feat: a report that shows what the near-dup gates decide about real artwork (4223)

The three pixel constants added with the #4223 fix were chosen without ever
measuring real files — CI only has synthetic split/solid fixtures, and FC
verifies nowhere else. This prints the measurements they should have been
chosen from: per pair, the hash distance, the mean drift, the changed-pixel
fraction, the verdict, and which gate produced it.

It drives the real find_similar with the real confirm rather than restating
the decision, so it cannot drift from what the importer does. Read-only:
opens files, touches no database.

Also splits fingerprint_diff out of fingerprints_match — same computation,
now returning the numbers instead of only the boolean, so the report can show
how far a pair sat from a limit rather than which side of it it fell on.

Runs inside the published :dev image (PIL + imagehash already there, no local
env needed) with the art folder mounted read-only — rule 147's channel, so
nothing has to reach main to be tried.

Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01LVjrnpQjRgHdvq95rASoiR

backend/app/utils/phash.py

@@ -122,6 +122,31 @@ def fingerprint_path(path) -> Image.Image | None:
         return None
 
 
+def fingerprint_diff(
+    a, b, *, changed_level: int = FINGERPRINT_CHANGED_LEVEL,
+) -> tuple[float, float] | None:
+    """(mean absolute difference, fraction of pixels past `changed_level`) for
+    two fingerprints. None if either is missing or the comparison fails.
+
+    This is the MEASUREMENT behind `fingerprints_match`, split out so the
+    calibration report (scripts/phash_gate_report.py) can show how far a pair
+    sat from the limits instead of only which side of them it fell on. The
+    constants were chosen without a real-library sample; the numbers this
+    returns are what moves them.
+    """
+    if a is None or b is None:
+        return None
+    try:
+        diff = ImageChops.difference(a, b)
+        hist = diff.histogram()
+        total = sum(hist)
+        if not total:
+            return None
+        return (ImageStat.Stat(diff).mean[0], sum(hist[changed_level:]) / total)
+    except Exception:
+        return None
+
+
 def fingerprints_match(
     a, b,
     *,
@@ -132,20 +157,11 @@ def fingerprints_match(
     """True when two fingerprints are the same picture: no large global
     drift AND no meaningful local region that differs. False on any
     failure."""
-    if a is None or b is None:
-        return False
-    try:
-        diff = ImageChops.difference(a, b)
-        if ImageStat.Stat(diff).mean[0] > max_mean_diff:
-            return False
-        hist = diff.histogram()
-        total = sum(hist)
-        if not total:
-            return False
-        changed = sum(hist[changed_level:])
-        return (changed / total) <= max_changed_fraction
-    except Exception:
+    measured = fingerprint_diff(a, b, changed_level=changed_level)
+    if measured is None:
         return False
+    mean, changed_fraction = measured
+    return mean <= max_mean_diff and changed_fraction <= max_changed_fraction
 
 
 def aspect_matches(