | 2 | Passed |
| boundary 5 | 6 | 6 | Passed |
| boundary 6 | 1 | 1 | Passed |
| control 7 | 9 | 1 | Failed |
SHA-256 / ee169ac611a7e2366772a1e95c2a2ee2d4218ebc07984c930af526e26c0e5ad8
3 / The verified repair
Exit 0"""Failure Map reference implementation. Python standard library only."""
import json
N = 1
observations = []
def solve(meta):
from_km = {(0, 0): 1, (0, 1): 2, (2, 0): 3, (2, 1): 4, (3, 1): 5, (1, 0): 6, (1, 1): 7, (3, 0): 8}
c = meta.get('container')
if c == 'heif':
rot = meta.get('irot')
mir = meta.get('imir')
rot = 0 if rot is None else rot % 4
if mir is None:
return from_km[((-rot) % 4, 0)]
if mir == 0:
return from_km[(rot, 1)]
return from_km[((rot + 2) % 4, 1)]
e = meta.get('exif')
if isinstance(e, int) and not isinstance(e, bool) and 1 <= e <= 8:
return e
x = meta.get('xmp')
if isinstance(x, str):
s = x.strip()
if s in ('1', '2', '3', '4', '5', '6', '7', '8'):
return int(s)
return 1
def check(label, actual, expected):
observations.append({"check": label, "actual": actual, "expected": expected, "passed": actual == expected})
fixtures = [[[{'container': 'jpeg', 'exif': 0, 'xmp': '\t5'}, 5], [{'container': 'tiff', 'exif': True, 'xmp': '7 '}, 7], [{'container': 'tiff', 'exif': 9, 'xmp': '6'}, 6], [{'container': 'png'}, 1], [{'container': 'jpeg', 'xmp': '2'}, 2], [{'container': 'heif', 'xmp': '\t5', 'irot': 3}, 6], [{'container': 'tiff'}, 1], [{'container': 'jpeg', 'exif': 9}, 1]], [[{'container': 'jpeg', 'exif': 0}, 1], [{'container': 'jpeg', 'exif': True, 'xmp': '\t5'}, 5], [{'container': 'jpeg', 'exif': 9, 'irot': 2}, 1], [{'container': 'png', 'xmp': '3\n'}, 3], [{'container': 'jpeg', 'xmp': '3\n'}, 3], [{'container': 'heif', 'exif': 5, 'xmp': ' 8', 'imir': 0}, 2], [{'container': 'heif', 'exif': 3, 'xmp': 'x', 'irot': 0}, 1], [{'container': 'jpeg', 'exif': 0, 'xmp': '6'}, 6]], [[{'container': 'jpeg', 'exif': 9, 'xmp': ' 8'}, 8], [{'container': 'jpeg', 'exif': True, 'xmp': '3\n', 'irot': 3, 'imir': 0}, 3], [{'container': 'png', 'exif': 9, 'xmp': '2'}, 2], [{'container': 'tiff'}, 1], [{'container': 'jpeg'}, 1], [{'container': 'heif', 'exif': 6, 'xmp': 'x', 'irot': 2}, 3], [{'container': 'png', 'exif': 1}, 1], [{'container': 'jpeg', 'exif': 0}, 1]], [[{'container': 'jpeg', 'exif': 9, 'xmp': '0', 'irot': 0}, 1], [{'container': 'png', 'exif': 9, 'xmp': ' 8'}, 8], [{'container': 'jpeg', 'exif': 9}, 1], [{'container': 'jpeg', 'exif': 1}, 1], [{'container': 'heif', 'exif': 1, 'xmp': '7 ', 'irot': 2}, 3], [{'container': 'heif', 'xmp': '\t5'}, 1], [{'container': 'jpeg', 'xmp': '7 '}, 7], [{'container': 'jpeg', 'exif': 0, 'xmp': '6'}, 6]], [[{'container': 'tiff', 'exif': 9}, 1], [{'container': 'jpeg', 'exif': 9}, 1], [{'container': 'png', 'exif': 9, 'irot': 3, 'imir': 1}, 1], [{'container': 'png', 'xmp': '7 '}, 7], [{'container': 'heif', 'irot': 2}, 3], [{'container': 'heif', 'xmp': ' 8', 'irot': 1}, 8], [{'container': 'jpeg', 'xmp': 'x'}, 1], [{'container': 'jpeg', 'exif': 9, 'xmp': '2'}, 2]]]
labels = ["regression: EXIF value validation", "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: EXIF value validation 0 | 5 | 5 | Passed |
| repair trap 1 | 7 | 7 | Passed |
| combined fault 2 | 6 | 6 | Passed |
| control 3 | 1 | 1 | Passed |
| control 4 | 2 | 2 | Passed |
| boundary 5 | 6 | 6 | Passed |
| boundary 6 | 1 | 1 | Passed |
| control 7 | 1 | 1 | Passed |
SHA-256 / fd3174c38668f960eeacdaa7662e58e2eafe6a6aa81bccb0fec574d808a9a97e
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 2026-09-29T14:49:40.520664+00:00.
Case digest / f9e39629f66de8c44fbf3f4d9b97d30ee62c6085288e5913dc8b28fb50afa24b